Date Submitted Full Name(s) of Founder(s) - Founder Name Email Id(s) - Email Address LinkedIn Profile(s) - LinkedIn Profile Founders’ Website link(s) - Link WhatsApp Number - Include country code Role(s) and Background How did you meet and how long have you worked together? How many founders are working full time on this startup? What’s your biggest strength as a team? Startup Name Website (if any) Which city is your startup based? Brief description of your startup What problem are you solving? Describe your solution What makes your solution unique or defensible? What is your current stage? Current traction Who are your target customers? Market size estimation - TAM (Total Addressable Market) SAM (Serviceable Addressable Market) SOM (Serviceable Obtainable Market) What is your revenue model? Who are your main competitors? How do you acquire customers? What is your go-to-market strategy? What’s your long-term vision? Incorporation status How much funding have you raised (if any)? Are you open to any equity model? Why are you applying to IITACB Incubator? What do you want to achieve during the programme? Are you open to virtual participation? How can you leverage the $16bn Bommasandra industry hub and Bangalore markets and how can IIT ACB help you? Would you like to rent seats in IITACB Incubator if you are selected for mentoring and investor-connect? How do you wish to leverage IITACB infrastructure and facilites when you rent seats in this Incubator? Are you building startup? How is AI or any deep-tech integrated into your product? Do you have IP? Describe your architecture What proprietary data advantage (if any) do you have? What makes your solution defensible against competitors? How do you evaluate your technology from performance & reliability stadpoint in comparison to your competition etc.? (metrics used?) How do you handle data privacy, compliance,security and other similar kind of concerns around your product?? Are there any policy interventions that help your business (if any) Are there any regulatory risks that could impact your product? What will break in your system if you scale 10x? Do you have an in-house deep-tech team? If yes, describe expertise. What datasets, open source codes and components are you currently using? Are they licensed, open or owned? Share your IP reference if you have any? How do you plan to continuously improve your technology performance? Are you building for India, global markets, or both? Pitch Deck(s) - CAUTION - overall size of all files should be less than 8MB Demo video link Are you building a mission-driven or impact-focused startup? Tell us more. Are you part of an underrepresented group in tech/startups? Referred by Additional information if any NOTE - Declaration
Sep 1, 2026 @ 10:56 AM Vy Nhat Nguyen brokazy1@gmail.com https://www.linkedin.com/in/vy-nguyen-559903251 https://www.linkedin.com/in/vy-nguyen-559903251 +16282189939 Founder and CEO We met and knew each other for almost 4 years till now 2 We have the advantage in which others do not have much experience in to support each other. I am good at financial analysis, business model formation and Akansha is good at her relationship with clients, other investors Veer https://veer-story-unfold.vercel.app/ New Delhi, India Veer, an ultra high quality bespoke Indian car brand with significant exclusive signature design representing for Indian culture and powered with AI for autonomous self-driving enhancement. The deficiency in extended wheelbase ultra high quality Indian car brand with exclusive signature design representing for Indian culture to adapt demand upgrading higher driving standard for clients from both India and global market Veer is a bespoke ultra high quality Indian car manufacture with exclusive signature design representing the Indian culture which produce only 1 signature design ultra high quality car. The unit price of each car will be around 200K USD and the price will have a principle of order placing rule to keep the price year over year from the later production model must be higher than the previous model. Anyway, "Veer" has one model version to order every year only but the quantity to produce is unlimited according to the actual number of order placement in reality will reflect the total sold cars a year The unique utilities for interior appliance and signature design from physical appearance of exterior are all the solution to make this product attractive enough Idea 1000000 300000 100000 Bespoke customize on demand sale NA as I consider other same industry companies as the benchmark to study from their success. We have different customer segment in a niche price for a discriminated signature design B2B client from high-end transportation service and B2C from direct sale NA Future of modern vehicle will be powored with AI for autonomous sel-driving ability enhancement NA NA Yes I want to attend the IITACB Incubator not only to get assistance from human resources distribution but for financial funding assistance in an instant capital line from priavte channel; I want to complete raising enough 5 million USD for 12 % equity from the pre-seed funding round. Then, if possible, I want to accelerate continue raise 35 million USD for the series A round and more than 100million USD for the series B round Yes, I am opened to virtual attendance I want to obtain the instant capital line in distribution according to all our provable submiited invoice to help shorten the grow timeline Yes Yes, I wish to use IITACB infrastructure to work with other team members from RnD team in India, including oline and offline apart from our main hub in New Delhi Yes Core engine Veer, an ultra high quality bespoke Indian car brand with significant exclusive signature design representing for Indian culture and powered with AI for autonomous self-driving enhancement. Data high concern of accuracy and cyber security is the matter that team must spend more efforts in deploying our own AI model for self-driving ability as well as to integrate from other 3rd party service if needed. Veer has unique signature design representing for Indian visual language plus all exclusive utilities, appliances from the interior Our RnD and tech team must work really hard to handle data privacy management, cyber security resolution and Veer must be very selective when choose other 3rd party with signed contract NDA to reach high compliance in security from integration If possible, I would need India government support by modifying some program to support optimizing the cost of production The supply chain of input material, replaceble components Input production materials, imported components will be a challenge Yes, Veer must build an in-house deep tech team for RnD including AI / Machine Learning, Autonomous Driving / ADAS, Robotics / Vehicle Dynamics / Controls, Sensor / Hardware / Electronics, Embedded / Vehicle Software, Battery / Energy / Power Electronics, Vehicle Computing / Semiconductor, Systems Engineering + Functional Safety, Testing / Simulation / Validation Veer prefer to use signed licensed source code of other 3rd party provider for cyber security compliance. Veer must have the legal team to take care on IP registration Continuous reinvest money from free cash flow generated or capital raise into RnD with actual feedback from client's driving experience will be the definite answer to keep pushing up the improvement of technology performance I am building Veer with the main factory, assembly & test plant in India to serve India and global market 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/gz2aIqNQgXx6-Veer.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/gz2aIqNQgXx6-Veer.pdf https://drive.google.com/file/d/1cTxPKI-z15TyVDmj7CfwxhO4MLQLNmXr/view?usp=sharing Yes I am building a mission driven startup to deploy autonomous self-driving enhancement for vehicle transformation in India. This is also an impact focused in cultural value where the signature design from both interior and exterior must outperform from validation NA NA checked
Aug 28, 2026 @ 12:37 PM Atul Jaiswal atuljaiswal1246@gmail.com https://www.linkedin.com/in/atul-jaiswal/ https://project-jarvis-iron-man.netlify.app/ +919315098482 Founder, Product Management, Marketing & Development We are husband and wife 1 The biggest strength is there's no overhead cost, all work is done by AI. J.A.R.V.I.S https://project-jarvis-iron-man.netlify.app/ Bengaluru Project JARVIS is an early-stage concept for J.A.R.V.I.S. OS, an AI-native operating system that can be installed on personal computers. Unlike conventional operating systems with a separate assistant, J.A.R.V.I.S. OS is designed so deeply around AI that the operating system and its intelligence function as one integrated system. Current operating systems are built around applications, menus, files, and manual workflows, while AI assistants are usually separate layers added afterward. Users need a more natural and personal computing experience in which the operating system itself understands intent, adapts to the user, and helps manage the computer privately and efficiently. J.A.R.V.I.S. OS will integrate an efficient AI directly into the operating system. Users will interact with the computer through natural language, voice, applications, files, and approved internet sources. The OS will manage permissions, remember user-approved context, learn from interaction, and adapt to individual needs over time. It will be designed to run locally on different classes of laptops, with optional cloud capabilities where appropriate. The AI is not a separate assistant installed on the OS—the AI is the operating system’s core interface and intelligence. J.A.R.V.I.S. OS is an AI-native operating-system concept rather than a chatbot or an assistant layered on top of an existing OS. Its differentiation is the deep integration of AI with system operations, privacy-focused local processing, efficient hardware use, permission-controlled actions, adaptive personal memory, and support for approved internet and application workflows. The same OS can become personalized for each user through accumulated context, preferences, and experience. Idea Initial target customers are privacy-conscious laptop users, developers, students, independent professionals, and accessibility-focused users who want a more natural and personalized way to operate their computers. The broader target market is anyone who wants an intelligent operating system that adapts to their individual needs. NA — detailed market validation is pending because the project is currently at the ideation stage. NA — the initial serviceable market will be defined after customer discovery and prototype validation. NA — the obtainable market will be estimated after identifying the first customer segment and conducting pilot testing. The revenue model is still being validated. Potential models include a paid operating-system license, optional subscription services for cloud-enhanced capabilities, enterprise deployments, and support or integration services. There is currently no revenue. Existing operating systems such as macOS, Windows, and Linux; AI assistants such as ChatGPT, Claude, Gemini, Copilot, and Apple Intelligence; and emerging AI-native computer interfaces. J.A.R.V.I.S. OS aims to differentiate itself by making AI the core of the operating system rather than adding an assistant as a separate feature. Initial customers will be reached through developer and privacy-focused communities, open-source channels, incubator networks, early-access programs, university partnerships, and controlled pilot deployments. Customer acquisition will begin with users who are willing to test and shape an early AI-native operating system. Begin with a local prototype and validate it with a small group of early adopters. Use their feedback to improve the operating system, privacy controls, hardware compatibility, and personalisation features. Then launch an open beta, build a developer ecosystem, and explore partnerships with hardware manufacturers, institutions, and enterprise users. Our long-term vision is to create J.A.R.V.I.S. OS, an AI-native operating system that can run on different classes of personal computers. The AI will be deeply integrated into the operating system so that users can interact naturally with their computer, while the system learns from approved experience and adapts to individual needs. We aim to build a private, efficient, and genuinely personal computing platform that grows with each user. Not incorporated yet. Project JARVIS is currently an ideation-stage concept with an early software proof-of-concept developed through founder-led experimentation. ₹0. The project is currently bootstrapped, and no external funding has been raised. Yes I am applying to IITACB to receive expert mentorship, validate the J.A.R.V.I.S. OS concept, develop a practical prototype roadmap, understand the technical and hardware requirements, and identify suitable grants or early-stage funding. IITACB’s technology, startup, mentor, and investor network could help transform this idea into a viable AI-native operating-system project. I want to validate the core concept, define the operating-system architecture, develop an initial installable prototype, test the system on suitable hardware, conduct early user discovery, refine the privacy and personalisation model, and prepare a clear path toward incorporation, grants, and future investment. Yes. I am open to virtual participation during the ideation and mentoring stages and can attend important in-person meetings, workshops, and demonstrations when required. J.A.R.V.I.S. OS is a technology product that can benefit from Bengaluru’s AI, software, hardware, electronics, enterprise, and startup ecosystem. The Bommasandra industrial hub and Bengaluru market could provide access to technical talent, hardware and systems expertise, early adopters, pilot partners, and potential industry collaborations. IITACB could help through mentorship, technical validation, introductions to relevant companies and experts, prototype guidance, investor access, and connections with potential pilot users. Yes If selected for seat-based incubation, I would use the infrastructure for product development, technical mentoring, system testing, research collaboration, demonstrations, and interaction with mentors, investors, and potential pilot partners. Yes Core engine The current proof-of-concept uses a Go-based application and a React/TypeScript interface, with Ollama providing a local model-provider layer. The runtime is designed to remain independent of the selected AI model and manages tool execution, permissions, task limits, visible results, and recovery. Local voice processing uses whisper.cpp/Whisper, with AVFoundation and WebKit used for macOS audio and application integration. The proposed J.A.R.V.I.S. OS architecture will integrate local AI, system services, approved tools, personal memory, application control, and privacy controls into one AI-native operating-system layer. We currently do not claim a proprietary dataset or data moat. The project is at the ideation and early proof-of-concept stage. Our planned advantage is user-controlled, on-device personal context and memory that remains private and helps each installation adapt to its user over time. Any future learning data will be collected only with user consent and will not be treated as proprietary unless legally and ethically appropriate. The current defensibility hypothesis is based on deep systems integration rather than a proprietary dataset. J.A.R.V.I.S. OS aims to combine efficient local AI, model-independent task execution, permission-controlled system actions, personal memory, privacy safeguards, application integrations, and continuous user adaptation. The same base technology can become meaningfully different for each user through local context and approved experience. Formal IP protection and commercial defensibility are still being evaluated. Early evaluation has focused on functional reliability, including successful tool execution, permission denial, cancellation, visible tool results, file read-back, voice transcription, and recovery from failed operations. Formal comparative benchmarks are still pending. Planned metrics include task-completion rate, model and tool latency, transcription accuracy, false-action rate, permission failures, crash rate, CPU/RAM usage, battery and thermal impact, and performance across different hardware configurations. J.A.R.V.I.S. is designed as a local-first system. AI inference, voice processing, memory, and personal data should remain on the device whenever possible. External network access will be optional and permission-controlled. System actions will use least-privilege tools, explicit paths, visible results, and approval gates for consequential operations. The project will follow data minimisation, user consent, retention controls, and secure handling principles. A formal legal and compliance review is still required before commercial distribution. Relevant support may include government and institutional grants for AI, deep-tech, software, and prototype development; technology incubators; university research collaborations; startup recognition; access to testing infrastructure; and programmes supporting privacy-preserving and locally deployable AI. No specific policy support has been secured yet. Potential risks include privacy and data-protection requirements, cybersecurity obligations, AI safety and transparency expectations, operating-system and accessibility permissions, software and model licensing, third-party intellectual-property rights, and App Store or platform distribution rules. These risks will be assessed as the product moves from proof-of-concept to a distributable operating system. The main risks are local inference latency, RAM and storage requirements, thermal and battery impact, hardware and driver compatibility, model reliability during multi-step tasks, permission complexity, application integration maintenance, personal-memory storage, and support across different devices. The architecture will need profiling, modular services, hardware-specific optimisation, stronger testing, and clear recovery controls. Currently, the project is founder-led and does not yet have a dedicated in-house deep-tech team. The next stage requires support from experts in operating systems, local AI optimisation, computer systems, cybersecurity, human-computer interaction, voice technology, and product engineering. The current proof-of-concept uses the open-source Ollama codebase, Go, React/TypeScript, WebKit, AVFoundation, whisper.cpp/Whisper components, and local AI models such as Qwen. Component and model licenses vary and are being audited separately before any redistribution. We currently do not own a proprietary dataset or claim registered intellectual property. The public project repository is available at: https://github.com/atuljaiswal1246/Project-JARVIS We will use hardware benchmarking, profiling, regression testing, crash monitoring, voice-accuracy testing, task-completion measurements, and user feedback. Improvements will focus on efficient local inference, memory and thermal usage, model routing, faster tool execution, hardware compatibility, privacy controls, and reliable recovery from failures. Both. India will be an important starting market for validation because of its large and diverse user base, strong software ecosystem, and need for affordable and accessible computing. The underlying need for a private, adaptive, AI-native operating system is global, so the long-term product is intended for international users and hardware environments. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/eu24x5k005s2-JARVIS_Pitch_Deck.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/eu24x5k005s2-JARVIS_Pitch_Deck.pdf http://NA Yes. J.A.R.V.I.S. OS is mission-driven and impact-focused. Its purpose is to make powerful, privacy-conscious computing accessible to individuals and educational institutions, especially students. The OS will be free for personal and educational use. Sustainability will come from commercial licenses, laptop unit sales, B2B customisation, and royalties where applicable. NA Self-referred J.A.R.V.I.S. OS is a mission-driven, student-focused project at the idea and early proof-of-concept stage. We are seeking incubation support, technical mentorship, prototype funding guidance, and access to infrastructure to develop and validate the first version. checked
Aug 28, 2026 @ 5:41 AM Vy Nhat Nguyen brokazy1@gmail.com https://www.linkedin.com/in/vy-nguyen-559903251 https://veer-story-unfold.vercel.app/ (+1)3024847478 Founder & CEO with education background in telecommunication-electronic engineering and fundamental finance analysis for business entrepreneurs We met each other when I am the client of Fluper Limited to ask for the outsourcing contract to build the social investing network connect certified stock brokers with investors/ traders. We knew each other for almost 4 years and I am attending Akansha's wedding party as an international guest 1 I believe the relationship structure between client and C-level of a big outsource company in Noida bring us a huge understanding towards the challenge of starting up and growing business across multi nation market Veer https://veer-story-unfold.vercel.app/ New Delhi, India Veer, an ultra high quality bespoke Indian car brand with significant exclusive signature design representing for Indian culture and powered with AI for autonomous self-driving enhancement The deficiency in extended wheelbase ultra high quality Indian car brand with exclusive signature design representing for Indian culture to adapt demand upgrading higher driving standard for clients from both India and global market Veer is a bespoke ultra high quality Indian car manufacture with exclusive signature design representing the Indian culture which produce only 1 signature design ultra high quality car. The unit price of each car will be around 200K USD and the price will have a principle of order placing rule to keep the price year over year from the later production model must be higher than the previous model. Anyway, "Veer" has one model version to order every year only but the quantity to produce is unlimited according to the actual number of order placement in reality will reflect the total sold cars a year The special utilitiesintegrated inside the car make it be unique from high-quality and ultra luxury segment Idea 950,000 millionaires living in india and a potenbtial breakthrough number of millionaire born around the world who want to pursue extended wheelbase bespoke ultra luxury car with the most affordable price 10,000,000 3,000,000 1,000,000 My revenue models are NA We create the fuel of order placement with in-advance booking before launching the production stage to manage carefully the inventory under control Target the B2B channel distribution for luxury transporting service and approaching to millionaire customer segment who is living in India and other regions across continens Automobile industry will be powered with AI for automation self-drive ability and the higher standard demand of driving experience will come. Not yet incorporated but Veer is willing to incorporate in New Delho 0 Yes I want to share the business idea to invite more attendee, advisor, consultor and experts in India to join this company for the acceleration Yes, I am for sure and I am willing to participate in the pitching session with high frequency to brainstorm and complete the structure of business model in planning to grow quick Veer requires co-join assistance, partnership with almost VC, professional organization in industry across India nation to boost up the deployment of factory operation for official manufacturing. If possible, Veer want to request an instant finance capital line in disbursement to prioritize this project implementation if the council and VC from IITACB believe in the succes and importance of this company Yes I am willing to rent seat whenever my startup receive fund, grants or donation from the angel or preseed round to ensure my company have capital ready to pay for expense at the incubator program from IITACB Yes Core engine Our car model has a concept to have 5 seat with only 1 seat at the front drive and 4 high-quality seat at the main cabin upon an extended wheelbase for space expansion of exclusive experience. The signature design from both interior and exterior of the vehicle is mandatory to ensure adopt high value of car brand I need more assistance, support from IITACB to register all mandatory license for brand secure when grow and scale business across continents It will requires efforts of a big team or whole India nation to accompany for building this Veer model representing for Indian technology and culture My startup is at the first pre-seed funding round with brainstormed business idea so this car concept and potential quality would highly depend on the foundation of automobile structure from India nation of other top successful car brand in India for further validation in the most accurate way. Our company;'s product is the physical properties from automobile where the centric value is in mechanical but the factor of AI empowered for delf-driving automation is inevitable. Data privacy will be handled to secure from signal transfer and method of decoding by top expert team in India and data center will be built in each nation where Veer is distributed to for ensuring the highest cyber security protection There may have and need more help from India government but we can discuss in further during the time we setup and start launch the first batch production for cost optimization in long-term I believe the regulatory risk would be the relation of sustainable cash conversion cycle from the quantity of placement order to the operating expense. In case the design team forecase well to manage at high enough for the profit margin to compensate the manufacturing cost including payroll of labors The supply chain of input materials for manufacture in India and logistic timeline of delivery impact the possibility of scaling rate in reality No, I do not and that is the reason why I want to attend the incubation program in India from IITACB Veer must use our strategic signed on contract for service integration to ensure cyber security control of all source code integrated from the outsider and internal building from algorithm and self-management, maintenance would be more prioritized at all situation RnD department must receivea stable commited fund for recruitment and investing in infrastructure to self-develop the ability of innovation. Those must be calculated and forecasted carefully from the spending of annual free cash flow I am building this Indian car brand in which the company's headquarter and the Giga factory to be placed in New Delhi NCR, India for both domestic and the global market in export 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/oFkX71lclnLw-Veer.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/oFkX71lclnLw-Veer.pdf https://drive.google.com/file/d/1cTxPKI-z15TyVDmj7CfwxhO4MLQLNmXr/view?usp=sharing Yes, it is a mission-driven at national level in India to create an official completed ultra-luxury car representing for Indian culture design language Yes, I must join the RnD team to keep warming up and incubating more idea for the next model NA checked
Aug 27, 2026 @ 2:11 PM Shubham Agrawal shubham.agrawal@crickbro.com https://www.linkedin.com/in/shubham-agrawal-288357129 http://NA +91 999 396 8327 Chief Operating Officer We met through our professional network and started working together on the idea of building a technology-driven cricket platform. Since then, we have worked closely together for a client since 2019, combining our expertise in technology, product development, and cricket operations to build and scale CrickBro. 2 Our biggest strength is our ability to combine strong technology and product execution with a deep understanding of real-world cricket operations. We complement each other’s skills, make decisions quickly, and stay focused on solving practical problems for players, teams, organizers, and cricket stakeholders. This combination allows us to move from an idea to a working product quickly and continuously improve based on real-world feedback. Crickbro Sports Private Limited https://crickbro.com Indore, Madhya Pradesh CrickBro Erp is an Ai Powered Multi-Tenant Architecture based Cloud-Native SaaS. The sports tournament ecosystem is highly fragmented and still relies heavily on spreadsheets, messaging apps, manual coordination and multiple disconnected software tools. Registration, payments, trials, player selection, auctions, scheduling, scoring, streaming, sponsorships and reporting are often managed separately, making tournaments difficult and costly to scale. Players also lack a continuous digital record of their trials, performances, tournament history and achievements, limiting transparent talent discovery and future opportunities. Organizers struggle to manage large player pools, multiple locations and stakeholders efficiently, while sponsors lack integrated and measurable visibility across digital, broadcast and physical channels. CrickBro is an AI Powered, cloud-native SaaS platform for end-to-end sports tournament operations. It acts as a unified operating layer connecting organizers, players, selectors, franchises, sponsors, broadcasters and officials. Crickbro manages the complete tournament lifecycle—from digital registration, payments, trials and player evaluation to auctions, team formation, automated fixtures, live scoring, streaming, broadcast overlays, LED & Linear board displays, sponsorship management and analytics. The platform is designed to transform tournament activity into structured digital data, enabling better talent discovery, performance intelligence, operational automation and scalable sports ecosystems. CrickBro is an end-to-end, automation-first sports operating layer, connecting registration, trials, selection, auctions, tournament operations, live scoring, streaming, sponsorships and analytics on one platform. Its growing player-organizer network and connected data layer create compounding network effects and long-term ecosystem value. MVP Users, Revenue, Pilots CrickBro serves the complete sports ecosystem: Tournament Organizers — End-to-end tournament creation, registration, trials, auctions, scheduling, scoring, streaming, sponsorship and analytics. Players — Tournament opportunities, registrations, trials, auctions, team selection, performance tracking and digital career records. Selectors & Coaches — Structured player evaluation, scoring, rankings, performance analysis and talent identification. Franchises & Team Owners — Player discovery, live auctions, squad building, player management and team performance insights. Match Officials & Crew — Scorers manage real-time ball-by-ball scoring and match statistics; Umpires & Officials manage match assignments, digital workflows and reporting; Commentators access real-time match, player and performance data for professional commentary. Streaming & Broadcast Teams — Live scoring integration, automated overlays, broadcast graphics, sponsor integration and live-stream management. Sponsors & Brands — Integrated visibility across registration platforms, live streams, broadcast overlays, LED boards, stadium branding and digital channels. 5000+ Crore 1500+ Crore 100+ Crore Player Registration, Trials Analystics Subscription, Base Camp Support, Auction Management, Live Streaming, Organizer Subscription, Vendor Subscription, Advertising & Sponsorship, Academy Management, LED Ticker and Graphics CricHeroes is our primary competitor. However CrickBro differentiates itself by building an end-to-end cricket ecosystem covering player registration, trials, auctions, tournament management, scoring, streaming, live overlays, LED boards, vendors, and sponsorships. We acquire customers through a combination of direct sales, partnerships, and grassroots cricket engagement. Our primary entry point is cricket tournament organizers, academies, clubs, and team. Our go-to-market strategy is onboard organizers through direct sales, on-ground demonstrations, cricket-community partnerships, and pilot tournaments. Once an organizer adopts CrickBro, players, teams, scorers, and spectators are brought onto the platform through registration, trials, auctions, live scoring, streaming, and tournament engagement. To become an operating system of cricket, empowering every stakeholder through technology and creating the world's most connected cricket ecosystem. Done - Crickbro Sports Private Limited NA Yes We are particularly looking for mentorship in product-market fit, go-to-market strategy, fundraising, technology scalability, and building partnerships across the sports ecosystem. We believe the IITACB network and guidance can help us transform CrickBro from a promising cricket-tech product into a nationally scalable platform. Our long-term goal is to scale CrickBro across India and create a sustainable, technology-driven ecosystem connecting players, teams, organizers, and the wider cricket community. Yes but I can come and meet F2F also IITACB, we want to access experienced mentors, IIT alumni networks, corporate connections, investor networks, and industry partnerships to accelerate CrickBro’s growth. Yes The incubator workspace would provide our team with a professional environment to work closely, conduct product planning and testing, and meet potential customers, partners, sponsors, and investors Yes Core engine Development and operational tools include Git-based version control, API testing/documentation tools, cloud monitoring, CI/CD workflows and analytics. The architecture is designed to be modular and scalable so that individual services can be optimized independently as the number of tournaments, concurrent users and live matches increases. CrickBro’s data advantage comes from building a structured, continuously growing dataset around grassroots cricke CrickBro is an end-to-end, automation-first sports operating layer, connecting registration, trials, selection, auctions, tournament operations, live scoring, streaming, sponsorships and analytics on one platform. Its growing player-organizer network and connected data layer create compounding network effects and long-term ecosystem value. Our key KPIs include API response time, live-score update latency, scoring accuracy, uptime, crash-free sessions, concurrent users, database response time, streaming stability, notification delivery rate, and recovery time from failures. We apply secure API practices, input validation, logging, monitoring, regular backups, and controlled access to production systems. Yes, Indirectly We see these policy interventions as ecosystem enablers rather than relying on direct subsidies or regulatory benefits. CrickBro aims to contribute to this ecosystem by making grassroots cricket more organized, data-driven, accessible, and technology-enabled. Yes, there are some regulatory and compliance risks, primarily around data privacy, user consent, payment processing, digital content/streaming rights, and the use of player and performance data. We are addressing these risks through privacy-by-design practices, appropriate consent and data-access controls, secure data handling, clear terms and policies, and careful management of third-party integrations. Our current architecture is modular and cloud-ready, but at 10x scale we would need to further optimize database queries, introduce caching and asynchronous processing, strengthen horizontal scaling and load balancing, and improve real-time event infrastructure. We would also scale streaming and media infrastructure independently from the core application. Yes. CrickBro has an in-house technology team with expertise in full-stack application development, mobile app development, backend/API engineering, database management, cloud infrastructure, real-time systems, and third-party integrations. As the product evolves, we plan to further build expertise in AI/ML, predictive analytics, computer vision, and other deep-tech capabilities that can enhance player evaluation, talent discovery, performance analytics, and automated cricket operations. postgresql & RDS open-source libraries/frameworks, cloud infrastructure components, and third-party APIs/services. We plan to continuously improve CrickBro’s technology through a combination of real-world usage data, performance monitoring, automated testing, user feedback, and regular architecture reviews. We will track key metrics such as API response time, live-score latency, uptime, crash-free sessions, scoring accuracy, concurrent users, database performance, and streaming stability. Both 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/YDHUv3BlYlEy-Crickbro_Pitch_Deck_2026.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/YDHUv3BlYlEy-Crickbro_Pitch_Deck_2026.pdf Yes. CrickBro is a mission-driven sports-tech startup focused on making grassroots cricket more organized, accessible, and data-driven. Our mission is to create a connected digital ecosystem that gives players, especially those from Tier 2 and Tier 3 cities, better access to tournaments, trials, selection opportunities, performance data, and visibility to teams, organizers, and scouts. Prefer not to say Ravi Teja checked
Aug 26, 2026 @ 12:08 AM S Theivam theivams203@gmail.com https://www.linkedin.com/in/s-theivam-b85b522a3?utm_source=share_via&utm_content=profile&utm_medium=member_android 9150830779 # Role(s) and Background **SASA NEXTGEN PRIVATE LIMITED** is an innovation-driven startup focused on developing sustainable, technology-enabled and value-added products to address real-world social, agricultural, healthcare and environmental challenges. The startup operates with a strong emphasis on **Food Technology, Biotechnology, Sustainable Product Development, Women-Centric Innovations, Renewable Energy and Smart Technologies**. The team consists of young innovators, student entrepreneurs and mentors with complementary expertise in **research and development, product formulation, food technology, biotechnology, business development, marketing and commercialization**. The startup aims to convert innovative ideas and research outcomes into practical, affordable and market-ready products. SASA NEXTGEN PRIVATE LIMITED is currently working on innovative product concepts including **women-centric wellness products, functional foods, sustainable food technologies and smart cold-chain solutions**. The startup follows an innovation-to-market approach involving **problem identification, research, prototype development, testing, validation, intellectual property protection and commercialization**. The company’s long-term vision is to build a technology-driven enterprise that creates **social impact, sustainable solutions, employment opportunities and commercially viable innovations** while contributing to the **Sustainable Development Goals (SDGs)**. he founding team members of SASA NEXTGEN PRIVATE LIMITED met through their academic and innovation activities at K. S. Rangasamy College of Technology (KSRCT). Our common interest in innovation, entrepreneurship, Food Technology, research and product development brought us together. We have been working together for more than two years, collaborating on various academic projects, product development activities, research initiatives, startup ideas and innovation programs. During this period, we have developed strong teamwork, complementary skills and a shared vision for transforming innovative ideas into practical and commercially viable solutions. Our continued collaboration and experience working together have provided a strong foundation for establishing and developing SASA NEXTGEN PRIVATE LIMITED. 1 Our biggest strength as a team is our complementary skills, strong teamwork and shared vision for innovation. We combine technical knowledge, research capabilities, creativity, problem-solving skills and entrepreneurial thinking to develop practical solutions to real-world problems. We communicate openly, support each other’s ideas and divide responsibilities based on individual strengths. Our ability to learn quickly, adapt to challenges and work together consistently helps us turn innovative concepts into feasible, sustainable and market-ready products. Most importantly, we share a common goal of creating meaningful social, environmental and commercial impact, which keeps our team motivated and focused. SASA NEXTGEN Thanjavur SASA NEXTGEN PRIVATE LIMITED is an innovation-driven startup focused on developing sustainable, technology-enabled and socially impactful products that address real-world challenges. We work across areas including Food Technology, Biotechnology, Women’s Wellness, Functional Foods, Sustainable Product Development, Renewable Energy and Smart Technologies. Our approach is to identify unmet needs, develop innovative solutions through research and product development, and transform them into affordable, practical and market-ready products. Through technology, sustainability and entrepreneurship, SASA NEXTGEN aims to create measurable social and environmental impact while building commercially scalable solutions. SASA NEXTGEN PRIVATE LIMITED is an innovation-driven startup focused on developing sustainable, technology-enabled and socially impactful products that address real-world challenges. We work across areas including Food Technology, Biotechnology, Women’s Wellness, Functional Foods, Sustainable Product Development, Renewable Energy and Smart Technologies. Our approach is to identify unmet needs, develop innovative solutions through research and product development, and transform them into affordable, practical and market-ready products. Through technology, sustainability and entrepreneurship, SASA NEXTGEN aims to create measurable social and environmental impact while building commercially scalable solutions. ### Describe Your Solution Our solution is an **eco-friendly cabbage-based herbal breast pad** designed to provide a natural cooling and soothing effect for women experiencing breast discomfort. The pad uses **cabbage-derived bioactive extracts combined with soft, skin-friendly and absorbent materials** in a multi-layer design. It is reusable, comfortable, affordable, and designed as a sustainable alternative to conventional breast-comfort products, while reducing dependence on synthetic materials. Our solution combines cabbage-derived bioactive compounds with a multi-layer, skin-friendly breast pad design to provide natural cooling and soothing comfort. Its uniqueness lies in the standardized extraction and incorporation of cabbage bioactives, sustainable materials, reusable design, and women-focused product development. The solution can be made defensible through proprietary formulation, extraction methods, product design, processing know-how, and potential intellectual property protection. MVP Testimonials Our primary target customers are women experiencing breast discomfort, breast tenderness, or the need for cooling and soothing breast care, particularly breastfeeding mothers and women seeking natural, reusable, and affordable breast-care products. Secondary customers include women’s wellness clinics, maternity hospitals, pharmacies, healthcare retailers, and e-commerce platform ₹1,000+ crore ₹200–300 crore ₹2–5 crore Our revenue model is primarily direct-to-consumer (D2C) and business-to-business (B2B) sales of our cabbage-based herbal breast pads. Revenue will be generated through individual product sales, multi-pack/bundle sales, and repeat purchases through our website, e-commerce platforms, pharmacies, hospitals, maternity centres, and women’s wellness stores. We will also explore institutional and distributor partnerships to expand market reach and create recurring revenue. ### Who Are Your Main Competitors? Our main competitors are **conventional reusable and disposable breast pads and breast-care products** offered by brands such as **Lansinoh, Medela, Philips Avent, and Pigeon**. These products primarily focus on absorbency, leakage protection, or general breast comfort. Our differentiation is the integration of **cabbage-derived bioactive ingredients, a natural cooling and soothing approach, reusable design, and sustainable materials** in a women-focused breast-care product. We will acquire customers through a combination of social media marketing, influencer and women-focused community outreach, e-commerce platforms, pharmacies, maternity hospitals, and wellness centres. We will create awareness through product demonstrations, educational content, sampling, customer testimonials, and referral programs. Strategic partnerships with healthcare professionals, maternity centres, women’s wellness organizations, and distributors will help build trust and expand our customer base. We will launch the product through a pilot-market approach, initially targeting breastfeeding mothers and women seeking natural, reusable breast-care solutions. We will begin with direct-to-consumer sales through social media and e-commerce platforms, supported by product demonstrations, educational campaigns, sampling, and customer feedback. After validating product-market fit, we will expand through pharmacies, maternity hospitals, women’s wellness centres, distributors, and retail partnerships, followed by wider regional and national expansion. Our long-term vision is to build SASA NEXTGEN PRIVATE LIMITED as a trusted women’s wellness brand that develops natural, sustainable, affordable, and scientifically validated breast-care solutions. We aim to scale our cabbage-based breast pad across India and global markets while continuously developing innovative products from plant-based bioactive ingredients and sustainable materials. Our goal is to improve women’s comfort and wellness while creating value through innovation, sustainability, and responsible product development. SASA NEXTGEN PRIVATE LIMITED is a registered Private Limited Company, incorporated in India and currently in the early-stage product development and commercialization phase. Funding Raised: ₹0 — No external funding raised to date. The startup is currently being supported through founder contributions and available institutional/incubation resources. Yes We are applying to the IITACB Incubator to receive expert mentorship, technical guidance, business support, and industry connections to accelerate the development and commercialization of our cabbage-based herbal breast pad. The incubation support will help us strengthen our product formulation, validation, intellectual property strategy, regulatory compliance, market positioning, and scalable manufacturing. We believe IITACB’s incubation ecosystem can help us transform our innovative concept into a scientifically validated, commercially viable, and scalable women’s wellness product. During the programme, we aim to validate and optimize our cabbage-based herbal breast pad, strengthen its formulation and product design, and conduct the necessary safety, quality, efficacy, and user validation studies. We also want to develop a scalable manufacturing process, strengthen our IP and regulatory strategy, validate the market through pilot sales and customer feedback, and establish industry partnerships. Our goal is to achieve product-market fit and commercial readiness for a successful market launch. Yes. We are open to virtual participation and can actively engage in online mentoring sessions, technical discussions, workshops, reviews, and other programme activities. We can leverage the Bommasandra industrial hub and Bengaluru market ecosystem to access potential manufacturing partners, packaging suppliers, testing laboratories, healthcare networks, distributors, investors, and technology partners. Bengaluru also provides a strong market for innovative women’s wellness and sustainable consumer products, enabling us to conduct pilot testing, customer validation, and early-market adoption. IITACB can support us through technical mentorship, product validation, industry connections, intellectual property guidance, regulatory support, business mentoring, and investor networking. This ecosystem can help us transform our cabbage-based breast pad from a prototype into a scientifically validated, scalable, and commercially viable product and support our expansion into wider Indian and international markets. Yes We wish to leverage IITACB’s laboratory, product development, testing, prototyping, and incubation facilities to further develop and validate our cabbage-based herbal breast pad. We plan to use the infrastructure for formulation optimization, material testing, product prototyping, quality and safety evaluation, shelf-life studies, and process standardization. We also aim to utilize the incubator’s workspace, technical mentorship, industry network, business support, and investor connections to establish a scalable manufacturing process and accelerate commercialization. Yes Supporting feature Our product follows a multi-layer functional architecture designed for comfort, cooling, absorbency, and skin-friendly use. The outer layers provide softness, durability, and structural support, while the inner functional layer incorporates cabbage-derived bioactive extract within a suitable absorbent/skin-contact material. The design is intended to support controlled contact, moisture management, breathability, and reusable functionality. The architecture can be further optimized through material selection, formulation standardization, and prototype testing to ensure safety, comfort, and consistent performance. At the current stage, we do not have a large proprietary dataset. However, we are developing proprietary formulation and product-development knowledge through our work on cabbage bioactive extraction, ingredient incorporation, multi-layer pad design, material selection, and prototype optimization. As we conduct laboratory validation, user feedback, performance testing, and market trials, we plan to build a proprietary database that can support formulation optimization, product improvement, quality consistency, and future intellectual property protection. Our solution is defensible through a combination of proprietary formulation, cabbage bioactive extraction and incorporation methods, multi-layer product architecture, material selection, and process know-how. We aim to protect key innovations through intellectual property, trade secrets, and standardized manufacturing processes. Continuous product validation, user feedback, quality optimization, and brand trust will further strengthen our competitive advantage and create barriers for competitors to replicate the complete solution. We evaluate our cabbage-based breast pad against conventional breast pads using measurable parameters such as cooling/soothing performance, moisture absorption and retention, skin comfort, breathability, leakage resistance, durability after repeated use, dimensional stability, shelf life, and user acceptance. We also assess the stability and consistency of cabbage-derived bioactive compounds and conduct appropriate safety and quality testing. Performance will be validated through laboratory testing, prototype trials, and structured user feedback, allowing us to benchmark the product against existing alternatives and continuously improve its reliability and effectiveness. Our product is primarily a physical women’s wellness product and does not require extensive personal data collection. We follow a privacy-by-design approach, collecting only necessary customer information for sales, support, and product feedback. Any customer data collected will be handled securely with appropriate access controls, confidentiality measures, and consent-based data practices. For product compliance, we will follow applicable Indian regulatory, safety, quality, labeling, packaging, and consumer-protection requirements and conduct appropriate laboratory and safety evaluations before commercialization. If digital customer or user data is collected in the future, we will implement appropriate data protection, secure storage, restricted access, and consent mechanisms. Yes. Government initiatives supporting women’s health and wellness, sustainable product development, MSME growth, startup incubation, innovation, and entrepreneurship can support our business. Schemes and institutional support related to MSME development, startup funding, technology incubation, R&D, intellectual property, and sustainable manufacturing can help us reduce development costs, access technical facilities, validate our product, and accelerate commercialization. Such policy support can also encourage the adoption of eco-friendly and locally sourced materials in women’s wellness products. Yes. Government initiatives supporting women’s health and wellness, sustainable product development, MSME growth, startup incubation, innovation, and entrepreneurship can support our business. Schemes and institutional support related to MSME development, startup funding, technology incubation, R&D, intellectual property, and sustainable manufacturing can help us reduce development costs, access technical facilities, validate our product, and accelerate commercialization. Such policy support can also encourage the adoption of eco-friendly and locally sourced materials in women’s wellness products. At 10× scale, the major challenges would be raw material consistency, cabbage bioactive extraction capacity, quality control, standardized formulation, supply-chain reliability, and production capacity. Maintaining consistent product quality and bioactive performance across larger batches will require improved process standardization and testing. We would address these challenges by establishing qualified supplier networks, standardized extraction and manufacturing SOPs, batch-wise quality testing, scalable production equipment, inventory planning, and robust packaging and distribution systems. Yes. Our team has an interdisciplinary technical background in Food Technology, product development, food processing, extraction techniques, formulation, biomaterials, and quality evaluation. We have expertise in developing plant-based products, optimizing bioactive extraction and incorporation, designing multi-layer functional products, and conducting laboratory-based performance and stability evaluations. We are also supported by academic mentors and incubation resources for advanced testing, validation, prototyping, and technology development. Our current solution does not depend on proprietary software, AI datasets, or open-source code. The product is primarily based on cabbage-derived bioactive ingredients, skin-friendly textile materials, formulation methods, extraction processes, and multi-layer product design. The materials and components will be sourced from appropriate suppliers and evaluated for quality and suitability. Our formulation, extraction methodology, product architecture, and process know-how are being developed in-house. We currently do not rely on third-party open-source code or datasets, and no third-party IP is being directly incorporated into the product. IP protection, including potential patent filing for novel aspects of the formulation, extraction process, and product design, is being evaluated. We plan to continuously improve our technology through iterative R&D, laboratory testing, prototype optimization, and structured customer feedback. We will monitor key performance metrics such as cooling/soothing performance, moisture absorption, skin comfort, breathability, durability, bioactive stability, shelf life, and user satisfaction. Based on test results and market feedback, we will optimize the cabbage bioactive extraction, formulation, material selection, and multi-layer architecture. As we scale, we will introduce standardized SOPs, batch-wise quality testing, and continuous process improvement to ensure consistent quality, safety, reliability, and product performance. ### Are You Building for India, Global Markets, or Both? We are initially building for the **Indian market**, focusing on women seeking natural, affordable, sustainable, and reusable breast-care solutions. After establishing product-market fit, completing required validation, and meeting applicable regulatory requirements, we plan to **expand into global markets** through strategic partnerships, distributors, and e-commerce channels. Our long-term vision is to build a scalable product suitable for **both Indian and international markets**. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/5Zk4BTCB7kOx-msme-5.01.pptx, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/5Zk4BTCB7kOx-msme-5.01.pptx ### Are You Building a Mission-Driven or Impact-Focused Startup? **Yes.** Our startup is mission-driven, with a focus on improving **women’s wellness through natural, affordable, sustainable, and accessible products**. Our cabbage-based breast pad aims to provide a plant-based alternative for breast comfort while promoting the value-added utilization of **cabbage, an agricultural resource that can otherwise face post-harvest losses and market wastage**. We aim to create impact by supporting **women’s well-being, sustainable product development, agricultural value addition, and local economic opportunities** while building a commercially scalable business. No. Our team is not currently classified under a specific underrepresented group in technology/startups. However, we are a young student-led startup team working to create an affordable and sustainable women’s wellness solution. COLLAGE checked
Aug 26, 2026 @ 12:03 AM Prachitesh Wakde prachiteshwakde@gmail.com https://www.linkedin.com/in/prachiteshwakde/ https://prachiteshwakde.github.io/PPW/ +918421855227 (Lead Inventor / Technical Lead): Associated with the Yeshwantrao Chavan College of Engineering . Prachitesh led the hardware prototyping, programming, and engineering of the device developing the Arduino Nano-based code and sensor architecture that automates the cooling system i am only guy working on it 1 As a solo founder, your biggest strength lies in the powerful combination of legally granted intellectual property and complete end-to-end technical mastery over your product. SmartCool NA IIT BHU Our startup is dedicated to bringing sustainable, affordable, and intelligent climate control to the masses, solving a critical summer challenge for millions of families who cannot afford traditional air conditioning. We hold the exclusive rights to a granted Indian Patent (Patent No. 413931) for the Cooling Control Device (CCD)—a plug-and-play retrofit system that upgrades traditional, manual desert air coolers into smart, autonomous appliances. By integrating an Arduino Nano micro-controller with digital temperature sensors, the CCD automates the cooling cycle. It initiates a unique pre-wetting sequence to eliminate the initial blow of hot, dusty air and strategically cycles the water pump and fan based on real-time room temperature. This innovation achieves 30% water savings, dramatically reduces electricity consumption, and eliminates manual intervention, ensuring uninterrupted sleep. Traditional desert air coolers suffer from critical operational inefficiencies, including severe water and energy waste due to continuous water pump operation and the lack of precise temperature control . Upon initial startup, dry cooling panels blow hot, dry, and dusty air into the living space, which degrades indoor air quality and actively heats up the room before cooling can actually begin . Furthermore, because these systems lack automation, users are subjected to extreme temperature fluctuations and must constantly intervene manually to turn the unit on or off—especially at night, resulting in interrupted sleep and frequent water refills . Meanwhile, traditional chemical-based air conditioning units remain financially out of reach for many and rely on ozone-depleting chemicals that harm the environment . To solve these challenges, the patented Cooling Control Device (CCD) introduces a smart, low-cost retrofit system that can be easily installed on any existing desert cooler without requiring hardware modifications . The device uses an Arduino-based micro-controller and a digital temperature sensor to automate the cooling cycle through a unique pre-wetting process . By running the pump before the blower fan, the panels are fully soaked to maximize the latent heat of vaporization, prevent the dusty blow of hot air, and immediately circulate cool air . The system then intelligently switches the pump off once the panels are saturated and stops the fan when the target temperature is met, which drastically reduces power consumption, minimizes water waste, and ensures uninterrupted sleep comfort The patented Cooling Control Device (CCD) is an intelligent, low-cost retrofit system designed to modernize traditional desert air coolers without requiring modifications to their original design . The hardware assembly is housed in a compact enclosure and consists of an Arduino Nano microcontroller, a DS18B20 waterproof temperature sensor, a 1602 LCD display, and a relay module, costing approximately ₹1,650 to build . By integrating directly into the power path of the existing cooler, the CCD automatically coordinates the operations of both the water pump and the blower fan based on real-time room temperature and user preferences . The system operates through an innovative multi-stage cooling process . Upon startup, it executes a 45-second pre-wetting cycle that runs the water pump before activating the blower fan . This ensures the water-holding panels are fully saturated, removing heat via the latent heat of vaporization and completely eliminating the initial blast of hot, dusty air typical of conventional startups . Once active, the system's smart logic constantly monitors the room temperature . To maximize water efficiency, it automatically shuts off the pump once the temperature falls below a set threshold, relying on the water already absorbed by the panels for continued evaporative cooling . If the temperature drops below the required comfort threshold, the device stops the blower fan to prevent over-cooling and save electricity , restarting both components dynamically only as needed to maintain perfect comfort . By automating these processes, the CCD completely eliminates the need for manual human intervention or rigid timers . It dramatically reduces water and power consumption , avoids extreme cooling fluctuations , and prevents loss of sleep at night by removing the need for manual water refilling or late-night adjustments . It offers a highly accessible, eco-friendly, and CFC-free alternative to expensive traditional air conditioners The defensibility of this solution lies in its granted Indian Patent (Patent No. 413931), which secures exclusive legal rights to its automated, water-efficient control cycle for a twenty-year term [5]. Technically, it is unique as a zero-modification retrofit device that easily installs on existing desert coolers without hardware alterations, built using an economical bill of materials costing 1,650 units [7, 8]. Its core innovation is a proprietary pre-wetting cycle that runs the pump before the blower fan to eliminate the initial blast of hot, dusty air and maximize cooling via the latent heat of vaporization [7, 8]. By intelligently cycling the pump and fan based on real-time temperature thresholds, the system prevents over-cooling and significantly reduces water and power consumption—providing a legally protected, eco-friendly alternative to traditional air conditioning [3, 7] Users Users, Pilots Our target customer base is highly diverse, spanning both B2C (direct-to-consumer) and B2B (business-to-business) channels: 1. B2C: Middle-Income & Budget-Conscious Households Families in Dry & Hot Climates: Traditional desert coolers are highly effective in low-humidity regions . This segment consists of millions of families who rely on evaporative cooling but are frustrated by issues like the initial blast of hot, dusty air or having to wake up in the middle of the night to adjust the settings or refill a dry water tank . Cost-Conscious Comfort Seekers: These are households that want the comfort of automated, precise temperature regulation but cannot afford the high purchase price and expensive electricity bills associated with running a traditional air conditioning unit . Eco-Conscious Consumers: Environmentally conscious buyers looking for a green, sustainable cooling option that drastically reduces power and water consumption while operating with zero ozone-depleting CFCs or hazardous refrigerants . 2. B2B: Original Equipment Manufacturers (OEMs) Desert Cooler Manufacturers: Major brands and local manufacturers of cooling appliances represent a massive licensing opportunity. Because our system is designed to be easily retrofitted without modifying any original components of the cooler , manufacturers can easily integrate this low-cost, patented technology directly into their production lines . This allows them to market and sell factory-fitted "Smart Coolers" to their existing retail networks without specialized worker training . 3. B2B2C: Retailers, Distributors & Electrical Technicians Appliance Retrofitters & Local Retailers: Since the device is a highly economical and simple plug-and-play solution , local electrical shops, technicians, and distributors can stock and sell it as an aftermarket accessory to upgrade the massive pre-existing market of manual coolers already installed in homes Your Total Addressable Market (TAM) comprises the entire global base of existing and newly manufactured desert air coolers, as well as the broader market of consumers seeking affordable, eco-friendly climate control alternatives. Because the Cooling Control Device is engineered as a highly economical, plug-and-play solution that retrofits onto any pre-existing desert cooler in the marketplace without requiring any component modifications , your immediate market includes every household currently using manual evaporative coolers. Since evaporative cooling is highly effective and primarily recommended for dry, hot, and low-humidity climates , this market is geographically concentrated in arid and semi-arid regions. Furthermore, because your patented technology serves as a low-power, CFC-free alternative to traditional air conditioning , your TAM expands to include budget-conscious and eco-conscious consumers who want automated temperature regulation but are deterred by the high energy costs and environmental impacts of conventional cooling systems Geographically, your SAM is highly concentrated in the arid, semi-arid, and dry sub-tropical regions of Northern, Western, and Central India—such as Maharashtra, Madhya Pradesh, Rajasthan, and Gujarat—where hot and dry summer climates make evaporative cooling exceptionally effective. Economically, this market consists of middle-income and budget-conscious households that rely on desert coolers as their primary climate control because they are priced out of the high purchasing and operational costs of traditional chemical-based air conditioning. By focusing on this specific Indian market, you are targeting a consumer base that is highly vulnerable to seasonal water scarcity and rising electricity rates, making your system’s automatic pump-cycling, 30% water savings, and overall power conservation an incredibly high-value proposition. Because the uploaded sources do not contain quantitative unit sales, household penetration rates, or market valuation figures for India's consumer appliance industry, your SAM cannot be calculated as an exact monetary figure without external data. This serviceable market represents the logical limit of your domestic expansion through direct-to-consumer retrofit sales and local distributor partnerships before you scale into global arid markets or licensing models. If you would like to establish an exact financial valuation for this market segment to include in your investor business plan, I can conduct web research to gather the latest industrial reports on the volume and growth of the Indian air cooler market. Our Serviceable Obtainable Market (SOM) represents the specific, highly realistic portion of the Indian desert cooler market that we can capture within the first one to three years of commercial launch. Given our academic roots at the Yeshwantrao Chavan College of Engineering and the natural geographic constraints of evaporative cooling, our immediate SOM focuses on middle-income households, local businesses, and regional appliance repair networks in Central India—specifically the high-temperature, water-scarce corridors of Vidarbha and Marathwada in Maharashtra. This initial target segment is highly motivated to adopt our solution, as they face severe summer water shortages and rising electricity tariffs, making our patented, ₹1,650 low-cost retrofit system an exceptionally high-urgency purchase to secure comfortable sleep while reducing resource bills. To capture this initial market share, our distribution strategy is twofold: we will sell the plug-and-play device as an aftermarket upgrade directly through regional electrical retailers and independent HVAC technicians who service existing coolers, while simultaneously targeting regional, unorganized desert cooler manufacturers to pre-install our automated controllers in new units. By focusing on this localized, high-impact region first, we can run an extremely lean, capital-efficient operation to establish immediate cash flow, validate our supply chain, and build local brand trust. This regional footprint serves as a vital proof-of-concept, providing the exact commercial validation and leverage needed to license our patented pre-wetting and pump-cycling technology to major national brands and expand our reach across the broader Indian market. Our business operates on a dual-revenue strategy designed to maximize immediate cash flow through direct sales while securing long-term, high-margin scalability through licensing. Although our technical documentation does not outline a finalized corporate financial sheet, it establishes a solid commercial foundation with an optimized prototype manufacturing cost of just ₹1,650 and a legally secured Indian Patent (Patent No. 413931) . By utilizing these two core assets, we can capture value from both the consumer aftermarket and the industrial manufacturing sectors. The first revenue stream is the direct hardware sales model, targeting the massive pre-existing market of manual desert air coolers. Because our Cooling Control Device is engineered as a plug-and-play, zero-modification retrofit system, it can be easily installed on any traditional cooler already operating in consumer homes without requiring any hardware changes or specialized tools . This wide compatibility allows us to package and sell the device as an affordable aftermarket upgrade kit directly to budget-conscious households and local appliance repair workshops. With our remarkably low bill of materials of ₹1,650 , we can set a retail price that remains highly attractive to middle-income families looking to save on water and electricity, while still retaining healthy gross margins to sustain our operations. The second, highly scalable revenue stream is a business-to-business (B2B) intellectual property licensing model. Our technology is backed by a fully granted Indian Patent valid for a twenty-year term starting from December 2021, giving us the exclusive right to prevent others from making or selling our automated, water-efficient cooling cycle . This legal exclusivity allows us to partner with major, established commercial cooler brands and license our proprietary pre-wetting and temperature-driven pump-cycling algorithms . Under this licensing arrangement, manufacturers can integrate our smart controller directly into their factory assembly lines to offer premium "smart" models, paying us a recurring royalty fee for every unit they manufacture and sell. This asset-light model enables us to scale rapidly across the entire national market by leveraging the existing distribution networks and production capabilities of established brands. Traditional, manually operated desert air coolers represent the most common and direct competitors in the mass market . While these units are cheap, highly accessible, and widely used, they lack any smart automation or precise thermal control, which results in continuous water and power waste . Standard coolers also force users to manually toggle switches or struggle with rigid timers, leading to extreme temperature fluctuations and late-night sleep disruptions when water tanks run dry or the room becomes uncomfortably cold . Additionally, on initial startup, these conventional coolers blow hot, dry, and dusty air into the living space because the cooling pads are completely dry, actively heating up the room and degrading indoor air quality before any cooling begins . Standard chemical-based air conditioning units serve as the high-end, modern climate control competitors, but they carry heavy financial and environmental drawbacks . Air conditioners consume exceptionally high amounts of electrical power, resulting in expensive monthly energy bills that place them completely out of reach for a massive portion of the middle-income and budget-conscious population . Furthermore, these cooling systems rely on ozone-depleting chlorofluorocarbons (CFCs) and hazardous refrigerants that actively harm the environment . Our Cooling Control Device directly challenges this competitor by offering an incredibly affordable, low-power, and eco-friendly alternative that utilizes the natural physics of the latent heat of vaporization to cool spaces safely with zero harmful refrigerants . On a highly technical level, our main competitors are defined by the specific patent prior art cited during our official Indian patent examination, notably patents CN108279719B (Temperature control method and device) and CN104153921B (Air-conducting component with charge air cooler) . These existing systems attempted to regulate cooling parameters through highly complex and expensive mechanical structures such as specialized control valves, stoppers, and intricate plumbing, making them difficult and costly to reproduce . More importantly, when these prior art devices adjusted their cooling parameters, they failed to successfully conserve either the coolant (water) or energy . In contrast, our patented Cooling Control Device (Patent No. 413931) overcomes these limitations by utilizing a remarkably simple, ₹1,650 micro-controller design that automatically stops the water pump to save water and power while keeping the airflow active, delivering far superior resource efficiency . Finally, typical automated or timer-based control systems frequently switch the heavy air blower fan motor on and off to maintain room temperature, which causes severe physical jerking and rapid mechanical wear on the motor's internal parts . Our system solves this engineering challenge by maintaining continuous airflow while dynamically cycling only the low-power water circulating pump . This smooth operational logic ensures excellent thermal stability and significantly extends the operational lifespan of the cooler's mechanical components . By offering a legally protected, zero-modification retrofit solution that is vastly more efficient than conventional coolers, far cheaper and greener than air conditioners, and technically superior to complex patented prior art, we hold an incredibly strong, defensible position in the climate control market We acquire customers through a dual-channel strategy that leverages both direct-to-consumer (B2C) aftermarket sales and business-to-business (B2B) original equipment manufacturer (OEM) licensing agreements. For the B2C aftermarket channel, we focus on regional distribution partnerships in hot, low-humidity, and water-scarce areas where families heavily rely on traditional desert air coolers . Since our patented Cooling Control Device is a zero-modification, plug-and-play retrofit system that easily installs on any existing desert cooler without altering its pre-existing design , we can acquire customers by placing our product in regional home appliance stores, local hardware shops, and independent HVAC repair networks. By training local technicians to recommend the device during standard summer service visits, we directly reach budget-conscious homeowners who want to upgrade their cooling comfort. This grassroots approach relies on demonstrating the immediate, tangible benefits of the system—such as preventing nighttime sleep disruption, eliminating the dusty startup blow, and drastically reducing electricity and water bills . These features are all made possible by our remarkably low hardware bill of materials totaling ₹1,650 . Simultaneously, we pursue a highly scalable, asset-light B2B customer acquisition model by licensing our proprietary technology directly to established national and regional desert cooler manufacturers. Because our unique automated cooling control cycles and pre-wetting algorithms are protected by a fully granted Indian Patent (Patent No. 413931) for a term of twenty years , we hold exclusive legal rights that prevent competitors from replicating this resource-efficient technology. We leverage this legal moat to pitch major cooling brands, showing them how they can instantly upgrade their product lines to offer "Smart Eco-Coolers" without investing in complex and expensive engineering redesigns . By licensing our microcontroller code, sensor architecture, and processing logic to be pre-installed on their production lines , we can rapidly scale our market penetration across the country, generating recurring royalty revenues while letting established manufacturers handle the high costs of mass production, marketing, and retail logistics. Our go-to-market (GTM) strategy for the patented climate control technology is built on a highly scalable, dual-channel commercialisation model that targets both the direct-to-consumer (B2C) aftermarket and original equipment manufacturer (B2B) licensing channels . The foundation of this strategy rests on the absolute versatility and cost-efficiency of our core innovation: a compact, intelligent control box that can be effortlessly retrofitted onto any existing desert air cooler already in use . Because the system integrates directly into the existing cooler's power lines without requiring any structural modifications, component additions, or technical changes, we can bypass the high barriers to entry usually associated with introducing new hardware solutions . By utilizing this frictionless design, we can rapidly capture a massive pre-existing market of budget-conscious households that already own evaporative coolers but suffer from severe inefficiencies and a lack of comfort . For our direct hardware sales (B2C) channel, we will manufacture and distribute the Cooling Control Device as an easy-to-install aftermarket upgrade kit . The complete assembly is housed in a rugged enclosure box and consists of highly accessible, robust parts—including an Arduino Nano microcontroller, a digital waterproof temperature sensor, a backlit LCD display, and a dual-channel relay module—yielding an exceptionally low production bill of materials of just ₹1,650 . We will distribute these physical kits through regional appliance repair networks, local hardware stores, and independent electrical technicians, focusing on low-humidity and water-scarce regions where evaporative cooling is most effective . By providing local repair technicians with simple installation guidelines, we turn them into active brand advocates who can directly recommend and install the ₹1,650 smart upgrade during routine pre-summer cooler maintenance visits . To achieve rapid, nationwide scale with minimal capital expenditure, we will simultaneously execute a B2B technology licensing model . This highly defensible, high-margin channel is fully protected by a granted Indian Patent (Patent No. 413931), which secures the exclusive legal rights to our automated pre-wetting and resource-efficient cooling cycle for a twenty-year term starting from December 2021 . We will leverage this legal moat to pitch established national and regional desert cooler brands, offering them a ready-to-adopt smart climate solution . Rather than managing the massive operational overhead of assembly lines and retail logistics ourselves, we will license our proprietary microcontroller code and sensor design to be pre-installed directly inside newly manufactured coolers, securing a recurring royalty fee on every "Smart Eco-Cooler" sold . Our marketing and customer acquisition messaging will focus heavily on quantifiable comfort and resource savings . We will actively market the device's ability to achieve a 30% reduction in water consumption and major electricity savings by stopping the water pump once the cooling panels are fully saturated and turning off the blower fan when the room cools below the user's target threshold . We will also emphasize the core lifestyle benefits of our proprietary pre-wetting cycle, which runs the pump for 45 seconds before the fan starts to eliminate the dusty, hot initial air blow and guarantees an uninterrupted night of sleep without the need to wake up for late-night manual adjustments or water refilling . By positioning our system as a highly affordable, ₹1,650 alternative that delivers the temperature-controlled comfort of an air conditioner with zero harmful chemical refrigerants or ozone-depleting substances, we can capture the trust of both economically driven and environmentally conscious consumer segments Our long-term vision is to democratise sustainable, intelligent climate control by completely transforming how evaporative cooling is utilised on a global scale. We aim to establish our patented Cooling Control Device as the universal standard for smart cooling automation, enabling millions of households in arid regions to access precise temperature regulation without the environmental or financial burden of traditional air conditioning . By systematically reducing dependency on energy-guzzling, chemical-based air conditioners that rely on ozone-depleting substances, we envision a future where high-quality, eco-friendly cooling is both affordable and accessible to all socio-economic segments . Ultimately, we strive to lead the transition toward green cooling technologies that actively preserve our planet’s precious water and power resources while elevating domestic comfort and indoor air quality . Over the course of our twenty-year patent term, we plan to scale our impact by forging strategic partnerships with major national and international appliance manufacturers, integrating our water-efficient algorithms directly into the factory lines of newly produced cooling units . This strategy will allow us to move beyond an aftermarket retrofit solution and directly shape the next generation of climate-smart household appliances . Furthermore, as water scarcity becomes an increasingly critical global challenge, we intend to expand our technology’s reach to other dry and hot countries, proving that smart, low-cost engineering can solve large-scale resource issues. By maximizing the natural physics of the latent heat of vaporization and eliminating manual human intervention, we aim to ensure that water savings, energy efficiency, and uninterrupted sleep comfort become standard household realities rather than premium luxuries NA NA Yes We are applying to the IITACB Incubator to bridge the critical gap between our successful academic prototype and mass-market commercialisation. Developed from our research foundations, our Cooling Control Device (CCD) is currently a proven, functional physical prototype utilizing an Arduino Nano microcontroller and a waterproof temperature probe, built on an incredibly lean bill of materials of just ₹1,650 [8]. While we have successfully validated the core hardware assembly and programmed the automated, temperature-triggered cooling cycle, we require the incubator's world-class IoT and hardware testing facilities to refine our system for high-volume manufacturing [1, 8]. Access to advanced labs will allow us to optimize our circuit design, conduct rigorous durability testing under extreme thermal conditions, and transition our current prototype into a ruggedised, market-ready consumer product. Securing a spot in the IITACB Incubator is also vital for navigating the complex landscape of intellectual property commercialisation and business development. We hold a fully granted Indian Patent (Patent No. 413931) protecting our unique water-efficient cooling cycle and pre-wetting process for a twenty-year term, establishing a powerful legal moat [3, 5]. However, translating this IP asset into a scalable business requires expert guidance. We want to leverage the incubator's mentorship network to refine our dual-revenue model—specifically in structuring robust technology licensing agreements with major national consumer appliance brands and setting up local distribution channels for our aftermarket retrofit kit [3, 7]. The strategic guidance from seasoned hardware entrepreneurs at the incubator will help us optimize our supply chain and establish commercial manufacture. Finally, the prestigious association with the IITACB Incubator provides our startup with the institutional credibility needed to engage in high-level B2B negotiations with major original equipment manufacturers (OEMs). Presenting a patented, resource-saving technology as an incubated startup instantly validates our scientific rigor and commercial viability when pitching to major desert cooler brands. Furthermore, the incubator’s extensive network offers direct access to venture capital, government grants, and industry partners who are actively seeking sustainable, CFC-free cooling solutions to combat rising energy costs and severe water scarcity [3, 7]. This incubation will give us the launchpad, resources, and strategic ecosystem required to scale our patented technology from a regional innovation into a national benchmark for eco-friendly climate control. During the incubator programme, our primary objective is to transition our functional, low-cost prototype into a fully optimized, market-ready commercial product. While we have successfully proven the technology using an Arduino Nano, a DS18B20 temperature probe, and a basic relay assembly within a ₹1,650 bill of materials, we want to leverage IITACB's state-of-the-art IoT labs and hardware testing facilities to design a custom, compact printed circuit board (PCB) and a ruggedised, weatherproof enclosure. We will conduct rigorous durability and thermal stress testing under simulated harsh summer environments to ensure the electronics can withstand the high humidity and ambient temperatures typical of desert coolers, transforming our academic prototype into a highly reliable, mass-manufacturable consumer accessory. Secondly, we aim to execute a comprehensive, scientifically rigorous comparative study to fully quantify our resource-saving algorithms and build an indisputable, data-driven business case for investors and manufacturers. By setting up two identical desert air coolers under the same environmental conditions—one operating conventionally and the other integrated with our patented Cooling Control Device—and equipping them with precise water flow sensors, power meters, and temperature probes, we will gather high-fidelity data on our system’s performance. This empirical testing will allow us to mathematically validate the projected 30% reduction in water consumption and significant energy savings achieved by our pre-wetting and automated pump-cycling cycles. Having these certified, publication-quality metrics will give us immense leverage when demonstrating our technology's efficiency to regulatory bodies and eco-conscious funding agencies. Our third major milestone during the programme is to translate our intellectual property into a scalable business through a structured business-to-business (B2B) licensing framework. Backed by our fully granted Indian Patent (Patent No. 413931), we possess a strong twenty-year legal monopoly over this water-efficient control cycle in India. With the strategic guidance of IITACB’s legal and business mentors, we intend to draft robust licensing templates and pitch presentations specifically tailored for major national and regional desert cooler brands. Our goal is to secure at least two pilot integration agreements with commercial cooler manufacturers during the incubation period, proving the commercial viability of pre-installing our smart controllers directly onto their factory assembly lines. Finally, we will use the programme to launch a regional pilot of our plug-and-play aftermarket retrofit kits in the high-temperature, water-scarce corridors of Maharashtra, establishing our first direct-to-consumer sales traction. By partnering with local electrical retail networks and independent appliance technicians, we aim to deploy our first thousand units, validating our supply chain, installation guidelines, and customer service models in real-world settings. Ultimately, we will leverage this combined technical validation, OEM pilot interest, and early retail traction to present a highly compelling, risk-mitigated business to venture capitalists and green technology investors at the IITACB Demo Day, securing the seed funding necessary to scale our eco-friendly climate control solution nationwide. Yes, we are fully open to virtual participation and are highly equipped to engage seamlessly with the incubator’s online mentoring, strategic workshops, and business development sessions. Since our core technology is backed by a fully granted Indian Patent (Patent No. 413931) and our Arduino-based control logic is already fully programmed, we can easily collaborate with advisors, refine our business and licensing strategies, and participate in marketing or financial planning modules remotely. This virtual flexibility ensures that we can maintain absolute operational momentum and actively participate in the cohort's educational and networking events without any geographical constraints. However, given the deeply hardware-centric nature of our Cooling Control Device (CCD), we strongly prefer a hybrid or physical participation model whenever hands-on development is required. Accessing the specialized IoT laboratories, PCB prototyping setups, and advanced testing facilities at the incubator is essential for us to optimize our current ₹1,650 prototype into a ruggedised, mass-manufacturable consumer accessory. Conducting environmental durability tests to ensure our electronics can reliably withstand the extreme heat and humidity inside a desert cooler is a task that heavily relies on physical infrastructure, making in-person access to your technical facilities the ideal pathway to achieving our product development milestones. The multi-billion dollar Bommasandra industrial hub in Bangalore offers an unparalleled ecosystem of electronic manufacturing services, precision mold-makers, and high-volume printed circuit board assembly plants that we can directly leverage to transition our Cooling Control Device from an academic prototype into a mass-produced commercial product. By tapping into Bommasandra's localized hardware supply chain, we can establish highly efficient contract manufacturing partnerships to mass-produce our control boards, securing reliable sourcing for the Arduino Nano, digital temperature sensors, displays, and relay modules to further drive down our already lean ₹1,650 bill of materials. Simultaneously, the broader Bangalore and Karnataka markets present a massive commercial opportunity; while Bangalore is known for its temperate climate, its rapidly expanding industrial corridors, construction colonies, student housing complexes, and PG accommodations rely heavily on cost-effective evaporative desert coolers, making them high-urgency markets for our zero-modification retrofit kit that dramatically slashes water and power consumption. The IITACB Incubator serves as the ultimate strategic catalyst to unlock these high-value industrial and commercial networks. Through the incubator’s prestigious network of IIT alumni, we can secure warm introductions to leading electronic manufacturing services founders in Bommasandra, enabling us to negotiate favorable high-volume production pricing and design a highly reliable, commercial-grade PCB. Furthermore, the business mentorship at IITACB is vital for helping us structure legally robust licensing frameworks for our fully granted Indian Patent (Patent No. 413931), giving us the credibility and legal guidance needed to pitch our patented pre-wetting and automated pump-cycling algorithms directly to national home appliance brands that have corporate offices in Bangalore. By combining Bommasandra's physical manufacturing capabilities with IITACB's elite mentoring and venture network, we can rapidly scale our green, CFC-free climate solution from a proven local prototype into a nationwide market leader. Yes Renting seats at the IITACB Incubator will provide our engineering team with a dedicated, high-energy workspace positioned directly within Bangalore's premier technology ecosystem. This physical presence is crucial for establishing our daily operations, managing local supply chains, and facilitating real-time collaboration with fellow hardware innovators and resident advisors. By working directly on-site, we can seamlessly integrate into the incubator's mentor network, allowing us to receive hands-on guidance on structuring robust commercial licensing agreements for our granted Indian Patent (Patent No. 413931) and refining our dual-revenue business model. This collaborative environment will help us transition from an academic research mindset into a fast-scaling commercial enterprise. We plan to heavily leverage the incubator's advanced electronics prototyping and IoT laboratories to upgrade our current hardware architecture. Our current functional prototype relies on an Arduino Nano microcontroller, a DS18B20 waterproof temperature probe, a 1602 LCD display, and a dual-relay module, all packaged within a basic enclosure for an exceptionally lean bill of materials of ₹1,650. At IITACB, we will use advanced PCB design software, high-precision soldering stations, and diagnostic oscilloscopes to consolidate these discrete components onto a single, custom-engineered, multi-layer printed circuit board (PCB). This redesign will significantly reduce the physical footprint of the controller, eliminate potential manual wiring failure points, and further drive down manufacturing costs, making the device highly reliable and ready for high-volume commercial production. Additionally, we wish to utilize the incubator’s environmental and thermal testing chambers to conduct rigorous durability testing under simulated extreme summer conditions. Because our device is retrofitted directly onto desert air coolers where moisture levels are high and ambient temperatures can exceed 45 degrees Celsius, our electronics must be completely resilient against moisture ingress, thermal stress, and corrosion. Testing our custom-built enclosure and sensor assemblies within IITACB's specialized environmental chambers will allow us to certify the device's electrical safety and long-term reliability. This rigorous validation is essential to secure the necessary consumer safety certifications and to build confidence when pitching our product to major retail distributors. Finally, we intend to use the incubator’s facility space to set up a controlled, instrumented experimental testing rig to formally document our system's resource-saving capabilities. By running a side-by-side comparative study of two mechanically identical desert air coolers—one controlled by our patented automation system and the other operating conventionally—we will gather high-fidelity data using calibrated water flow sensors and power meters. This testing will allow us to empirically validate the system's ability to achieve a 30% reduction in water consumption and major electricity savings through our dynamic pump-cycling and pre-wetting algorithms. Having these certified, publication-quality performance metrics will provide our startup with incredible leverage when pitching to green-technology venture funds, government sustainability agencies, and major national home appliance manufacturers. Yes Not applicable 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/yopTFJ9NdeHl-Smart_Cooling_Resource_Validation-1_compressed-1.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/yopTFJ9NdeHl-Smart_Cooling_Resource_Validation-1_compressed-1.pdf https://drive.google.com/drive/folders/1Wm7dCL3Sd_1GsdciGqJuA8mHMwKQtjOB?usp=drive_link IIT BHU checked
Aug 25, 2026 @ 11:57 PM Aryan Singh hello@pitchtoship.com https://www.linkedin.com/in/aryansingh https://pitchtoship.com +919601978892 Founder & Lead Architect — Full-Stack Systems, Distributed AI Orchestration, and Automation Tools Architecture. Solo founder (OPC structure) with 3+ years of deep R&D across developer productivity tooling, local-first architectures, and autonomous agent systems. 1 Full-cycle deep-tech execution: ability to independently architect, build, benchmark, and deploy production-grade software spanning local-first AI compression, API automation, cryptographic verification, and scalable web interfaces. PITCHTOSHIP (OPC) PRIVATE LIMITED https://pitchtoship.com Bangalore PitchToShip is an automation and developer productivity startup building AI context compression (CutCtx), Git-native API workspaces (Cortex), and automated multi-carrier shipping logistics. 1. AI Context Degradation & Token Costs: Developers and agents lose context and waste excessive API spend on bloated prompts. 2. Fragmented Developer Workflows: API testing, agent memory, and logistics shipping operations require clunky, disconnected legacy tools. A unified suite of high-productivity automation tools: (1) CutCtx — local-first reversible context compression & persistent memory for AI agents (MCP server + proxy). (2) Cortex — Git-native API testing workspace. (3) PitchToShip — automated multi-carrier shipping command center. Local-first zero-telemetry architecture, sub-millisecond offline cryptographic licensing (ECDSA tokens), and lossless context compression algorithms that retain reasoning fidelity without token bloat. MVP Pilots, Signups, Testimonials AI engineering teams, autonomous agent developers, enterprise platform engineers, and high-growth e-commerce/D2C automation teams. $45 Billion (Global AI Developer Tooling, Workflow Automation & Logistics SaaS) $6.5 Billion (API-first productivity infrastructure & agent optimization tools) $85 Million (High-growth AI engineering teams & mid-market cross-border automation) Tiered B2B SaaS subscriptions (Starter/Pro/Enterprise) + usage-based developer licensing and self-serve Razorpay/Stripe checkout. For AI Context/Memory: LangSmith, MemGPT/Letta. For API Tooling: Postman, Insomnia. For Logistics: ShipStation, Shippo. Developer-led growth (PLG), open-source MCP ecosystem distribution, technical benchmarks, developer community advocacy, and direct B2B pilot outreach. MCP-first distribution for AI engineers, followed by self-serve website onboarding, bottom-up developer adoption, and enterprise seat expansion. To establish the foundational local-first automation and context optimization infrastructure layer for the next generation of AI agents and developer workflows worldwide. Incorporated — PITCHTOSHIP (OPC) PRIVATE LIMITED (CIN: U62011BR2026OPC085421; PAN: AARCP1354J; TAN: MRTP15957E; GSTIN: 10AARCP1354J1ZF) Bootstrapped / Self-funded Yes To leverage IITACB’s prestigious alumni network of deep-tech mentors, scale enterprise B2B customer traction, and access premier institutional seed capital. Deploy enterprise pilots for CutCtx & Cortex, scale recurring revenue, expand international developer platform partnerships, and close an institutional seed round. Yes Bangalore is the epicenter of deep-tech AI and enterprise SaaS. We plan to pilot productivity and logistics automation directly with regional tech startups and manufacturing hubs, accelerated by IITACB mentor connections. Yes Utilize high-productivity co-working spaces to collaborate closely with mentors, host prospective enterprise clients, and network with fellow deep-tech founders. Yes Core engine Frontend: React 18 + Vite SPA on Cloudflare Pages. API & Edge: Express 4 + Node 22 on Render with Cloudflare Pages Functions (V8 Isolates). DB & Cache: PostgreSQL 17 + Redis distributed rate-limiting. Licensing & Security: ECDSA P-256 signed entitlement tokens with offline HWID verification. AI Context: Local MCP server with vector & structural pruning heuristics. Proprietary multi-agent prompt compression datasets, token reduction heuristics, and empirical benchmark traces across tool-calling workflows. Strict local-first privacy (code/prompts never leave user machine), sub-millisecond offline cryptographic licensing, and native integration into modern AI ecosystems (MCP protocol, V8 edge isolates). Compression ratio (% token savings), execution latency overhead (99.9%). Zero data retention policy: all context compression runs locally or via zero-knowledge proxies. Authenticated using tamper-proof ECDSA token signatures; compliant with DPDP and GDPR standards. IndiaAI Mission compute/infrastructure grants, DPIIT startup recognitions, and patent fast-tracking incentives. Rapidly evolving AI data sovereignty regulations and cross-border SaaS tax compliance (mitigated by certified payment gateways Razorpay & Stripe). PostgreSQL connection pooling under high concurrency (addressed with Redis caching and moving stateless licensing to Cloudflare V8 Edge isolates) and upstream carrier API rate limits. Yes. In-house deep-tech expertise spanning systems architecture, cryptographic verification (ECDSA), TypeScript/Node.js internals, V8 edge runtimes, and LLM context optimization. Using MIT/Apache 2.0 open-source dependencies (React, Vite, Express, Zod, pg, Sentry). All proprietary licensing logic, compression algorithms, and server implementations are 100% owned by PitchToShip (OPC) Private Limited. Continuous benchmarking against new frontier LLM releases, automated Playwright/Vitest regression suites, and refining edge compute performance. Both (Global market for developer productivity & AI context tools; Indian & international markets for shipping automation). 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/XLNw2NtcCk27-PitchToShip_Pitch_Deck.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/XLNw2NtcCk27-PitchToShip_Pitch_Deck.pdf https://pitchtoship.com Yes. We are dedicated to eliminating computational waste and energy consumption from redundant LLM token processing, while democratizing access to high-performance automation tools. NA IITACB Website / Self / Open Application Registered under MCA as PITCHTOSHIP (OPC) PRIVATE LIMITED. Fully compliant with active GST and PAN registration. Ready for in-depth technical review. checked
Aug 25, 2026 @ 11:42 PM Shri Prakash Gupta shriprakash2802@gmail.com https://in.linkedin.com/in/shri2802 http://NA +919648923480 Shri Prakash Gupta (Co-Founder)B.Tech ( Chemical ) , IIT Gandhinagar (2013). M.Tech ( Chemical ), IIT Kanpur ( 2015) 11 years Experience as Scientist with Bhabha Atomic research Center, Mumbai. Dr. Raj Kumar Singh, B.Tech ( Mechanical) , IIT Kanpur (2004), PhD, HBNI, 21 years Experience as Scientist up to Scientific Officer H, with Bhabha Atomic research Center, Mumbai, We met as colleagues in the Reactor Engineering Division at the Bhabha Atomic Research Centre (BARC) several years ago and worked on several problems. R.K. began developing this project, and we have been actively collaborating on its development for the past four years. 2 Our greatest strength lies in exhaustive engineering experience (11 and 21 years, respectively). We possess the end-to-end technical capabilities required to design, analyze, and build complex systems in-house. My expertise focuses on thermal-hydraulics, multiphase flow, corrosion, and the physical fabrication of high-temperature pressure vessels. This pairs seamlessly with R.K.’s extensive background in fluid mechanics, applied mathematics, thermodynamics, vibration analysis, and comprehensive mechanical design, integration of multidisciplinary subsystems, execution and commissioning of power plant projects . Navier Corp NA Mumbai We are a deep-tech energy startup introducing G.E.O (Green Energy from Ocean). We provide a revolutionary, economical renewable energy technology that operates 24/7, offering true, year-round baseload electricity generation. The global energy transition is bottlenecked by the inability of traditional renewables to provide continuous, stable baseload power. We solve this by harnessing ocean energy to deliver economically viable, round-the-clock clean electricity. GEO is an innovative, modular heat engine that generates continuous, carbon-free baseload electricity by harnessing the constant temperature difference between warm ocean surface water and cold deep water. By operating round-the-clock without the need for fuel, this quickly deployable technology offers highly economical power that solves the intermittency challenges of traditional renewables. Our uniqueness lies in delivering continuous, 24/7 renewable baseload power at a highly disruptive LCOE of 1.35 cents per unit. Solution is quite unique as the system adapts to the sea conditions, and remains safe from the rough condition. It requires various different working of components which are based on fundamentals but not common in routine energy engineering. This is highly defensible due to a deep-tech moat, nature of the energy sector, highly innovative design at various levels and the immense technical barrier to entry secured by our team's combined 28 years of specialized engineering expertise. MVP Pilots Island Nations & SIDS, State Utilities and Grid Operators, Energy-Intensive Heavy Industry 88,000 Terawatt-hours per year globally, which represents the total worldwide capacity for this technology. 3.5 trillion $. Over 1,140 Gigawatts NA We generate revenue primarily through the sale of electricity to state grids and heavy industries. In growing phase we form SPV for each plant enabling project finance, collaboration with local partner, The SPV signs the PPA, sells the electricity. Original company has a share in each SPV. Coal, Nuclear, BESS We will acquire our initial customers through a physical technology showcase by deploying a 1 MWe pilot unit in the ocean. Now most of the Islands depend on diesel,Fuel cost, logistics and supply security makes reliable power extremely expensive there. Some Places even Rs. 40-90 per unit. This successful demonstration will act as our primary sales catalyst to secure medium-scale, 10-50 MWe commercial orders directly from there and then big plants on continents also for industrial and utility off-takers. We will first demonstrate a 1 MWe pilot in the ocean to secure an initial 50 MWe commercial order from industry. To scale, we will establish a coastal assembly line near Visakhapatnam to mass-produce our modular units. For global distribution, we will segment the market into four ocean regions, shipping units directly via sea and leveraging local country partners for shore connectivity and regulatory compliance. Our long-term vision is to defeat global warming by replacing the world's baseload fossil fuel plants with continuous, economic renewable energy at a massive scale. We aim for the worldwide implementation of GEO to permanently change the global energy landscape. In Process (Private Limited) NA Yes We are an IIT alumni-led deep-tech startup transitioning from years of R&D to physical commercialization. We are applying to IITACB to access the strategic mentorship, industry connections, and investor networks needed to build and deploy our 1 MWe pilot unit. The collective strength of the IIT alumni network is the ideal catalyst to help us scale this complex, hardware-heavy green energy solution Secure the ₹14 crore funding required to build our 1 MWe pilot unit, and establish heavy-engineering manufacturing partnerships to successfully transition from R&D to physical commercialization. Yes We plan to utilize Bommasandra’s engineering and fabrication ecosystem to manufacture our critical components, while tapping into Bangalore for deep tech capital. We are looking to IITACB for industry introductions for access to its investor network to fund our physical pilot demonstration. Yes We will leverage the IITACB workspace as our design headquarters in Bengaluru to closely manage our fabrication partners in Bommasandra. Yes Core engine GEO is a modular offshore heat engine that operates in the ocean. The temperature difference between different layers of ocean is converted into mechanical and finally electrical power. NA Our competitive edge is unmatched unit economics for continuous green power. GEO delivers baseload energy at just $13/MWh. This is four times cheaper than coal ($80/MWh) and less than half the cost of nuclear ($45/MWh). Crucially, unlike solar and wind, GEO operates 24/7 naturally, completely eliminating the need to attach economically prohibitive Battery Energy Storage Systems (BESS) to achieve baseload capacity. We evaluate performance primarily using the Levelized Cost of Electricity (LCOE) and Capacity Factor. GEO offers a highly disruptive LCOE of 13 $/MWh (compared to coal at $80 or solar PV at $40) and achieves a baseload capacity factor, providing continuous power unlike intermittent renewables. Because our product is a physical offshore energy infrastructure asset, traditional consumer data privacy is not applicable. Security concerns are handled by ensuring our marine assets and grid connections adhere strictly to national grid cybersecurity standards and maritime safety protocols. Government mandates for renewable energy transitions, carbon reduction goals, and financial incentives like Renewable Energy Credits (RECs) directly support and accelerate the adoption of our green baseload technology. Key regulatory risks involve navigating maritime operational clearances, securing offshore environmental approvals, and meeting the grid integration compliances required by local state electricity boards. Because GEO utilizes identical, modular 5 MWe units, the core technology itself scales seamlessly without breaking. Yes. Our in-house founding team possesses decades of specialized engineering experience in nuclear reactor components, thermal multiphase flow, fluid mechanics, structural design, integration and power plant design. For our offshore deployment, our Marine lead, Shesh Nath Gaur, brings 20 years of dedicated marine operational experience. Crucially, our deep-tech R&D and marine scaling are guided by two highly distinguished mentors: Dr. A. E. Muthunayagam ( Former Secretary of the Department of Ocean Development, Founding Pioneer of NIOT which is ocean technology arm of Govt. Of India, Padma Shri ), and Prof. J.B. Joshi (Padma Bhushan awardee in Engineering Sciences) We utilize standard commercial engineering and CFD software for modeling. Our core thermodynamic designs and marine integration systems are entirely owned and proprietary, representing 7 years of in-house R&D. As an R&D-focused company, our primary strategy is the continuous in-house optimization of critical components for the GEO heat engine. Both 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/CuuzznsrQcym-GEO-introduction_brief.pptx, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/CuuzznsrQcym-GEO-introduction_brief.pptx https://drive.google.com/file/d/1DUm6mOVjf7MYsFGmgf_6xKA_7wqq8jec/view?usp=drive_link Yes. Our mission is to defeat global warming through innovation by enabling the massive-scale replacement of carbon-heavy baseload fossil fuel plants with continuous, economic renewable energy. NA NA checked
Aug 25, 2026 @ 11:28 PM Aadhar Gupta s21007@students.iitmandi.ac.in http://NA http://NA +91 9568044473 Aadhar is responsible for technology, software devlopment. Responsible for leading the technical direction of the startup with vivek,and both are developing the product roadmap, and representing the company while seeking funding and strategic partnerships. We met at IIT Mandi since four yeaars back and we are working on this project since last 8 months. 2 We are coordinating together as a team and We actively listen to each other’s suggestions, respect everyone’s opinions, and make decisions collaboratively. Bharat-H2 NA Gujrat,Rajasthan Indias green-hydrogen sector is dominated by giant, capital-heavy plants (Rs 300+ crore) that are out of reach for small enterprises. Bharat-H2s innovation is not new chemistry but a replicable, asset-light business and engineering blueprint that makes green hydrogen profitable at MSME scale. Its Zero Power-CAPEX model co-locates a modular 5-10 MW plant behind an Independent Power Producers substation at a renewable hub (solar/wind in Khavda or Jaisalmer, or hydro), buying power on a fixed behind-the-meter PPA at about Rs 2.6-3/kWh and bypassing grid transmission, wheeling and banking charges. Capital is cut further by leasing the electrolyser (Electrolysis-as-a-Service), choosing low-cost Alkaline electrolysis with abundant nickel-iron catalysts instead of precious-metal PEM, tolling ammonia synthesis at existing fertiliser plants, and using SEZ / Green-Hydrogen-Hub plug-and-play water and grid infrastructure - together lowering Day-1 CAPEX by up to 70. A second differentiator is an integrated dual-product design: half the hydrogen is sold domestically and half is converted to green ammonia for premium export. Finally, it stacks every available incentive - SIGHT (Rs 50/kg), ISTS transmission waiver, IREDA concessional debt and the Gujarat Green Hydrogen Policy 2025 into one financeable model. The result is a low-barrier, modular template that a small enterprise can build, prove and scale from 5 to 20 MW We are solving the problem of pollution by the production of hydrogen. Concept: A modular 5-10 MW green-hydrogen micro-plant built behind an IPP renewable substation. Ultrapure water is supplied by compact reverse-osmosis units, reusing industrial wastewater or clean hydro water (9-11 litres per kg H2). A leased Alkaline electrolyser splits water into green hydrogen and oxygen using low-cost renewable power. Output follows a 50/50 strategy: half the hydrogen is purified, compressed and supplied to nearby refineries and SECI green tenders the other half is converted to green ammonia - via a small modular Haber-Bosch skid or a tolling agreement with an existing fertiliser plant - and exported through Gujarat ports such as Kandla or Mundra. Objective: To produce certified green hydrogen (at or below 2 kg CO2 per kg) at globally competitive cost, and to prove that green-hydrogen manufacturing can be profitable at MSME scale by minimising capital and stacking policy incentives. The venture aims to secure bankable offtake for at least 70 of output before investment, create skilled clean-energy jobs, deliver a replicable and financeable blueprint, and scale modularly from 5 to 20 MW while supporting Indias decarbonisation and green-export goals. We want to produce and sell hydrogen at very low cost. Idea Pilots Goverment, Pvt Ltd, and export to other countries NA NA NA NA NA we will approach goverment, pvt ltd, and export to other country Our go-to-market strategy will follow a pilot-first, B2B-led approach. We will initially identify a focused group of target customers in Bengaluru and the Bommasandra industrial ecosystem, understand their specific pain points, and offer pilot deployments at a low initial cost or through strategic partnerships. Based on pilot feedback and measurable outcomes, we will refine the product, build strong customer case studies, and convert successful pilots into paid contracts. We will acquire customers through direct industry outreach, strategic partnerships, networking, referrals, industry events and digital marketing. Once we establish product-market fit in Bengaluru, we will expand to other industrial hubs and cities across India. Our long-term strategy is to build a scalable technology platform with recurring revenue, while using strategic partnerships and investor funding to accelerate market expansion. Our key focus will be validate → pilot → convert → scale. Our long-term vision is to build a scalable, technology-driven company that solves a meaningful real-world problem and creates measurable value for businesses and society. We aim to establish ourselves first in Bengaluru and India, build a strong and sustainable customer base, and then expand into international markets. Over time, we want to develop our solution into a trusted industry platform, continuously innovating through AI, automation and data-driven technology. Our goal is not only to build a successful business, but also to create employment, develop strong industry partnerships, and contribute to India’s growing technology and innovation ecosystem. With the right mentorship, industry access and funding, we envision building a globally competitive company from India. NA NA Yes We are applying to the IITACB Incubator because we believe our startup can grow significantly faster with the right combination of mentorship, industry connections, technical guidance and access to investors. IITACB’s strong IIT ecosystem can help us validate and strengthen our technology, refine our business model, connect with potential industry partners and early customers, and prepare for fundraising. The opportunity to learn from experienced mentors and interact with entrepreneurs, researchers and industry leaders will help us avoid common early-stage mistakes and accelerate our path to product-market fit. We are particularly interested in leveraging IITACB’s network to conduct real-world pilots, build strategic partnerships and connect with potential investors. In return, we aim to contribute with a problem-focused, technology-driven startup and build a scalable venture from India with global potential. During the incubation program, our primary goal is to move from an early-stage idea/prototype to a validated, market-ready and scalable product. We aim to achieve five key outcomes: 1. Product Validation: Test our solution with real users and industry partners, gather feedback, and improve the product based on actual market needs. 2. Product-Market Fit: Clearly identify our target customers, refine our value proposition, and establish a repeatable customer acquisition strategy. 3. Industry & Strategic Partnerships: Build connections with potential customers, technology partners and industry experts, particularly within the Bengaluru ecosystem. 4. Business & Fundraising Readiness: Strengthen our business model, revenue strategy, financial projections and investor pitch, and connect with potential angel investors and venture funds. 5. Scalable Growth: Develop a clear roadmap for expanding beyond Bengaluru and establishing the startup as a sustainable, technology-driven company with national and eventually global potential. By the end of the program, we want to have stronger technology, validated customers, meaningful industry partnerships, a clear revenue model, and a fundable business ready for the next stage of growth. Yes and also physical We plan to leverage the Bommasandra industrial hub and the wider Bengaluru market as an early customer-validation and scaling ecosystem. Bommasandra has a strong concentration of manufacturing, engineering, pharmaceutical, electronics, automotive and other industrial businesses, giving us access to potential B2B customers, pilot partners and domain experts. Our approach will be to identify industry-specific pain points, run pilot implementations with selected companies, collect real-world feedback and use these deployments to refine our product before expanding across Bengaluru and subsequently to other Indian markets. Bengaluru’s strong technology, startup and investor ecosystem will also help us access skilled talent, technology partners, enterprise customers and potential investors. Karnataka’s broader industrial ecosystem includes sectors such as EVs, electronics, aerospace, biotechnology, healthcare and innovation, creating opportunities for future expansion. IITACB can significantly accelerate this process by providing access to experienced IIT alumni, mentors, industry leaders, incubation infrastructure, maker spaces, industry-academic collaborations and investor networks. In particular, we would value IITACB’s support in validating our business model, strengthening our technology and product strategy, connecting with potential pilot customers, developing our investor pitch and facilitating introductions to angels and venture funds. Our objective is to use Bommasandra for real-world industry validation, Bengaluru for market access and talent, and IITACB as the bridge connecting our technology with industry expertise, mentorship and funding. No NA Yes Not applicable Our tech-enabled platform utilizes a Python (FastAPI) backend paired with a React-based operator dashboard hosted on AWS. Hardware telemetry from our solar infrastructure is ingested via MQTT APIs and stored in a high-performance TimescaleDB time-series database. To maximize profitability, we leverage Prophet forecasting models integrated with OpenWeather APIs to predict energy generation and optimize grid distribution in real-time. NA Our solution will be defensible through a combination of proprietary technology, real-world data, customer relationships and continuous product improvement. As we deploy the solution with early customers, we will build a proprietary dataset and domain-specific insights that improve the accuracy, personalization and effectiveness of our product. These learnings will create a data and technology advantage that becomes stronger with usage. We will also develop deep integration with customer workflows, making the solution more valuable and difficult to replace over time. Strong relationships with early industry partners, strategic partnerships and a growing customer base will further strengthen our position. Our long-term moat will therefore come from proprietary data + product intelligence + customer integration + industry partnerships + continuous innovation, rather than relying on a single technology feature that competitors can easily replicate. We evaluate our technology against competitors using measurable performance, reliability and user-experience metrics rather than relying only on feature comparisons. Our key benchmarks include accuracy, response time, system uptime, scalability, error/failure rate, data security and overall cost of operation. We conduct controlled testing against comparable solutions and validate our results through real-world pilot deployments with users and industry partners. We continuously monitor system performance through automated testing, logging and analytics, identify failure points, and improve the technology based on real-world feedback. As we scale, we will target high availability, faster response times and consistent performance under increasing workloads. Our objective is to build a solution that is not only technically competitive but also reliable, scalable and cost-effective in real-world operating conditions. We will use independently measurable KPIs and customer feedback to continuously benchmark ourselves against existing and emerging competitors. We follow a privacy-by-design and security-by-design approach. We collect only the data necessary to deliver the product, clearly communicate how it is used, and obtain appropriate user consent wherever required. Sensitive data will be protected through encryption in transit and at rest, secure authentication and role-based access controls. We will minimize data retention, maintain appropriate backups, and use anonymization or pseudonymization wherever practical. For compliance, we will align our practices with applicable Indian data-protection requirements, including the Digital Personal Data Protection Act, 2023, and any sector-specific regulations relevant to our customers. We will maintain appropriate policies for consent, data access, deletion, retention and breach response. As the product scales, we will conduct regular security assessments, vulnerability testing and access reviews, maintain audit logs, and work with qualified security and legal professionals to ensure that our practices evolve with regulatory and industry requirements. Our goal is to make privacy, security and compliance integral to the product architecture from the beginning, rather than treating them as an afterthought. If we will get electricity on subcidy on minimal rate then that will make our production at very low rate and then we also sell hydogen at very low cost. NA At 10× production, the biggest challenges would likely be energy availability, water supply, electrolyzer capacity, hydrogen storage and compression, safety systems, and downstream logistics. The first potential bottleneck would be the availability and reliability of low-cost electricity and water required for production. Increasing electrolyzer capacity would also require upgrades to power electronics, cooling systems, gas separation, compression and storage infrastructure. As production increases, maintaining consistent hydrogen purity, pressure and quality would become increasingly important. Safety would be a critical scaling consideration because hydrogen is highly flammable and requires appropriate leak detection, ventilation, pressure management and emergency systems. Therefore, safety systems would need to scale alongside production rather than being added later. Our approach would be to scale in controlled stages, validate each production level, monitor key parameters such as energy efficiency, hydrogen purity, equipment uptime and safety incidents, and use modular infrastructure wherever possible. This would allow us to identify bottlenecks early and expand capacity without compromising reliability or safety. yes, we have some phd scholar from iit delhi NA NA Both 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/MdnLto9hKq2j-BharatHGreenHydrogenBlockDiagram.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/MdnLto9hKq2j-BharatHGreenHydrogenBlockDiagram.pdf http://NA Yes. Hydrogen production can be affected by regulations related to environmental clearances, electricity and water usage, hazardous-gas handling, storage and transportation, fire and industrial safety, and applicable quality standards. For green hydrogen, additional considerations include the sourcing and traceability of renewable electricity and compliance with applicable green-hydrogen certification requirements. As production scales, requirements for pressure systems, hydrogen storage, transportation and facility safety may also become more stringent. We plan to manage these risks through a compliance-by-design approach. Before each scale-up stage, we will identify the applicable central and state regulations, obtain the required approvals, follow recognized safety and engineering standards, maintain proper documentation and monitoring systems, and work with qualified regulatory and safety experts. Our goal is to ensure that regulatory compliance and safety are built into the production process from the beginning, allowing us to scale without creating avoidable regulatory or operational barriers. NA DORA Office IIT Mandi NA checked
Aug 25, 2026 @ 10:45 PM Karan Raj K R karanrajkr2008@gmail.com https://www.linkedin.com/in/karanrajkr/ http://karanrajkr.com +91 9535773370 Founder We met in our first year at NIAT–S-VYASA University in Bengaluru and started working together within a few months. We've been building together for about a year — KĀRYO started in August 2025. In that time we've shipped client projects, done door-to-door outreach to businesses across Bengaluru together, and competed as a hackathon team, including reaching the TakeOver'26 finals. 1 We ship and we sell. Most student teams do one or the other. The split is clean — Havinash owns frontend, I own backend, business development and client outreach — so nothing gets duplicated and neither of us blocks the other. We've taken KĀRYO from zero to paying clients by walking into businesses and asking for the work, and delivered production projects including the ISKCON Visakhapatnam website. We also build fast under real constraints: at the TakeOver'26 finals we designed, built and demoed a working client-onboarding product in 24 hours. The strength isn't a single skill — it's that we've already gone from cold conversation to delivered, paid project, repeatedly, while studying full time. Karyo karyo.online Bangalore KĂRYO is a Bengaluru digital agency that brings local businesses online - websites, Google Business profiles, and the systems to run enquiries and payments. Most small Indian businesses have no working online presence — no site, an unclaimed Google listing, enquiries scattered across WhatsApp — and the agencies that could fix it price for enterprises and won't take a 730,000 project. We productise what a small business actually needs into fixed-price, fixed-timeline packages: a fast website, a properly set up Google Business Profile, and a WhatsApp- based enquiry and payment flow the owner can run themselves. We win clients the way they buy — in person and in their own language. We've done door-to-door outreach across Bengaluru to clinics and local businesses rather than waiting on inbound. Delivery runs on a modern stack (Next.js, Tailwind, Supabase) with Al-assisted development, so two people ship in days what a traditional agency needs a team and several weeks for. That's what makes small-ticket work profitable instead of charity. We've also built our own internal tooling — a client onboarding system that turns a signed brief into contracts, quotations and GST invoices automatically - which removes the admin overhead that normally caps how many small clients an agency can carry. Cost structure and distribution. Al-assisted delivery plus our own onboarding automation means we can serve the 720k-50k segment profitably, which most agencies structurally cannot. And we acquire clients face-to-face in a market where trust is local — a channel that doesn't get out-bid the way ad auctions do. Revenue Revenue, Testimonials Consumer-facing small businesses in Bengaluru and Karnataka — dental clinics, small hospitals, schools, retail and service establishments with 5-50 staff. Typically owner- operated, with no in-house marketing person, currently running on WhatsApp and word of mouth. ~ 721,000 crore. India has 4.72 crore MSMEs registered on Udyam as of June 2026, 98.9% of them micro. Assuming ~15% are consumer-facing businesses that would buy a 730,000 online-presence package, that is ~ 70 lakh businesses. ~ 71,000 crore. Karnataka is a top-10 Udyam state; applying the same 15% addressable filter to the state's registered MSME base gives roughly 3.5 lakh target businesses. concentrated in Bengaluru. 72-3 crore over 3 years. Constrained by delivery capacity, not demand: 2 founders today at 3-4 projects/month, scaling to a team of 8-10 by year 3. Fixed-price project fees of 720,000-R1,25,000 per engagement depending on scope, plus monthly retainers for hosting, maintenance and listing management. Recurring retainers are the growth lever — one-time builds fund the business, retainers compound it. Local freelancers and small web shops on the low end; established agencies on the high end who won't take sub-71 lakh projects. Also DIY tools (Wix, Shopify) and free listing setup - but those require owner time and skill that our customers don't have. Direct in-person outreach. We have walked into clinics and businesses across Bengaluru and pitched face-to-face, plus referrals from delivered projects. We're now adding an inbound channel — founder-led content on Instagram and LinkedIn, and paid search where buying intent is explicit. Vertical by vertical. We pick one category — currently dental clinics and schools — build a reference customer and a category-specific package, then use that reference to sell the rest of the category. Repeat the pattern in the next vertical. It compresses the sales cycle because every prospect sees a business identical to theirs already using us. To become the default way India's small businesses get and stay online. The agency proves what these businesses actually need; the software productises it. We're already building internal tooling that automates client onboarding, contracts and GST invoicing, and category-specific products like clinic management. The end state is a company where services acquire the customer and software retains them. Not yet incorporated. Operating as a proprietorship; registration is in progress. NA — bootstrapped, funded entirely from client revenue. Yes We've built KÄRYO to paying clients on our own, but we've hit the limits of what two student founders can figure out alone — pricing, contracts, hiring, and how to turn a services business into something that scales. IITACB gives us access to operators and IIT alumni who have solved exactly these problems, and a Bangalore network we can't reach by cold outreach. We're also physically close: our campus at S-VYASA in Jigani is adjacent to Bommasandra, so this is our local ecosystem, not a remote one. Three things. First, convert our services revenue into a repeatable model - standard packages, standard pricing, predictable delivery. Second, validate whether our internal onboarding automation can become a standalone product with paying customers outside our own agency. Third, build a customer pipeline in the Bommasandra and south Bangalore business corridor. Concretely: we want to exit the programme with a defined product line, a repeatable sales process, and revenue several times where we start. Yes, but we'd prefer in-person. Our campus is in Jigani, minutes from Bommasandra, so we can be on site regularly. Bommasandra is dense with manufacturing, pharma and engineering MSMEs - precisely the businesses that have no real online presence and no in-house marketing capability. That is our customer, concentrated in one industrial corridor rather than scattered across the city, which makes in-person acquisition efficient. One reference customer in a cluster like that sells the next five. IIT ACB helps in two ways: credibility, since being incubated changes how an established manufacturer treats two young founders, and introductions, since a warm intro through the alumni network replaces months of cold calling. We'd also use the hub as a testbed for a B2B-manufacturer package, a segment we haven't served yet. Yes A dedicated workspace to work from outside hostel and class hours, and to hold client meetings somewhere credible rather than a café. Access to mentors and the alumni network for pricing, contracting and hiring decisions. Investor-connect sessions to understand what the software side of our business would need to be fundable. And proximity to other founders in the space — most of them are potential customers or referral sources for exactly what we do. Yes Supporting feature Client sites: Next.js 16 / React 19 / TypeScript / Tailwind v4, deployed on Vercel. Backend and auth on Supabase (Postgres with row-level security). Internal document-automation service: Fastity service exposing extract, fill, convert, render and invoice endpoints. Uses docxtemplater for docx placeholder substitution and headless LibreOffice for PDF conversion, containerised via Docker. Bearer auth, magic-byte file validation, per-request temp cleanup. LLM inference via Groq (Llama 3.3 70B) for field detection. Delivery is Al-assisted throughout — coding agents for scaffolding and implementation, with human review before anything ships to a client. None currently. We hold no proprietary dataset. What we accumulate is operational: templates, pricing, and delivery playbooks per vertical, which reduce time-to-delivery on each subsequent client in the same category. That's a process advantage, not a data moat, and we'd rather state that accurately. Cost structure and distribution rather than technology. AI-assisted delivery plus our own document automation lets us serve 720k-50k projects profitably, a segment traditional agencies structurally cannot reach. Acquisition is face-to-face and local, a channel that can't be out-bid the way ad auctions can. Delivery-side metrics rather than model benchmarks: time from signed brief to live site, defect rate at handover, and client-reported time saved on admin. On the document service specifically, we test for output fidelity. Our test suite covers 73 cases including pixel-level comparison of source templates against rendered PDFs, measuring maximum x-axis deviation in points across font substitutions, plus reflow testing across three value-length profiles to confirm page count and layout hold. Client and customer data is the main concern. Our clinic product is architected so each clinic owns its own database under its own account — we build it but don't hold the data. Row-level security is enforced at the database layer and tested with multi-tenant isolation checks. Where AI touches clinical workflows we apply hard guardrails: the system does not generate drug names or dosages. For the clinic product: India's DPDP Act creates data-processing obligations, requiring a data processing agreement per clinic. Longer term, ABDM/ABHA integration may become expected in healthcare software. For the agency itself, GST compliance on invoicing. None are blockers, but the healthcare product needs DPA coverage before it handles real patient data at scale. Delivery capacity first — this is a services business, and revenue currently scales with founder hours. That's the constraint the software line is meant to remove. Technically, the document rendering service is the known weak point. Headless LibreOffice ignores embedded OOXML fonts on PDF export and falls back to substitutes, which causes layout deviation when a template uses a font with no metric-compatible free equivalent. Aptos, Word's default since 2023, has no licensable substitute for Linux. Our mitigation is upload-time font detection with a rendered preview so users see the real output before sending, but at 10x volume this needs a proper rendering pipeline. No dedicated deep-tech team. Two founders: one on backend, AI integration and business development, one on frontend. Both are CSE (AI/ML) students. We are applied engineers, not researchers — we integrate existing models rather than train them. No proprietary datasets and no registered IP — no patents or trademarks filed. Stack is standard open source: Next.js, React, Tailwind, Fastify, Supabase, docxtemplater, LibreOffice, all under permissive or copyleft licences used within their terms. LLM inference via commercial API (Groq). One licensing constraint we've documented: Microsoft's Aptos font cannot be redistributed under its EULA, so we design around it rather than bundle it. Expand the automated test suite as we add document types and verticals. Widen font coverage where licensing permits and improve upload-time detection. Convert internal tooling from mock data layers to production data paths. Instrument delivery time per project so improvement is measured against a number rather than a feeling. India first, by design. Our advantages are India-specific — GST invoicing, UPI payments, WhatsApp-based workflows, in-person local sales, and rupee-denominated pricing that works at small ticket sizes. The document-automation product is jurisdiction-agnostic and could go global later, but small-business services are won locally and we don't intend to dilute that focus. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/EYcBo0wLfd3E-KARYO-Pitch-Deck.pptx, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/EYcBo0wLfd3E-KARYO-Pitch-Deck.pptx Partly, and I'd rather be precise about it than overclaim. KĀRYO is a commercial business, not a social enterprise. But the segment we serve is one the market ignores: small owner-run businesses that every agency has decided aren't worth serving. A clinic in Gubbi or a shop in Bommasandra has the same need for a working online presence as a company in Koramangala, and no realistic way to get one. Making that affordable has a real effect on their revenue. Two things beyond the core business. We intend to create internship opportunities for students at our own college and others — access to real client work is scarce for students outside the top institutions, and we're in a position to change that for a few people. And our school ERP work is aimed at small Karnataka schools that established vendors won't support properly, where better fee and record systems free up administrative staff time. Both founders are full-time B.Tech CSE (AI/ML) students at NIAT–S-VYASA, Jigani, minutes from Bommasandra. We've been building and selling alongside coursework since our first year. Portfolio: karyo.online. IIT Alumni Centre, Bengaluru (IITACB) whatsapp channel checked
Aug 25, 2026 @ 10:45 PM Dr Sanjan Gupta sanjan.tp@biotech.iitm.ac.in https://www.linkedin.com/in/sanjan-t-p-gupta/ http://Under%20construction 9004633645 Founder and CEO Currently, I am solo founder and am actively scouting for a co-founder ... open to clubbing with IIT-ACB cohort applicants if our goals and values are synergistically aligned. 1 B.Tech. with honors from IIT-Madras + PhD in AI for HealthTech from University of Wisconsin Madison, USA + Worked on data-science projects in Fortune 500 orgs in USA + AI Professor of Practice (Taught grad level courses to MS/PhD students as a guest faculty) + AI Technical Advisory Board Member (to help set up new AI CoE) + 5 invention reports, 11 peer-reviewed scientific publications, 1 book chapter and 4 funded proposals (7.5k USD to 2 million USD or 7.5 lacs INR to 15 Crore INR range). Stealthmode AI Startup Under construction Mumbai but very much open to relocate to Bangalore Clinical decision support system powered by scientific first principles and AI Working on solving niche problems in radiology and ophthalmology Building a digital platform that can act as an aid to doctors and health-care providers that is powered by AI and first principles scientific modeling. Specifically focusing on solving niche problems within radiology and ophthalmology. Building IP based, clinically validated, scientifically backed decision support system and not just a vanilla AI offering Idea Users, Signups, Testimonials Large-bed multispecialty hospitals for phase-1; Small clinics and anganwadi centers in semi-urban/ rural areas for phase-2 $ 26.32 Bn (global market) 834 Cr 100 Cr in 8-10 years SAAS licensing for private sector global players and govt contract orders for rural deploys No direct competitors but indirect competitors include big players like Samsung, Philips, GE Healthcare as well as established startups like Qure.AI Through freemium pricing model, promos at medical expos, and B2B sales channel setup. Private sector large hospitals & govt contract orders for rural deploys followed by global markets Build an R&D centric healthcare scientific research foundation that acts as a launch-pad for multiple game-changing products proudly built in India for rural to global markets. An organization wherein the work fabric is built on mutual respect that fosters employee growth -- amazing researchers who are passionate about what they do is an intended by-product 🙂 In process Self-funded Yes (1) Connets to early stage customers/ adaptors (2) Office space and community (3) Pre-seed stage funding based on founders credibility and vision Build the MVP, at least one pilot run with customer, and pre-seed stage funding yes Connects to top-tier hospitals in Bangalore, potential co-founders from IIM-B and IISc student/ alumni, and the startup ecosystem of Bangalore will come handy Yes Focused environment for building the startup on a fast-track basis with like-minded folks Yes Core engine SVLMs (Small Vision Language Models) fine-tuned for niche models combined with first principles scientific modeling Looking for potential hospital connects to tap into proprietary data and/or govt contract work orders for rural clinical studies IP backed, wholistic solutions for clinical not just vanilla AI offerings in pre-clinical or post-clinical modules Thorough benchmarking will be done post MVP phase along with scientific principles Will be exploring federated learning as well as following the DPDP and HIPAA guidelines Yes, potentially but that's also the USP to keep large number of competitors entering the space Too early to answer this Yes, PhD in AI for HealthTech from USA + B.Tech. with honors from IIT-Madras Phase 1 will be based on open-sourced resources while phase 2 will explored licensing proprietary data actionable deliverables will be set for every quarter and superior technology is going to be our USP phase-1: India market, phase-2: global market 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/f73Y0AbieUox-Biosketch_Dr_Sanjan_Gupta_hc.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/f73Y0AbieUox-Biosketch_Dr_Sanjan_Gupta_hc.pdf Mission driven to build a world-class R&D centric ecosystem that can act as a launch-pad for multiple game-changing products from India for the global markets as well as rural population NA checked
Aug 25, 2026 @ 10:14 PM Srinivas Rao Nalla srinivasrao.nalla@gmail.com http://www.linkedin.com/in/srinivas-r-nalla-b57766a http://NA +16786447771 I have worked across Technical (SW development), Pre-sales, Sales and Executive roles over 26 years. I'm the founder and have a core team and advisors who are IIT alumni as well. Beas Dev Ralhan - IIT Bombay. We met in 2000 after my graduation when he was the key developer for Party Gaming Jailendra Kumar - IIT Bombay. We met at Samsung R&D where he hired me in 2003 and have been in touch across organizations. Venkat Nandimandalam - IIT Roorkee. We met at Terralogic in 2015. I was part of the sales leadership team in USA. 1 We bring together multiple decades of experience and background to conceptualise and build the technology levers needed to disrupt the high entry barrier and opaque industry of private charters. Indus Jets Pvt Ltd NA Hyderabad We are building India's first technology-led private jet and EVTOL sharing marketplace with global expansion capabilities We are solving the cost ballooning, plane sharing and opaque booking structure problems that exist the private charter market. An Intelligent booking engine based solution optimizing “fill-rate” and eliminating “empty-legs” by aggregating and sharing private charter aircrafts using an AI-enabled technology platform leveraging mutual discovery and willingness to share. The result is a comfortable, time saving and lower cost (compared to traditional charter) flight plan with easy booking using our Smartphone APP. Our algorithms drive demand by matching members, dynamic pricing and operations scaling with route intelligence. MVP Signups Business owners, UHNI/HNI, Corporate executives 2600 CR 1040 CR 44 CR Charter margin + take-rate + membership JetSetGo, BookMyCharters, ClubONE Air IIT alumni network, UHNI/HNI events, Corporate sales NA The solution for private charter is scalable to support EVTOL integration in future - creating new revenue segments. This is an untapped market with disruptive vectors for the entire travel industry. Flying will be near or from the home. Indus Jets Pvt Ltd NA Yes It is a curated opportunity for IIT alumni and I believe the strategic push needed to disrupt a high barrier of entry and opaque business segment with a technology led solution will be more impactful by an IITACB Incubator startup. Seed stage funding, start revenue generation with our MVP and development of core components of our booking engine for Group formation Yes Bangalore is a technology hub with heavy professional travels by successful entrepreneurs and corporate executives between Mumbai (financial hub) and Delhi (political hub). The IIT ACB will be instrumental in unlocking networking options to onboard our anchor and connector members primarily in Bangalore and nation wide as well. Yes Yes Yes Core engine The fundamental concept underpinning our system is the division of labour among autonomous AI agents. Instead of a single, all-encompassing AI attempting to manage every facet of trip planning, the task is intelligently disaggregated into more manageable sub-problems, each handled by an expert agent. Dual-Database Foundation: Based on our method for private jet booking systems, the algorithm queries two separate databases simultaneously : Full charters DB Shared seats DB When a member searches for e.g BOM → DEL, our system: 1. Query both databases in parallel 2. Return both options in a single interface Allowing seamless toggling between full charter and shared seat pricing Our solution is based on demand (predictive member groups) - supply (Operator committed capacity) fulfilment using advanced technology - out moat. Current competition has limited technology to manufacture flights with 80%+ occupancy with consistency. NA Our product is GDPR compliant from the very beginning and we treat our UHNI/HNI personal data with outmost privacy. The data "insights" for this segment is the most valuable output of this solution. No Yes, DGCA regulations for aircraft movements are subject to regulatory issues. They may impact our Supply (Aircraft operators) The Supply - India has less that 200 aircrafts with a subset actually available in real time for private charter. Scale 10x will need to bring in aircrafts initially on wet-lease and subsequently on dry-lease. Yes - we are building our team of veteran IITians with deep knowledge of Artificial Intelligence LLMS. NA Our CI/CD strategy is under planning right now and we are developing our processes for auto code walkthrough and auto merge to mainline by an AI agent based on a working baseline after every master commit. Both 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/N7sOI3ISxjdH-Investor_Deck.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/N7sOI3ISxjdH-Investor_Deck.pdf We are a clearly defined impact-focused startup creating a new revenue opportunity with current general aviation and future EVTOL air mobility. Our members benefit with cost-effective general aviation opportunities and time saving with convenient access to near city airports and private airstrips and fast-track onboarding process. Our operators benefit with block charter agreements that provide reliable revenue streams in a volatile business environment. NA NA checked
Aug 25, 2026 @ 9:39 PM Jaydeep Vishwakarma jaydeepv.rs.met17@iitbhu.ac.in http://www.linkedin.com/in/dr-jaydeep-vishwakarma +33780727517 Founder & Technology Lead: Researcher in materials engineering and advanced manufacturing, with a focus on additive manufacturing, powder processing, sustainable materials and e-waste valorisation. Leading the development of an integrated WPCB recycling platform combining additive manufacturing, electrode fabrication, electrorefining of Cu and downstream recovery of valuable metals such as Au, Ag, Pd and rare-earth metals. Responsible for technology development, experimental validation, process optimisation, material characterisation, prototype development and translation into a scalable circular-economy Business . The co-founder is my brother and brings rich experience in social engagement, marketing and business strategy. His expertise complements my technical and R&D background by providing strengths in business development, market positioning, partnerships and strategic management. Together, we bring a combination of deep technical capability and business leadership that is essential for taking the technology from laboratory development to a scalable commercial venture. 2 Our biggest strength is the complementary expertise of the team-deep technical and R&D capabilities combined with strong business strategy, marketing and management skills. K-Photon Recycling Ambedkar Nagar, Uttar Pradesh We are building a deep-tech urban-mining platform that converts waste printed circuit boards (WPCBs) into strategic resources for India. By integrating additive manufacturing, electrorefining and selective metal recovery, we aim to recover high-value copper first, followed by precious and critical metals such as Au, Ag, Pd and other valuable elements, while also converting the non-metallic fraction into value-added products. Our vision is to turn India’s growing e-waste stream into a domestic source of critical materials, reducing dependence on primary mining and imports while enabling a scalable circular-economy solution. India is generating rapidly increasing volumes of e-waste, yet valuable copper, precious metals and critical materials remain under-recovered, while conventional recycling can be energy-, chemical- and waste-intensive. We are addressing this gap by converting e-waste into a domestic source of strategic resources through an integrated, lower-waste recovery and circular-manufacturing process. We are developing an integrated, closed-loop e-waste recycling platform that combines additive manufacturing, electrorefining and hydrometallurgy. After mechanical and physical separation, the metallic concentrate is converted into a conductive, high-surface-area electrode using binder-jet additive manufacturing technique and used as an anode for electrorefining to recover high-purity copper first. The resulting anode slime stream is then processed for recovery of valuable metals such as Au, Ag, Pd and rare-earth minerals. In parallel, the non-metallic e-waste concentrate is processed through binder-jet additive manufacturing to create value-added products. This enables us to recover multiple high-value resources from e-waste while reducing waste, energy, chemical and environmental burdens. We are not building another e-waste recycling plant-we are building an urban-mining platform. Our first demonstration will integrate binder-jet additive manufacturing with electrorefining and selective metal recovery to convert e-waste into multiple high-value outputs: Cu first, followed by Au, Ag, Pd and other rare-earth metals, while simultaneously valorising the non-metallic fraction. Unlike conventional routes that primarily focus on metal extraction, our approach is designed to increase resource recovery per tonne of e-waste while reducing energy, chemical, water and waste intensity. The first milestone is a data-backed proof of improved recovery efficiency and unit economics; these results will define the quantified advantage for scale-up. Proprietary electrode design, binder/material formulations, process parameters and accumulated process data provide the basis for defensibility. MVP Pilots Our primary customers are authorised e-waste recyclers and WPCB processors seeking higher-value recovery. Secondary customers include electronics and metal industries, government agencies and public-sector organisations working on resource recovery and circular economy, and manufacturers using recycled materials. The modular technology can also be deployed or licensed across countries and other waste-intensive industries, creating international technology-transfer opportunities. ~USD 1.88B – India e-waste management market ~USD 853M – metal recovery/value-recovery segment ~USD 8.5M – initial 5–7 year target (~1% of SAM) Our primary revenue will come from the sale of recovered high-purity copper, followed by Au, Ag, Pd and other valuable/critical metals. Additional revenue streams will come from value-added products made from the non-metallic e-waste fraction, technology licensing, and B2B toll-processing/technology deployment with authorised e-waste recyclers. Our competitors include established e-waste and precious-metal recovery companies such as Attero and Eco Recycling (Ecoreco), as well as conventional pyro-, hydro- and mechanical-metallurgical recyclers. Our differentiation is the integration of binder-jet additive manufacturing with electrorefining and downstream metal recovery, while simultaneously valorising the non-metallic fraction. We will acquire customers primarily through partnerships with authorised e-waste recyclers, e-waste processors, electronics manufacturers and metal/material buyers. We will begin with technology-demonstration and pilot projects using real industrial e-waste feedstock, convert successful pilots into long-term processing or technology-deployment agreements, and build partnerships through industry networks, government programmes and strategic investors. We will follow a B2B, pilot-to-scale strategy: first validate the technology with authorized recyclers using real e-waste feedstock; then demonstrate recovery, purity, energy and economic advantages at pilot scale; subsequently deploy modular systems with recycling partners across India; and finally license/deploy the technology internationally and in other waste-intensive industries. Our long-term vision is to establish a new integrated and sustainable model for complete e-waste recycling that supports true circularity-from e-waste to recovered copper, precious and critical metals, and value-added products from non-metallic fractions. We aim to deploy our modular recycling technology across India through partnerships with recyclers, industries and government organisations, creating distributed urban-mining and circular-manufacturing capabilities. In the long term, we will adapt and commercialise the modular system for international markets and other waste-intensive industries. By increasing resource recovery, reducing energy and material consumption, creating multiple revenue streams from a single waste stream, and reducing dependence on primary mining and imported critical materials, we aim to create both significant environmental impact and a scalable, economically viable global business. Incorporated — K-Photon Recycling. The company has been legally registered and is currently developing its technology for pilot-scale validation and commercialization. No external funding raised to date. K-Photon Recycling has been developed through founder-funded and research resources, and we are now seeking incubation, strategic partnerships and seed funding to accelerate pilot-scale validation and commercialization. Yes We are applying to IITACB because K-Photon Recycling is at the stage of converting a validated deep-tech technology into a scalable business. We seek IITACB’s support in pilot-scale development, industry and e-waste-recycling partnerships, business mentorship, market access, IP/commercialisation strategy and investor connections. IITACB’s ecosystem can help us transform our integrated additive-manufacturing and electrorefining approach into a commercially scalable circular-economy solution for India and global markets. During the programme, we aim to leverage IITACB’s incubation ecosystem to build strong industry and academic networks, connect with e-waste recyclers and strategic partners, access technical and business mentorship, explore collaborations with relevant industries and institutions, strengthen our business and commercialisation strategy, and connect with investors for seed funding. We also aim to use IITACB’s ecosystem to accelerate pilot development and establish partnerships for scaling K-Photon Recycling across India and internationally. Yes, I am open to virtual participation. Bengaluru’s strong electronics, manufacturing and industrial ecosystem can help us access e-waste recyclers, electronics companies, technology partners and potential customers for pilot deployment. IITACB can accelerate this through industry networking, technical and business mentorship, incubation infrastructure, academic collaborations and investor connections, helping K-Photon Recycling move from validated technology to commercial scale. Yes We will leverage IITACB’s infrastructure for prototyping, industry collaboration, technology validation, mentoring and investor engagement to accelerate K-Photon Recycling’s commercialization. Yes Core engine e-waste separation → powder processing → binder-jet processing → electrode fabrication → Cu electrorefining → Au/Ag/Pd recovery, while the non-metallic fraction is converted into value-added products Proprietary experimental data linking e-waste composition, powder properties, binder formulation, printing parameters, electrode properties and metal-recovery performance. Integrated process architecture, proprietary process know-how, electrode design, material formulations and accumulated process-performance data create a technology and data advantage. We track Cu purity/recovery, energy consumption, chemical and water use, processing time, yield, reproducibility and cost against conventional recycling routes. Our current demonstration achieved ~99% Cu purity and ~50% energy savings. We protect proprietary process data and partner information through controlled access, confidentiality agreements and secure data handling, while following applicable e-waste, environmental, chemical and worker-safety regulations. Yes. India’s EPR framework, circular-economy initiatives and growing focus on domestic recovery of critical minerals from secondary resources support our business model. Key risks include e-waste authorisation, environmental compliance, hazardous-material handling, wastewater/residue management and regulatory requirements for recycling operations. The main challenges will be feedstock variability, powder handling, printing throughput, thermal processing, electrorefining capacity and downstream metal separation. Our modular architecture is designed to scale these units independently. Yes. The core team combines expertise in additive manufacturing, materials processing, e-waste recycling, electrochemical processing, business strategy and marketing. Proprietary value is being developed through process know-how, experimental data, material formulations and system design. By using experimental data and design-of-experiments to optimise powder, binder, printing, thermal and electrorefining parameters for higher recovery, purity, lower energy/chemical consumption and improved economics. Both — India first, followed by international deployment through modular technology licensing, partnerships and localised recycling systems. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/IHa8aMyHLwjt-K-Photon_Recycling_Pitch.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/IHa8aMyHLwjt-K-Photon_Recycling_Pitch.pdf https://jaydeepvishwakarma.in/wp-content/uploads/2026/04/metals-printing-2.mp4 Yes. K-Photon Recycling is mission-driven with a focus on sustainable e-waste recycling, resource security and circular manufacturing. We aim to turn e-waste into a domestic source of copper, precious and critical metals while valorising the non-metallic fraction. Our goal is to reduce landfill and dependence on primary mining, lower resource and energy intensity, and build a scalable circular-economy solution for India and global markets. NA Prof N.C. Santhi Srinivas (HOD); Department of Metallurgical Engineering IIT BHU Varanasi checked
Aug 25, 2026 @ 9:34 PM Rugved S M Patil by.rugved@gmail.com http://www.linkedin.com/in/rugved-patil-40197527b https://www.isostance.com/ 9136886950 Rugved Patil — Co-Founder M.Tech CSE student at IIT Gandhinagar with a research background in Computer Vision and AI, with a research paper currently under review. Leads the R&D efforts, focusing on Computer Vision, AI, and the development of the startup's core technology. Denish Sharma — Co-Founder Software Engineer with a B.E. from the University of Mumbai, specializing in full-stack web development. Responsible for building deployable software solutions and managing the platform's deployment, maintenance, and technical infrastructure. We met during our B.Tech studies in college and have known and worked together for the past seven years. 1 Our biggest strength is that we discuss ideas together and come up with better ways to execute them. We also complement each other well, one focuses on AI and Computer Vision, while the other handles full stack development and deployment. Isostance https://isostance.com/ Mumbai We are a B2B fashion tech venture providing phone camera body measurement and virtual tryon software for D2C ecommerce brands. Our mission is to shift the industry away from generic US/UK size charts toward standardized charts built specifically for Indian body shapes using IndiaSIZE standards, eliminating fit uncertainty and high return rates. Indian online fashion suffers from return rates as high as 30% to 40%, primarily driven by fit mismatch. Most brands rely on Western size charts that do not reflect unique Indian body shapes, forcing consumers to guess sizes, order multiple items, or abandon purchases entirely, costing brands millions in reverse logistics. We provide a lightweight API widget that integrates directly into a brand’s product pages. Through a quick smartphone camera scan, our technology captures accurate body dimensions, maps them to IndiaSIZE standards first, and then predicts the customer's exact size on the brand's chart. Furthermore, our platform feeds sizing deviation analytics back to brands, giving them clear, data driven insights to refine their manufacturing and sizing distribution. Unlike generic Western sizing widgets or manual input questionnaires, our solution combines real time camera scanning with native calibration to IndiaSIZE body proportions, specifically solving fit in ethnic and plus size categories. Our proprietary algorithms calculate precise fit deviations between standard body types and brand inventory, creating a high utility data loop that directly cuts return logistics costs while helping brands design garments tailored specifically to Indian bodies. Users Pilots Geographic: Digital first fashion brands operating in Tier 1 metro hubs, specifically Mumbai, Bengaluru, and Delhi-NCR. Demographic: High growth D2C apparel brands specializing in structured ethnic wear and plus-size fashion, where precise fit is critical. Behavioral: Brands routinely handling 25 to40% product returns, running expensive reverse logistics cycles, and losing sales to fit related cart abandonment. Psychographic: Margin focused, tech forward founders and category managers driven to cut logistics waste and build brand loyalty through innovation. 32.143B 6.7B NA Subscription 3DLOOK LinkedIn and Networking NA Our long term vision is to build the core AI foundation for digital human body modeling, solving complex fit and design challenges across global fashion. From there, we will expand our spatial computer vision technology into digital health and fitness tracking, translating real time body analytics into personalized wellness solutions. Ultimately, we aim to become the universal standard for precision body intelligence across both retail and healthtech ecosystems. NA NA Yes We are applying for early funding, founder mentorship, and guidance to refine our go-to-market strategy and close enterprise B2B pilots. As technical founders, our primary goal is to master the business and commercialization side, from B2B enterprise sales to executing a repeatable go-to-market strategy. Yes Bangalore is home to India’s leading D2C fashion headquarters, while the Bommasandra industrial belt houses dense apparel manufacturing and supply chain units. We can run live pilot tests with local fashion brands and validate our sizing data directly with Bommasandra garment manufacturers. IIT ACB can connect us directly to these brand decision makers, provide access to industrial partners, and mentor us on B2B sales execution. No We would love to participate online Yes Core engine JavaScript SDK, REST API, FastAPI, Docker, ViT-B (DINOv2) Backbone,r, Multi task learning, SMPL 3D Mesh Model, Cloud GPU Inference Collaboration with IndiaSIZE Competitors provide surface level fixes by mapping shoppers to existing, flawed size charts. We build defensibility through an upstream data loop that calculates true body-to-garment fit deviations. Brands use these proprietary analytics to adjust future manufacturing ratios and design patterns for Indian body types, creating high switching costs and a compounding sizing intelligence moat that simple frontend widgets cannot match. Accuracy of the model, Deviation Error Margin, Net Return Rate Reduction NA BA NA At a 10x scale, our centralized cloud GPU inference infrastructure will face bottlenecks and escalating compute costs, requiring us to scale multi region GPU clusters and transition to optimized on device edge processing. Yes. we have one member handling all core deep tech and AI research full time, with a strong background in 3D computer vision and machine learning from IIT. We also have a PhD mentor on board who advises us whenever we hit complex technical bottlenecks. We utilize open source frameworks, including architecture with Apache 2.0 licensed, fully open for commercial use and modification and public benchmark datasets like AGORA and BEDLAM for training. We will continuously fine tune our models using high quality, real world body scan data and sizing deviation data collected directly through live brand integrations. Specifically for India. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/dMESvfDUxXSB-testppt.pdf, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/TkMXmVG6dikA-testppt.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/dMESvfDUxXSB-testppt.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/TkMXmVG6dikA-testppt.pdf Yes, we are mission driven. Our goal is to replace outdated Western sizing standards across Indian fashion with normalized IndiaSIZE charts, eliminating the fit frustration, self consciousness, and massive reverse logistics waste caused by ill fitting clothes. NA NA checked
Aug 25, 2026 @ 9:03 PM Arjun Morya arjun.morya.cer24@itbhu.ac.in https://www.linkedin.com/in/arjun-morya-407249320/ http://NA 9950669088 Arjun Morya Co-founder & Product/Business Lead — B.Tech Ceramic Engineering, IIT (BHU). Responsible for product concept, customer problem identification, business model, market research, pitch development and coordination with potential manufacturing and incubation partners. Rishabh Co-founder & Technical/Product Development Lead — B.Tech Chemical Engineering, IIT (BHU). Responsible for technical feasibility, protein formulation research, product development and coordination with potential protein and manufacturing partners. Rishabh and I are college friends at IIT (BHU), Varanasi. We met through our college and developed a strong interest in building something together. Rishabh is pursuing Chemical Engineering and I am pursuing Ceramic Engineering. We started working together on TWISTY recently, combining our different technical backgrounds to develop the concept and explore its feasibility. 2 Our biggest strength is our complementary backgrounds and our ability to approach the same problem from different perspectives. Arjun brings a product, design and business perspective from Ceramic Engineering, while Rishabh brings a Chemical Engineering perspective relevant to protein formulation and product feasibility. As students, we are also highly adaptable and willing to learn, experiment and iterate quickly as we develop TWISTY from an early concept into a validated product. Twisty NA varanasi TWISTY is an early-stage protein beverage startup developing a single-serve, recyclable bottle with a two-twist cap that stores a pre-portioned protein serving separately from the water. Users simply twist to release the protein, shake and drink, eliminating the need to carry a separate shaker, scoop and protein powder. TWISTY aims to make daily protein consumption as convenient as grabbing a ready-to-drink beverage. Daily protein consumption is inconvenient. People who consume protein regularly have to carry a shaker, protein powder and scoop, prepare the drink, and clean the shaker after every use. This becomes especially inconvenient for students, gym-goers, office workers and travellers. TWISTY aims to remove this preparation and carrying hassle by making protein portable, pre-portioned and ready to mix when needed. TWISTY is a single-serve, recyclable protein beverage bottle designed to simplify protein consumption. It uses a specially designed two-twist cap that stores a pre-portioned protein serving separately from the water. The user simply adds water, twists to release the protein, shakes and drinks. This eliminates the need to carry a separate shaker, scoop and protein powder, making protein convenient for people on the go. Our differentiation lies in integrating a pre-portioned protein serving directly into a purpose-built two-twist dispensing cap, allowing users to release the protein only when they are ready to consume it. The solution combines protein, packaging and dispensing into a single convenient experience, eliminating the need for a separate shaker, scoop and protein container. Our potential defensibility will come from the cap mechanism, moisture-isolation and dispensing design, manufacturing know-how, supplier relationships, and consumer brand. We plan to evaluate IP and patentability as the prototype is developed. Idea Our primary target customers are gym-goers and fitness enthusiasts who already consume protein regularly. Our initial focus will be college students and hostel residents, followed by office professionals and travellers who need a convenient, portable protein option without carrying a shaker, scoop and protein powder. In the longer term, we aim to expand TWISTY into an everyday protein beverage for a broader consumer market. ₹8,350 Cr ₹707 Cr ₹5–10 Cr/year TWISTY will follow a direct-to-consumer, single-serve recurring revenue model. Customers will purchase individual recyclable protein bottles containing a pre-portioned protein serving. Revenue will come from repeat purchases by regular protein consumers, initially through online sales and campus/fitness channels, with potential expansion to gyms, retail and distribution partnerships. Our primary competitors are traditional protein powders consumed with reusable shakers, as well as ready-to-drink (RTD) protein beverages. Brands such as MuscleBlaze, Optimum Nutrition and Fuel One compete in the protein category, while RTD protein drinks compete on convenience. However, TWISTY differentiates itself by integrating a pre-portioned protein serving directly into a specially designed bottle cap, combining the convenience of an RTD beverage with the flexibility of preparing the protein drink at the time of consumption. We will initially acquire customers through IIT (BHU) as our pilot market, targeting gym-goers, students and fitness communities through campus gyms, student networks and direct product trials. After validating product-market fit, we plan to expand through gyms, colleges, fitness communities, social media and direct-to-consumer channels. Word-of-mouth and repeat purchases will be important for building the customer base. We plan to start with a focused pilot at IIT (BHU), targeting gym-goers, students and fitness communities. We will validate the product through user trials, customer interviews and initial paid sales, focusing on taste, convenience, pricing and repeat purchases. After validating product-market fit at IIT (BHU), we plan to expand to gyms, colleges and offices in Varanasi, followed by D2C and wider distribution across India. Our long-term vision is to make protein as convenient and accessible as a regular ready-to-drink beverage. We aim to build TWISTY into a leading convenient nutrition brand, starting with single-serve protein and eventually expanding into other functional and nutritional beverages. We want to change the way people consume protein—from carrying powders and shakers to simply picking up, twisting, shaking and drinking. NA NA Yes We are applying to IITACB Incubator because TWISTY is at an early stage and we need the right ecosystem to move from concept to a functional, validated product. We are particularly looking for mentorship in product development, guidance on the custom bottle and two-twist cap mechanism, connections with relevant manufacturers and industry experts, and support in customer validation and commercialization. As student founders from IIT (BHU), we believe an incubation ecosystem can help us avoid early mistakes, validate the idea systematically and build TWISTY into a scalable business. During the programme, we aim to take TWISTY from the concept stage to a functional prototype and validate its technical and commercial feasibility. We want to develop and test the two-twist dispensing cap, connect with suitable bottle and protein manufacturers, validate the product with potential customers, understand regulatory and manufacturing requirements, and refine our business model. We also seek mentorship and industry connections to prepare TWISTY for an initial pilot launch. yes Bommasandra offers a strong manufacturing ecosystem with thousands of industrial units, including food processing, chemicals, packaging and engineering companies, making it highly relevant for TWISTY's bottle and two-twist cap development. We plan to leverage this ecosystem to identify packaging and manufacturing partners, develop our prototype, obtain supplier quotations and eventually establish scalable production. Bengaluru also provides access to a large fitness, student, professional and startup ecosystem, which we can use for customer discovery, pilot testing and early market validation. Through IIT ACB, we hope to access experienced IIT alumni, mentors, industry experts, manufacturing connections, startup networks and investor introductions. IIT ACB specifically provides mentorship, maker/incubator facilities, industry-academic tie-ups and funding/investor access for early-stage startups. Our goal is to use Bommasandra for product development and manufacturing connections, Bengaluru for customer and market validation, and IIT ACB for mentorship, industry access and fundraising support. Yes We would like to leverage IITACB’s infrastructure for product development, prototyping, testing and early-stage validation of TWISTY. In particular, we would benefit from access to technical facilities, product-development resources and expert mentorship for developing and refining our two-twist dispensing cap and recyclable bottle. We would also like to leverage the incubator’s industry, manufacturing, investor and startup network to connect with suitable packaging/cap manufacturers, protein suppliers and potential mentors. The incubation environment would help us move from our current concept stage to a functional prototype and validated pilot product. Yes Not applicable 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/W5rznNpXohCx-cc.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/W5rznNpXohCx-cc.pdf https://drive.google.com/drive/folders/1mW-hXBVJGB45Emoa2fhYu5rDDe9CCAb5?usp=drive_link Yes. TWISTY aims to make convenient protein consumption more accessible and easier to integrate into everyday life. We want to move protein beyond being a gym-specific supplement and make it a convenient beverage option for students, working professionals and everyday consumers. By offering pre-portioned servings in a recyclable, portable format, we aim to reduce the everyday friction associated with consuming protein while encouraging more consistent nutritional habits. Our long-term vision is to make convenient, affordable protein more accessible across India. NA NA NA checked
Aug 25, 2026 @ 8:41 PM Pankaj Yadav yadav_pankaj@iitgn.ac.in https://www.linkedin.com/in/yadavpankaj07/ https://sites.google.com/alumni.iitgn.ac.in/pylab/home +917587781458 Dr. Pankaj Yadav- Nanomaterials, Biomaterials; Dr. Dhiraj Bhatia- DNA Nanotechnology I was working as a PhD scholar with Prof. Dhiraj Bhatia and then to commercialize my PhD research we formed our startup Qnanosol biotech Private Limited 1 The biggest strngth our team is the founding team have strong research background both the founders are PhD and working towards applied reserach for combating the global challenges in healthcare. Qnanosol Biotech Private Limited https://www.qnanosol.com/ Gandhinagar Gujarat The company is 3 year old having foundation in biomaterials for healthcare applications Prostate cancer diagnosis The conventional methods of diagnosis MRI and CT scans are costly and few in numbers. Therefore, we are working on do-it-yourself kit for rapid prostate cancer diagnosis using fluorescent carbon-based nanoparticles. Home based self diagnosis kit , Over the shelf MVP Signups Men US 120 billion dollar US 120 billion dollar US 2.5 billion dollar Selling to PHC, diagnostic labs, CTK through Doctors, diagnostic labs providing service to government through Primary Health centers PHCs Our long term goal is to have multiplex healthcare diagnosis kit for rapid diagnosis for various types of cancer such as ovarian cancer, prostate cancer. In addition our novel fluorescent material can be used for various other applications such as QLEDS, Photovolatics. Incorported as Private Limited on october 10 2022 Confirmed Recivable of 40 Lakhs in grants Yes For connections and consultation and funding For connections and consultation and funding Yes For setting up the Industrial scale production of our carbon dots and then connecting us with the potential buyers No NA Yes Not applicable NA NA Plant based fluorescent carbon nanoparticles for both qualitative and quantitative diagnosis, which are biocompatible and environmentally friendly as compared to gold and heavy metal-based nanoparticles. The diagnosis result will be within 30 minutes and is do it yourself. Sensitivity, self diagnosis, home based diagnosis kit NA NA There are less regulatory risk since we are into diagnosis for us MD12 and MD13 will be required along with clean room facility of ISO class 7 NA Yes we are team of scientist having in expertise in nanobiotechnology for biomedical applications Indian Patent Published for our two product Patent Number 202321074777 , 202521086024 Yes we are improving ourself and adding new materials of improved quality in terms of stability, Quantum yield and biocompatibility Both 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/vPp92BfwsbC4-Startup_Presentation_2026.pptx, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/vPp92BfwsbC4-Startup_Presentation_2026.pptx https://www.youtube.com/watch?v=Lpei7HAI6ys The mission is driven by suppoeting made in India and Sustainable development goal 3 by United Nations NA NA NA checked
Aug 25, 2026 @ 7:57 PM Aditya Verma aditya.verma.phy22@itbhu.ac.in https://www.linkedin.com/in/adityav-iitbhu/ http://NA +91 7828455727 Saurabh Kumar - Founder & CEO, Final year undergrad in Engineer Physics IDD @IIT (BHU) Varanasi; Sachin Kumar - Co-Founder & CTO, prefinal year undergrad in Btech Metallurgical Engineering @IIT (BHU) Varanasi; Aditya Verma - Co-Founder & CPO, Final year undergrad in Engineering Physics IDD @IIT (BHU) Varanasi; Dr. Manoj Kumar Meshram - RF engineering lead and Strategic advisor, Professor Department of Electronics Engineering, Director, Ideation Innovation & Incubation Foundation (I3F), IIT(BHU), Varanasi Coordinator, Joint Incubation Center, IIT(BHU), Varanasi Coordinator, IFCI Venture Capital Fund for ST, IIT(BHU), Varanasi Ex-Professor In-charge, Entrepreneurship and Incubation, IIT(BHU), Varanasi Ex-Head, Department of Electronics Engineering, IIT(BHU), Varanasi Me (Aditya Verma) and Saurabh were classmates. Saurabh came up with the initial idea, and we started working on it together. Later, I approached Dr. Manoj K. Meshram Sir, who was also fascinated by the idea and decided to join us. During our first hiring process for interns across different roles, we met Sachin, who later became an important part of the founding team. The four of us have been working together for the past four months. We are currently at TRL 4. All Our biggest strength as a team is the combination of complementary skills and a strong bias toward execution. Each of us has a different skill set, so we have divided responsibilities based on our individual strengths. This allows us to move faster and take ownership of different aspects of the company while still working closely as one team. Saurabh focuses on the core idea and product direction, I focus on product development and hardware, Dr. Manoj K. Meshram Sir contributes in RF engineering and strategic advice, and Sachin focuses on software development. This combination allows us to cover the technical, product, and business aspects of the venture without unnecessary overlap. Beckkon Systems Pvt. Ltd. beckkon.com Varanasi Beckkon makes devices like smart ID cards and gateways for schools, connects them to the cloud, and gives schools real-time visibility of everyone on campus - with alerts, safety features, tracking, and communication all integrated into one platform, while giving parents greater peace of mind about their children's safety. Schools don't have real-time visibility of what is happening with students and people on campus. Information about attendance, movement, safety, transport, and incidents is often scattered across different systems or is only known after something happens. Beckkon is an integrated school safety and visibility platform built around four parts: 1. Smart ID Card - A lightweight ID card with up to 5 years of battery life. Students simply wear it like a normal ID card - no tapping, swiping, or scanning required. 2. Low-Cost Gateway Infrastructure - Gateways installed across the campus communicate with the ID cards and provide campus-wide coverage at around 1/100th the infrastructure cost of existing technologies. 3. School Dashboard - A single platform giving schools real-time campus visibility, including student location and attendance, a 3D digital view of the campus, ERP integration, instant safety alerts, and other school operations. 4. Parent App - Parents get real-time updates about their child's attendance, movement, transport, and safety, giving them greater peace of mind. Together, these give schools a simple way to know what is happening across the campus in real time and respond quickly when something needs attention. No tapping or swiping: Students simply wear the smart ID card like a normal ID; everything works automatically. Real-time campus-wide coverage: Schools can see where students are across the campus, rather than relying only on entry/exit scans. Very low infrastructure cost: Our gateway system is designed to provide campus-wide coverage at a fraction of the cost of existing technologies. Everything in one platform: Attendance, tracking, ERP, transport, safety, alerts, and parent communication are connected instead of being separate systems. Instant alerts: Schools and parents can be immediately notified when something unusual or unsafe happens. Built for schools: The hardware, software, and parent experience are designed specifically around the way schools operate. MVP Pilots Schools and Colleges 3.3 Lakh private unaided schools in India ~12000 (private unaided schools in India having fee more than 40K annually) ~2000 schools in 2-3 years Beckkon follows a hardware + recurring SaaS model. verkada, Leads School, SkoolSmart, PowerSchool Direct outreach We will start with private, established schools where student safety, attendance, transport, and parent communication are high priorities. Start with existing LOIs: We already have Letters of Intent (LOIs) from schools, which will form the initial base for our deployments and product validation. Pilot deployments: Begin with these schools, deploy Beckkon on campus, and demonstrate real-time tracking, alerts, and the dashboard in real-world conditions. Convert pilots into full deployments: Use the results and feedback from initial schools to refine the product and convert pilots into long-term customers. Expand district by district: Use successful deployments as references to acquire other schools in the same city and nearby districts. Target school groups: Approach school chains and education groups to deploy Beckkon across multiple campuses. Scale nationally: Once the product and deployment process are proven, expand across India through direct sales, referrals, and institutional partnerships. Our approach is to start with schools that have already shown interest, prove the product in real environments, build strong references, and then scale systematically across India. Our long-term vision is to build a global IoT + SaaS company that connects physical spaces to cloud software, starting with schools and expanding into multiple sectors. We aim to eventually serve: Schools Higher Education Government Cities & Counties Retail Manufacturing Healthcare Law Enforcement Banking & Finance Hotels & Resorts Restaurants Logistics We want to build a common technology platform that can be adapted to different industries, combining low-cost IoT hardware, cloud software, real-time visibility, alerts, and automation. We will start by becoming a leader in school safety and visibility, then use the technology and experience we build to expand into other sectors and become a large-scale IoT SaaS company. CIN: U62099UP2026PTC248903 NA Yes NO During the programme, we want to focus on product validation, customer deployment, and building the foundations for scale. Our key goals are: Complete and validate our hardware and software, including the smart ID card, gateways, cloud dashboard, and parent app. Deploy Beckkon in our initial schools, including schools with whom we already have LOIs, and convert these pilots into paying customers. Leverage IITACB's labs, maker spaces, and industry connections to improve our hardware and prepare for large-scale manufacturing. Work with IIT faculty, mentors, and industry experts to strengthen our technology, business model, and go-to-market strategy. Use IITACB's investor and alumni network to build relationships with potential investors and strategic partners. Build our Bengaluru software team and establish the operational base needed for expansion. Develop partnerships with manufacturers and suppliers in the Bengaluru industrial ecosystem to support scaling. By the end of the programme, we aim to have a validated product, paying customers, scalable manufacturing and deployment capabilities, and a clear path to expanding Beckkon across India. YES Bengaluru will be important for Beckkon as we scale our hardware and software operations. The Bommasandra area gives us access to manufacturing, electronics, engineering, logistics, and other industrial companies that can support our hardware development and deployment. IITACB is located directly within the Bommasandra industrial area and highlights its proximity to around 2,500 companies. Yes We primarily need office space in Bengaluru for our software and product development team. The space will provide our team with a professional working environment as we expand our software development and operations. We would also like to leverage IITACB's incubation infrastructure, meeting facilities, networking opportunities, and ecosystem to support our product development, business growth, and connections with potential partners and customers. Yes Supporting feature Our architecture consists of four main layers: Smart ID Card: A lightweight, battery-powered BLE ID card worn by students and staff. It communicates wirelessly with nearby gateways without requiring any tapping, swiping, or scanning. Gateway Infrastructure: Low-cost gateways are deployed across the campus to receive signals from ID cards and provide complete campus coverage. The gateways securely transmit the collected data to the cloud. Cloud Platform: Our backend processes and stores real-time location, attendance, and event data. It also handles alerts, ERP integration, analytics, and other school operations. Applications: The processed information is provided through a school dashboard and parent app. Schools get real-time campus visibility, attendance, alerts, and other tools, while parents receive relevant updates about their children. Frontend consist of Flutter Backend is in Golang Database: Pg SQL and Redis Cloud: AWS In simple terms: Smart ID Card → Gateway → Cloud → School Dashboard + Parent App. Our proprietary data advantage will come from the real-time, campus-level data generated through our own hardware infrastructure. Low infrastructure cost: Our gateway architecture allows us to provide campus-wide coverage at a significantly lower cost than many existing tracking technologies. No-friction experience: Students simply wear the ID card like a normal ID. No tapping, swiping, or scanning is required, making adoption easier. Growing proprietary data: As more schools deploy Beckkon, we collect real-world campus data that helps us improve location accuracy, alerts, analytics, and the overall product. Hardware + software integration: Competitors focused only on software or individual hardware products would need to replicate both our infrastructure and software ecosystem to offer the same experience. We evaluate our technology through both technical performance metrics and real-world school deployments. Our key metrics include: Location accuracy: Accuracy of student presence/location detection across different areas of the campus. Coverage: Percentage of the campus covered by the gateway infrastructure and consistency of coverage across buildings and outdoor areas. Latency: Time taken for an event detected by the ID card to reach the cloud and appear on the dashboard. Reliability: Successful event detection and data transmission rate under normal and high-density conditions. Battery life: Actual operating life of the smart ID card under continuous usage. Gateway scalability: Number of ID cards that can be reliably supported by a gateway and the performance as the number of devices increases. Alert accuracy: Detection rate and false-alert rate for safety and other configured events. System uptime: Availability and reliability of the cloud platform and applications. Infrastructure cost: Cost required to achieve complete campus coverage compared with alternative technologies. We continuously test these metrics in controlled environments and during school deployments. Our goal is to achieve reliable real-time campus coverage at significantly lower infrastructure cost, while maintaining a simple experience for students, schools, and parents. We treat student and school data as highly sensitive and design our system with privacy and security from the beginning. Data minimization: We collect only the information required to provide the service and avoid unnecessary personal data collection. Secure communication: Data transmitted between the ID cards, gateways, cloud, and applications is encrypted and securely authenticated. Access control: Schools, staff, and parents only have access to the information relevant to them, with role-based permissions. Secure cloud infrastructure: Our backend is hosted on AWS, with appropriate security controls, backups, monitoring, and access management. Privacy by design: Student location and activity data is handled with strict access controls and is not exposed to unauthorized users or third parties. Compliance: We will design and operate the platform in accordance with applicable Indian data-protection requirements, including the Digital Personal Data Protection Act (DPDP Act) and relevant rules and regulations. Data retention: We will define clear data-retention policies and securely delete data when it is no longer required or when legally appropriate. As we scale, we will conduct regular security reviews and audits and work with qualified security professionals to continuously improve our security and compliance practices. Yes. Since Beckkon deals with student location and personal data and uses wireless devices, there are some regulatory considerations. Data protection: Student and parent data must be handled in accordance with India's data-protection laws, including the Digital Personal Data Protection Act (DPDP Act) and applicable rules. Children's data: Since our users include minors, we need appropriate parental consent, access controls, data minimization, and safeguards for children's personal data. Wireless regulations: Our BLE smart ID cards and gateways must comply with applicable Indian wireless, radio-frequency, and equipment regulations. Cybersecurity: As a connected system handling sensitive school data, we need to maintain strong security practices and protect the platform against unauthorized access. We view these primarily as compliance requirements rather than barriers to the business and plan to work with qualified legal and technical experts as we scale to ensure compliance with applicable regulations. At 10x scale, the main challenges would be hardware manufacturing, deployment, data volume, and customer support, rather than the core technology itself. Hardware manufacturing: We would need to significantly increase production capacity for smart ID cards and gateways while maintaining quality and reliability. Gateway deployment: Deploying and maintaining gateway infrastructure across hundreds of additional campuses would require a larger installation and support network. Cloud infrastructure: The volume of real-time location and event data would increase significantly, requiring us to scale our cloud infrastructure, databases, and data-processing systems. Customer support: Supporting a much larger number of schools, administrators, and parents would require better automation and a larger support team. Data management: Managing large volumes of real-time data while maintaining low latency, reliability, and security would become increasingly important. We are designing the architecture to scale horizontally, using AWS, Golang, PostgreSQL, and Redis, so that computing and storage capacity can be increased as deployments grow. Our initial deployments will also help us identify and solve these bottlenecks before scaling significantly. Yes. We have an in-house technical team with expertise across RF engineering, embedded systems, hardware, firmware, and software development. Dr. Manoj Kumar Meshram, our RF Engineering Lead and Strategic Advisor, is a Professor in the Department of Electronics Engineering at IIT (BHU) Varanasi and brings extensive expertise in RF engineering, wireless communication, electronics, and technology development. Our founding team contributes expertise in embedded systems, electronics, hardware development, software engineering, and product development. Our software stack includes Golang, Flutter, PostgreSQL, Redis, AWS, while our hardware platform is based on BLE-enabled smart ID cards and low-cost gateway infrastructure. This combination allows us to develop and improve the core technology in-house, from the BLE hardware and RF infrastructure to the cloud platform and applications. We plan to continuously improve our technology through real-world deployments, data, testing, and customer feedback. Real-world testing: Monitor performance across different school environments, buildings, campus sizes, and device densities. Measure key metrics: Continuously track location accuracy, coverage, latency, battery life, gateway reliability, alert accuracy, and system uptime. Use deployment data: Analyze data from our growing network of schools to identify performance issues and improve our hardware, algorithms, and software. Customer feedback: Regularly collect feedback from schools, staff, students, and parents to identify problems and prioritize improvements. Hardware iteration: Improve the ID card, gateway design, power consumption, communication range, and reliability based on field results. Software updates: Continuously improve our cloud platform, dashboards, alerts, analytics, and mobile applications through regular releases. Continuous testing: Maintain automated testing and controlled experiments before deploying major hardware and software changes. Our goal is to build a continuous feedback loop where every deployment helps us improve the technology, making Beckkon more accurate, reliable, affordable, and scalable over time. Both 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/HLyeqyCE3eWa-Beckkon-Systems-Pitchdeck-Incubation-submit.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/HLyeqyCE3eWa-Beckkon-Systems-Pitchdeck-Incubation-submit.pdf Yes. Beckkon is mission-driven in its focus on making schools safer and giving parents greater peace of mind. Today, schools often rely on manual processes and disconnected systems for attendance, student movement, transport, and safety. Parents have limited visibility into what happens to their children during school hours. Beckkon aims to make this easier by providing real-time visibility, automatic attendance, instant safety alerts, and better communication between schools and parents through affordable technology. Our goal is to make this technology accessible not only to premium schools but also to well-established schools in smaller cities and towns, by keeping our infrastructure costs low. As we grow, we want to help create safer, more transparent, and better-connected schools while building a scalable technology company. Yes. Members of our founding team belong to the SC/ST community. Dr. Manoj Kumar Meshram - Coordinator, Centre for Innovation, Incubation &Entrepreneurship (CIIE), Indian Institute of Technology (BHU) checked
Aug 25, 2026 @ 7:00 PM Dr. Jaydeepsinh Pravinsinh Chavda jaydeepsinh3636@gmail.com https://www.linkedin.com/in/dr-jaydeepsinh-chavda-291a9690/ http://NA 7069030194 Director Prof. Iti Gupta is my PhD Supervisor. We worked together since 2020. 1 Research and Development of Novel cost effective synthetic methods of APIs (Active Pharmaceutical Ingredients) Chemsrajan Helathcare Private Limited NA Ahmedabad Indigenous costeffective method development of APIs and Novel Anticancer agents for photodynamic therapy Decrease their raw material dependency on China Indigenous cost effective method development of APIs and Novel Anticancer agents for photodynamic therapy Research and Development Cost effective method development Idea Users, Revenue, Pilots, Signups, Testimonials Pharmaceutical company Pharmaceutical company Incorporated NA Yes Academic innovation with scaled manufacturing No NA Yes Not applicable 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/G7c9ZhmmWaPR-PitchDeck.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/G7c9ZhmmWaPR-PitchDeck.pdf Alumni Relations, IIT Gandhinagar checked
Aug 25, 2026 @ 5:08 PM Nagarajan Viswanathan nagarajanv@thefingertip.in https://www.linkedin.com/in/nagarajan-viswanathan-a6393823%20 http://www.thefingertip.in +919686663343 Nagarajan V- Founder with 20 years of banking experience and 4 years as a Business head of corporate payment solutions and overall corporate life of 3+ decades, Kannan SS with 3+ decades of corporate experience with 7 years in banking and rest with other large corporates Colleagues during ICICI days managing unsecured for different states of the country 2 Domain Knowledge Transcendz Paysol Private Limited www.thefingertip.in BANGALORE Acceptance platform for commercial credit cards for B2B enterprises connecting Clients, Banks, Payment Networks & Gateways Real world issue of credit- both availability and usage of credit line on the card for Businesses for their cashflow management, revenue opportunity for Banks What is GPay, Phone Pe for UPI, What is POS for credit cards, What is NEFT, RTGS for Wire, Fingertip is for commercial credit cards, A Web and Mobile platform that just doesn't move money/payment, it moves credit & money together for Business enterprises for their payables and receivable, Enables credit utilization on the commercial cards for customers and enables interchage revenue opportunity for banks Multi Gateways by Design, Payable and Receivable in one single platform, unified interface, future ready eco system Revenue Revenue Large and Mid corporates and MSMEs, eligible to be carded $550Bn $220Bn $2Bn Platform Subscription fee, Integration fee, Transaction fee income Enkash as a platform, CMS as a category Bank as a channel, CUG & Cluster acquisition Issuing bank's existing customers & Network references - Anchor - Vendor Be a Platform of preference for Business enterprises, Banking Partners and Payment eco-system, Make the Businesses experience value through Cost saving, Control of money movement and Convenience of operation January 2023 Bootstrapped and LOI for INR 5 Mn Yes Networking, Strategic collaboration & Funding exploration Networking, Strategic collaboration & Funding exploration Yes Fingertip is just right for this eco-system coz our very purpose is to enable B2B cashflows Yes Employment Generation as the most preferred option Yes Supporting feature Fingertip follows a cloud-based application architecture with a web-based user interface, backend application services, databases, APIs. The architecture is designed to support secure data management, role-based access, integrations with external systems, and scalable deployment. s a startup, in our current stage with around 30 customers, we do not yet have a significant proprietary data advantage. However, Fingertip is continuously building a valuable dataset through customer-generated content like usage patterns, workflow data, and domain-specific information accumulated on the platform. Over time, this data can help improve personalization, recommendations, automation, and AI-assisted features, subject to customer consent and applicable data-protection requirements. Fingertip's defensibility comes from its established ecosystem and deep integration with the commercial payments workflow. Fingertip has tie-ups with 5 Payment Gateway (PG) providers, an exclusive agreement with one bank, and ongoing engagements with two additional banks. In addition, domain-specific workflows, customizable approval processes, split MDR capabilities, and integrations with banks and payment providers create differentiation and make the platform more difficult to replicate. Fingertip is a B2B platform where corporates log in and make payments to their suppliers using commercial cards, as well as make GST and utility payments. The platform is built on a cloud-based architecture with auto-scaling capabilities, enabling it to handle varying transaction volumes efficiently while maintaining performance, availability, and reliability. Continuous system monitoring is also implemented to identify and address performance or reliability issues. Fingertip is a PCI-DSS Level 1 certified platform and has maintained this certification for three consecutive years. The platform complies with the applicable requirements and controls prescribed under PCI-DSS Level 1, with appropriate security measures covering data protection, access control, secure development, monitoring, vulnerability management, and transaction security. Government initiatives promoting digital transformation and increased adoption of digital payments are supportive of Fingertip's business. In particular, initiatives encouraging the issuance and adoption of commercial cards for 1 million MSMEs, as well as micro-credit card initiatives linked to Udyam-registered MSMEs, can significantly expand the addressable market for commercial payment solutions such as Fingertip. Currently, we do not foresee any specific regulatory risks that are expected to materially impact Fingertip's business. We continue to monitor changes in applicable payment, banking, data protection regulations and will adapt the platform as required. Fingertip is hosted on AWS and its services are designed with auto-scaling capabilities to accommodate increases in transaction and user volumes. Therefore, even if transaction volumes increase by 10x, the platform is designed to scale automatically without a major impact on system availability or performance. Necessary monitoring and alerting mechanisms are also in place to identify and address issues proactively. We have an in-house technology team with expertise in software engineering, cloud-based application development, APIs, databases, and integration of AI/ML capabilities into product workflows. Our current approach focuses on effectively applying existing AI technologies and models to solve domain-specific problems rather than developing AI models from scratch. Fingertip does not currently rely on external datasets, open-source codebases, or third-party software components as core parts of its platform. The platform has been developed entirely by our in-house technology team using technologies such as React.js, Node.js, React Native, and MySQL. The application code, architecture, workflows, integrations, and product-specific implementations are developed and owned by Fingertip, subject to the applicable rights associated with the underlying development technologies. We follow an iterative product-development approach based on customer feedback, usage analytics, system monitoring, testing, and continuous enhancement of the platform. Both for India and Global Markets,Fingertip is being developed with both Indian and global markets in mind. While the initial focus is on solving relevant customer problems in India, the platform architecture is designed to support international customers, integrations, localization, and evolving global data and compliance requirements 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/66YEhidLb5CS-The-Fingertip-DECK-.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/66YEhidLb5CS-The-Fingertip-DECK-.pdf http://%20https://vimeo.com/1221113064/b3c5c98e4d?share=copy&fl=sv&fe=ci Fingertip is an Societal Impact Focussed startup, enabling MSMEs to benifit from organized credit thats unsecured and freeing the enterprises from the private loan sharks YES because of B2B Centricity Ganesh Chandrasekaran- Director, IITM Pravartak Incubated Company Winner of Elevate 2024, GoK, Grant-in-Aid checked
Aug 25, 2026 @ 4:32 PM Sudarshan Nagaonkar sudarshan@suchenix.com https://www.linkedin.com/in/sudarshan-nagaonkar/ http://NA +919867731333 Sudarshan has more than a decade experience in surgery related technologies. He enjoys the role of a product manager. NA 1 More than 10 years of surgery technology experience. Author of an Amazon bestselling book 'The Third Dimension of Surgery'. More than 1,000 hospitals served through strong distribution network. Presented to more than 1,000 surgeons. Suchenix Private Limited NA Bangalore Suchenix is in the domain of what is called as 'digital surgery'. Reducing surgical errors in laparoscopic surgery using technologies like AI. We have 3 products in the pipeline: - Web based training solution available to early surgeons to improve their surgical skills. - A surgery department head dossier generator that provides insights to the head of the department about the events happened in all the surgeries in the department. - A surgical co-pilot that advises the surgeon in real time during surgery. We do not know at the moment. We are in experiment stage. Idea All the hospitals in India that have laparoscopic camera systems of top brands. 6000 2000 600 One time sale plus annual subscription NA Leads from conferences, events, digital marketing and direct foot on the field. Direct as well as distribution through dealers. To cover the entire gamut of digital surgery, including expanding to robotic surgery and open surgery. Would also include additional share of wallet through coming out with our own laparoscopic camera systems. Incorporated in Apr 2026 60,00,000 No Access to mentors. Refining the business model, fine tuning technology roadmap. Yes. I am not sure if the Bommasandra industry would have any relevance for us. Yes Address for GSTIN :-). Access to various programs. Yes Core engine We are still in exploratory phase and it is difficult to share at this moment. We have access to hundreds of hospitals. Not clear at the moment. Too early to comment. We are considering all the applicable laws and regulations including CDSCO, US FDA, European CE and DPDP Act. The work is in progress. None. Yes, medical devices are highly regulated and it takes a long time to get regulatory approvals. Too early to comment. No. Still in experiment mode. We are trying many of these but too early to comment. Too early to comment. India first and then global with 2-3 years' lag. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/DUAdzru3ojYv-SuchenixDeckIITACB.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/DUAdzru3ojYv-SuchenixDeckIITACB.pdf http://NA Patient is the most important person in our business. Our mission is to improve outcomes for the patients with better utilisation of technology. No. Kamlesh Chaudhary I have been very brief in the application because we are still in experiment mode. checked
Aug 25, 2026 @ 2:24 PM R. Sudhir Shenoy sudhir@getomni.co https://www.linkedin.com/in/rsudhirshenoy/ https://www.getomni.co +919902029570 ROLES: Sudhir Shenoy - Cofounder, CEO and Praveen Sampath - Cofounder, CTO BACKGROUNDS: Sudhir Shenoy - 20+ years leading Product & Business roles globally, Led $100M ARR business at Verisign in Asia Pacific, Led 0-1 growth of a Cloud Telephony venture in India, Shouldered Product Management responsibility at Yahoo! APAC & Verisign, B.Tech, IIT Bombay · MBA, ISB Hyderabad AND Praveen Sampath - 10+ years in software engineering, Built AI data analytics agent at ThoughtSpot, Built Core maintainer of Blobstore - Rubrik's data backup core, Hands-on Machine Learning experience at LinkedIn and Google, B.Tech, Computer Science, IIT Bombay Praveen and I met through the IIT Bombay Alumni network in 2018 and we teamed up to do a side-gig to build an OKR software for Enterprises just to validate if the product has legs. Thereafter we have remained friends and noodled on a bunch of ideas since we both remain passionate about building something to create impact. In 2025, we both took the full time plunge into building and Growing Omni https://www.getomni.co - An Open Source harness that connects disparate software and systems in an enteprise and allows orgs to work with multiple AI models, including Open weight models. All Our biggest strength as a team is that we bring complimentary skill sets and experience. Praveen comes with strong hands technical skill set to architect and build technology products and Sudhir comes with a proven background in taking Tech products to Market - both with Large global companies as well as in Startups. We are also good friends and have a bond of trust and respect that forms the foundation of our working relationship Omni https://www.getomni.co Bangalore, India Open Source Harness to enable Companies to work with Multiple models using Company data SECURELY (including working with and connecting Open-weight models through a single layer) We are solving the problem of connecting company data that is fragemented across disparate systems (Mail, Slack, Drives, CRMs, Ticketing systems, Jira and many others) with multiple AI models using a single layer that can switch and route between different models Omni is an open-source, self-hosted platform that provides the infrastructure companies need to deploy AI on their internal data. It includes ready-made connectors to workplace applications, a searchable company knowledge layer, tools for running AI agents, and support for multiple model providers - both commercial and open-source. Companies retain control of their data and can choose the best model for each use case without vendor lock-in. Our core software is open source and this allows companies to extend the set of connectors to even integrate with lesser known Saas softwares and even homegrown systems, if needed. Companies can also audit the code and ensure compliance with internal security requirements Users Users, Signups Enterprises with more than 200 employees where there is a need for "governed" enterprise wide AI deployment We charge Enteprises maintence fees and a per user subscription charges Onyx.app, Glean.com Through network, referrals and through frugal digital marketing on Linkedin and Email currently Mix of digital marketing, content marketing and network referrals to get leads and free trial sign-ups and use a combination of inside and field sales to close the sale. Our long term vision is to make Omni the single, Model-independent layer through which ALL employees in Enteprises use AI to search for company knowledge as well as to automate mundane repititive tasks & workflows. Legal entity incorporated None Yes To gain access and acquire Enteprise customers through the IITACB network Get mentorship, network and acquire new customers Yes We can help willing companies in the Industry to leverage AI to increase productivity within their workforce. IIT ACB can help us get customers who are willing to work with us to implement AI enteprise wide No We are not looking to rent facilities. Our main driver is to access the IIT Bombay network for acquiring new customers or for early stage funding Yes Core engine Omni is open-source. GitHub: https://github.com/getomnico/omni The tech stack is Postgres (ParadeDB), Redis, Rust, Python, Svelte. AI Coding Tools: Claude Code. not applicable We are Open source and self hosted giving customers the advantage of protecting their sensitive company data Like already mentioned, we offer an open source self hosted technology stack which ensures that the company data is kept within their private infrastructure and also connect with APIs of private instances of hosted models such as the ones provided by AWS bedrock and the likes. This enables companies to ensure data privacy, compliance and security. NO Since we are a primarily a self hosted solution, scaling to 10x customers is unlikely to break us. But since we offer a hybrid index at the core of our solution, maybe massive data volumes may impact near term performance of the solution. These can be addressed with implementation specific interventions. We are just 2 cofounders at the moment. Praven comes with demonstrated hands-on experience with Machine learning and AI models Omni is open-source. GitHub: https://github.com/getomnico/omni The tech stack is Postgres (ParadeDB), Redis, Rust, Python, Svelte. AI Coding Tools: Claude Code. As and when we acquire more customers, we continue to work on improving performance wherever needed. Building for US and India. Currently have 4 customers using our product (2 US and 2 India) 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/PXBKm7gavBmu-Omni_merged.pdf, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/HxwpwttQBx9r-Omni-Introduction-Deck.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/PXBKm7gavBmu-Omni_merged.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/HxwpwttQBx9r-Omni-Introduction-Deck.pdf https://youtu.be/Gim_hwKZWgw We want to build a truly global AI venture headquartered out of India. We aim to make it very easy for Enteprises to leverage AI for improving productivity within their workforce without getting locked-in with any single or set of AI models. NA checked
Aug 25, 2026 @ 1:54 PM Mohammed Azzan Patni azzan@heykoala.ai https://linkedin/in/azzaxp http://NA 09964188684 Azzan Co-Founder and Director Customer Success, Atul BP Engineering Head Azzan and Atul met through Pace Wisdom Solutions a services and product engineering company and had worked together on delivery-side engineering before starting Koala AI Solutions. They have worked together for 2 years, and have been building HeyKoala full time since incorporation in Nov 2025. All We get things live inside real hotels, which is the part most AI teams never reach. Anyone can demo a voice agent. Very few can make one work against a live Oracle Opera or eZee instance, a property's existing EPBX and SIP stack, and a front-office SOP written by a GM who has no interest in changing it. The pairing matters too. One founder carries the commercial and domain side, including the OTA-commission pain we experienced first hand. The other carries the engineering, including every integration in production today. Neither of us needs to translate the problem to the other, so the loop from a customer complaint to a shipped fix is days, not quarters. HeyKoala AI https://heykoala.ai Bengaluru HeyKoala builds agentic AI voice and messaging agents for hospitality. Roughly 40 percent of hotel phone calls go unanswered, and around 85 percent of those callers never call back. For a luxury or upscale Indian resort with an ADR between ₹10,000 and ₹50,000, every missed after-hours call is a booking that walks to an OTA charging 15 to 25 percent commission on a stay the property could have taken directly. The property pays twice, once in the lost direct margin and once in the commission. An autonomous agent that acts, not a bot that replies. On a single call HeyKoala will recognise a returning guest by caller ID, check live PMS availability, quote a rate, collect a deposit over UPI or WhatsApp, block the room, write the reservation back to the PMS, raise service tickets to the right department and send the confirmation, then log the transcript, summary and analytics to the manager dashboard. Architecturally it is a multi-agent system with a maker-checker layer. A compound request such as extend my stay two nights, upgrade to a suite and book the spa is decomposed into specialised sub-agents, each validated before it commits, with full context maintained across the chain and graceful escalation to staff when confidence drops. Deployment needs no hardware. A property forwards its existing number. Self-serve tiers go live in under 30 minutes. Full integrated deployments run three to five weeks. 16. What makes your solution unique or defensible? Four things, in order of how hard they are to copy. In-conversation Indian payment rails. UPI, WhatsApp and Razorpay let us take money mid-call and auto-block the room. This turns an answered call into confirmed, commission-free revenue. Western voice AI tools do not have this and will not prioritise building it for India. Transaction completion through deep PMS integration. Oracle Opera and eZee are live in production today. Each PMS is four to eight months of work with its own API, data model and operational quirks. A large model vendor can match our conversation quality in a weekend and cannot match this integration library for years. Language depth that is native, not translated. 26 languages with mid-conversation switching and genuine Indian-accent handling, which is the difference between serving domestic and inbound luxury guests and merely transcribing them. Agentic AI in a Deep vertical integration with both geust and staff facing agents makes us unique. Revenue Users, Revenue, Pilots Beachhead: luxury and upscale Indian resorts and small hotel groups NA ndia premium plus English-speaking markets. Roughly 3,000 premium properties and 15,000 to 20,000 premium F&B outlets. Estimated annual software value of ₹450 to ₹550 Cr, approximately USD 55m to 65m. 24 to 36 months, to March 2029. Roughly 150 hotels and 800 F&B outlets, 3 to 5 percent of the premium SAM. Estimated ₹25 to ₹30 Cr, approximately USD 3m to 3.5m ARR. B2B SaaS subscription, priced per property per month by number of concurrent channels rather than per minute, because concurrency is what drives our delivery cost. Customers never see a per-minute rate. Inbound calls within a generous fair-use pool are unlimited. Indian horizontal voice AI: Gnani.ai, Skit.ai, Vodex, Slang Labs. Capable engines, but horizontal. They do not carry hospitality workflow intelligence or live PMS write-back. Founder Led Sales, Reference, Inbound Leads Land and Expand Strategy To become the AI operating system for global hospitality, winning first by leading India's luxury and upscale segment decisively within three years. The deeper thesis is that hospitality runs on thousands of small transactions that currently require a human to be awake, available and fluent in the right language. Every one of those is an agent-shaped problem. We start with the booking because it is the one with a rupee value attached, then move outward across the guest lifecycle and inward across staff operations. The India playbook, built on payment rails and language depth, then ports to the GCC and other emerging markets where the same conditions hold. Incorporated as Koala AI Solutions Private Limited Not External Funding, Friends and Family Yes Establish Credibility, Fine tune GTM, Explore Networking Build a selling motion that does not depend on the founder, so that logos 6 through 20 close on the playbook rather than on founder meeting time. yes Bengaluru as the AI talent and channel market. Our voice AI hiring pool, our PMS and POS partners including eZee, IDS Next, Aiosell, Petpooja and Posist, and FHRAI Karnataka are all here. Our beachhead geography, the Karnataka leisure corridor running to Coorg and Chikkamagaluru, is a weekend drive from the hub. The proximity is not incidental to the strategy, it is the strategy. No We would use the programme's facilities selectively rather than as a daily office, since our engineering team is remote-first. Yes Core engine A layered agentic system. Telephony and channel layer. Plivo plus custom SIP for voice, WhatsApp Business API, webchat and SMS. The property keeps its existing number and simply forwards it. Hotel deployments also integrate with EPBX and intercom systems. Speech layer. Third-party STT and TTS today, including Ultravox and Deepgram, with noise suppression and Voice Activity Detection in the pipeline. We are migrating to self-hosted open-source and licensed STT, LLM and TTS models on Jio GPU infrastructure, both to control unit cost and to reduce third-party dependency. Orchestration layer, which is the proprietary part. A multi-agent planner decomposes compound guest intent into sequential sub-tasks, dispatches each to a specialised sub-agent, and passes every state-changing action through a maker-checker validation layer before it commits. Full conversation context is maintained across the chain, with graceful escalation to human staff, transcript attached, when confidence drops. Integration layer. Two-way connectors to PMS (Oracle Opera and eZee live, IDS Next and Mews in build), POS (Petpooja, Posist, Rista) and CRM, plus payment rails on UPI, WhatsApp and Razorpay. We are implementing Model Context Protocol for standardised tool connectivity. Automation and analytics layer. Post-call actions fire automatically, including ticket creation, departmental routing, WhatsApp confirmation and CRM update, feeding a manager dashboard with live analytics, SLA tracking, transcripts and summaries. Infrastructure. Cloud-native on AWS, with hosting on Hostinger and GPU workloads on Jio. No on-premise hardware at the property for hotel deployments. We use Django, Fast API, MongoDB and PostgreSQL, React for Frontend. We hold an accumulated library of PMS and POS integration behaviour, including the undocumented quirks of each system in production, which is genuinely hard-won and reduces every subsequent deployment. Agents for Deep Vertical integration is the biggest moat with customer validation. What we measure today: call completion rate, meaning the agent resolved the guest request end to end without human escalation, escalation rate with reasons, latency from guest utterance to agent response, PMS write-back success rate, and per-minute AI delivery cost. Every call is recorded, transcribed and summarised, which gives us a complete audit trail for review.. Reliability engineering: graceful degradation to human escalation on low confidence, maker-checker validation before any state-changing action so a misunderstanding cannot silently corrupt a booking, and alternative-offering rather than conversation-dropping when an integration call fails. We are aligning to India's DPDP Act, including consent capture for call recording, purpose limitation and data-principal rights handling. Our move to self-hosted models on Jio GPU infrastructure materially improves our position here, since it removes guest conversation content from third-party model APIs. For Gulf deployments we work to the data residency requirements of the market. We also have an EULA and Data Processing Agreement in place (v1.0) and maintain subprocessor compliance documentation covering every third party in the pipeline, including speech, LLM and telephony vendors. That documentation is provided to customers during procurement. Yes, three would matter. Clarity on consent and disclosure standards for AI voice agents under the DPDP Act. We disclose that the caller is speaking to an AI agent, but a clear national standard would remove a recurring procurement objection and would stop less scrupulous operators from undercutting compliant ones. Support for Indian-language speech data and open models. Indian-accented multilingual speech is under-represented in global training data. Public datasets or compute support for Indic speech models would raise quality across the board and reduce our dependence on foreign model APIs, which is a strategic as well as a commercial issue. Procurement and incentive access. Inclusion of AI voice agents in tourism and hospitality digitisation schemes, and continued GPU and compute credit programmes for deep-tech startups, which directly offset our largest variable cost while we build self-hosted infrastructure. Yes, and we track four. Telecom and call-recording regulation. Voice AI on Indian telecom infrastructure sits in an evolving regulatory space, including DLT registration and consent for recording. Rules tightening on automated calling could affect our outbound use cases, though our core motion is inbound, which is materially lower risk. Data protection. DPDP Act implementation could impose stricter consent, localisation or retention obligations. Our self-hosting migration reduces exposure rather than increasing it. AI-specific regulation. Disclosure obligations for AI agents and any future rules on synthetic voice would require product changes. We already disclose, so we expect this to be a compliance cost rather than a business-model risk. Payments. We operate through regulated rails and do not hold funds, so changes to UPI or payment aggregator rules reach us indirectly through our providers. Cross-border. Gulf market data residency requirements may require regional infrastructure for Saudi and UAE deployments. None of these are existential. The most likely outcome is that tighter regulation favours operators who have already built compliance in, which we have. We can name the specific failure points, which is the honest version of this answer. Concurrency and cost, first. Our pricing is built on concurrent channels precisely because concurrency drives delivery cost, and at 10x volume the third-party STT, LLM and TTS API bill becomes the binding constraint at ₹2.90 per minute. This is exactly why self-hosted voice infrastructure at a target of ₹1.50 per minute is our top engineering priority rather than a nice-to-have. Integration maintenance, second. Every PMS and POS partner ships breaking changes on their own schedule. At 10x properties across more systems, manual integration maintenance stops scaling. The fix is contract-testing every connector and standardising tool connectivity through Model Context Protocol, which is in progress. Implementation and onboarding, third. Today's three to five week integrated deployment is founder and engineer assisted. At 10x that becomes the bottleneck before anything technical does. The self-serve tier and a templated onboarding playbook exist to absorb this. Observability, fourth. At current volume a human can review escalated calls. At 10x we need automated quality scoring and anomaly detection to catch a regression that only shows up in one language or one property's configuration. Support and human escalation, fifth. Escalation assumes staff availability at the property. At 10x we need tiered fallback so an escalation never simply dead-ends. Yes. Engineering is in-house and led by co-founder Atul, who built the production voice engine, the multi-agent orchestration and maker-checker layer, and every live PMS integration. The team is remote-first and Bengaluru-anchored, covering voice and speech pipeline engineering, agent orchestration, integrations, and platform and infrastructure. We use external specialists deliberately and narrowly. Pace Wisdom acts as our Gold Implementation Partner for deployment capacity, and Partek is our channel partner for the Saudi drive-thru work including hardware. Core AI and orchestration is never outsourced. A key use of the current round is taking the team to roughly 20 people, weighted toward voice infrastructure engineering for the self-hosting migration, and toward customer success so implementation stops depending on founders. Speech and language. Third-party STT and TTS including Ultravox and Deepgram, with Krisp AI and open-source noise suppression engines under evaluation for Voice Activity Detection. Third-party LLMs including OpenAI for base language understanding, migrating to self-hosted open-source and licensed models on Jio GPU infrastructure. Telephony and messaging. Plivo and custom SIP, TeleCMI, Jio Haptik, WhatsApp Business API. Protocols and standards. Model Context Protocol for standardised tool connectivity. Integrations. Official APIs for Oracle Opera, eZee, Aiosell, Petpooja, Posist and Rista. Payment rails via UPI, Razorpay and WhatsApp. Infrastructure. AWS, Hostinger, Jio GPU. All open-source components are used under their respective licences, and licence compatibility is reviewed before adoption given our commercial deployment. A closed loop from production back into the model. Every call produces a recording, transcript, summary, completion or escalation label, and the downstream PMS action. Escalated and failed conversations are triaged weekly into a labelled regression set, which becomes the fixed benchmark every release is scored against. That converts anecdotal quality into a measured trend. On cost and latency, the self-hosting migration is the main lever, taking AI delivery cost from ₹2.90 toward ₹1.50 per minute while removing a third-party latency hop. Noise suppression and Voice Activity Detection work continues in parallel, with drive-thru acoustics as the hardest case. On coverage, every new property configuration and every new PMS quirk is folded back into the shared workflow library, so deployment N plus 1 is cheaper than deployment N. This is the compounding asset in the business. On accountability, each of these has a named owner and a date, tracked alongside the ten open decisions in our GTM plan rather than left as an aspiration. Both 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/7DzNTbTwadiQ-HeyKoala_IMC_2026_Pitch_1.pptx, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/7DzNTbTwadiQ-HeyKoala_IMC_2026_Pitch_1.pptx https://youtu.be/qII_o8_jk_A Yes, in a specific and unglamorous way. Our positioning is that we are the intelligence layer that amplifies your people, not the thing that replaces them. The concrete impact is on independent Indian hospitality operators. A single boutique resort in Coorg cannot afford three shifts of multilingual front-desk staff and therefore loses bookings to OTAs charging 15 to 25 percent. That commission is a direct transfer from small regional operators to large aggregators. Every booking we complete directly is margin that stays with the property, and by extension with local hospitality employment. We are levelling a playing field that currently favours scale. Second, language access. 26 languages with real Indian-accent handling means a guest can transact in their own language with a property that could never have staffed for it. That is meaningful in a country where language is a genuine barrier to service. Third, staff experience. The agent absorbs repetitive after-hours call volume and routes work with full context, which reduces front-desk burnout in an industry with severe attrition. Our staff-facing agents coach rather than monitor. NA NA checked
Aug 25, 2026 @ 12:57 PM Yogesh Kabir & Gaurav Pant gaurav@storywiseacademy.com https://www.linkedin.com/in/gauravpanth +91 7019528965 Gaurav : Educator, creator, storyteller, animator. Built Storywise to 2.5M+ followers in 20 months; previously senior at TictacLearn (600K+ subs). The voice and pen behind the characters. Yogesh - Educator, Author, Certified Coach. He previously led a JEE/NEET coaching institute for nearly 9 years, giving him deep first-hand exposure to the gap between teaching and actual learning. We met through IIT-Delhi networking event some 2 years ago. As we were working in a same space we keep interacting on different issues and what kind of solutions can work. We started working together 8 months ago when yogesh joined us full time. All We have deep understanding of market, students challenges and gaps in the market. Gaurav's understand engaging students with stories. Yogesh is expert in effective learning methodelogies and habit building products. We are Storywise https://youtube.com/@storywiseacademy Bengaluru Storified, Gamified Active Learning for JEE/NEET Students Online lectures are boring and passive earning leading to poor learning outcomes and undue stress. We are creating bit sized story based practical application lessons; gamified practice modules; Active revision modules and AI tutor for personalization. We have launched the Learning App on Play Store and Apple Store and has 30k+ downloads, 2k DAU, 6k WAU in 40 days. Unique pedagogy at the intersection of Art and Science. Comic style lessons, which are hard to replicate. Users Users Engineering and Medical Competitive Exam Aspirants $ 430B $ 10B ₹ 1500 Cr Yearly Fee PW, Vedantu, eSaral etc 2m+ YouTube and Instagram Following Freemium Model Creating a Duolingo for Science Education for K-12 and Competitive Exams. Pvt Ltd 1 Cr Yes Mentoring and Funding Scale it to 30k DAU with sustainable growth Yes IITACB can help us reach right people who are passionate about Education. No We are a WFH organization with app people working from their base location throughout India. No Supporting feature 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/ydlVNwsxqzXQ-storywise_deck_1.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/ydlVNwsxqzXQ-storywise_deck_1.pdf NA checked
Aug 25, 2026 @ 12:40 PM Kumar Shubham founders@getlumina.in https://www.linkedin.com/in/kumarshubham12/ http://NA 6200705301 Vivek Kumar, Co-founder & CEO: Ex-founder at Elyzian, scaled the company to $60K ARR, with 6+ years of experience building scalable, production-grade SaaS platforms. BTech CSE, BMS College of Engineering. Shivang Kumar, Co-founder & CTO: Ex-founder of FrostAI and founding Security Lead at CloudDefense, contributing to its $4M Series A. Has built AI security solutions for Piramal, Columbia University and MobiKwik, and collaborated with JAIST, Japan on enterprise LLM security. Kumar Shubham, Founding Member, Operations: AI researcher and ex-founding member at Elyzian, with experience taking AI products end-to-end from IEEE-published research to revenue-generating platforms. IDD, EE, IIT (BHU) Varanasi, 2026. Piyush Raj Singh, Founding Member, Product: Lead product designer specialising in enterprise SaaS and AI platforms. Helped GENIE AI raise $400K and has delivered products for clients across the US, Canada, UAE and India. BTech CSE, KIIT. We are a close-knit founding team and have known each other since childhood. Vivek and Shivang previously founded and built Elyzian together, giving them experience working together as founders across technology, product, business, and execution. We have now been working together on Lumina for the past year. Our long-standing personal relationship, combined with our previous experience of building a company together, gives us a high level of trust, communication, and understanding of each other's strengths. All Our biggest strength is the combination of complementary expertise and proven experience in building technology businesses. We bring together SaaS and startup execution, AI research and engineering, enterprise security, operations, and product design. This allows us to build Lumina end to end, from deep technology and research to product and business execution. Our previous experience of building together also gives us strong alignment, trust, and the ability to move quickly as a team. Aroha Research Private Limited www.getlumina.in Ranchi, Jharkand Aroha Research Private Limited is building Lumina, the decision-intelligence layer for marketing. Lumina acts as a second brain calibrated to each business, allowing teams to validate ideas, messages and campaigns by simulating how their real audience will react before a rupee is spent. It brings pre-launch, personalised and decision-grade intelligence to marketing. Advertising is a hundreds-of-billions-of-dollar industry that still launches creative on gut feel. Every expensive decision, from the audience and positioning to the offer and creative, is committed before evidence exists. In 114 interviews with CMOs and agency owners managing Rs 30 lakh to Rs 4 crore annual budgets, even experienced marketers reported only about 30% confidence that an ad would work before it runs. Traditional copy testing costs Rs 10 to 50 lakh and takes four to six weeks, while live A/B testing makes businesses pay media costs to discover what does not work. Lumina simulates how a brand's real audience will react to an ad before any money is spent. A marketer submits the copy, creative, target audience, platform and objective. Lumina generates a synthetic audience grounded in the brand's own customer data, models individual reactions and social spread, surfaces the themes that resonate, scores the creative, and generates improved variants that are re-tested against a fresh audience. The system is continuously calibrated against the brand's actual campaign outcomes, moving marketing intelligence from post-launch optimisation to pre-launch decision-making. Lumina combines proprietary, domain-specialised AI models with customer-specific data and real-world campaign outcomes. Our in-house models, Lumina-mini (15B parameters) and Lumina-hilux(25B parameters), are specifically developed and trained for marketing simulation rather than relying solely on general-purpose models. They work with our customer-voice grounding layer and live campaign-performance feedback to simulate audience behaviour and continuously calibrate predictions against actual outcomes. This creates a proprietary feedback loop between data, simulation and real-world performance that strengthens with every campaign. Users Users, Revenue, Pilots, Testimonials Our primary customers are performance marketing agencies managing 10 to 50 client brands and D2C brands or in-house marketing teams spending approximately ₹30 lakh to ₹4 crore annually on paid social. Agencies are a key distribution multiplier because one relationship can bring Lumina to multiple brands. We are also expanding toward enterprise marketing and insights teams that currently spend ₹10 to ₹50 lakh on research and copy testing, as well as product teams validating naming, pricing and positioning before launch. Our initial focus is India, followed by the United States. $150B to $200B $40B to $80B $0.5B to $2B Lumina follows a recurring SaaS subscription model built around usage credits. Growth is ₹5,000 per month for a single brand, while the Agency plan is ₹10,000 per brand per month with credits pooled across the agency roster. Enterprise customers are priced per engagement and receive capabilities such as private models and API access. Additional credits can be purchased separately. Revenue grows through conversion of pilots, expansion across agency client rosters, enterprise adoption, and expansion from Meta into additional platforms and creative formats. Artificial Societies, Simile ai, Nielsen, Ipsos, Kantar, Qualtrics Our primary acquisition motion is agency-led. We identify high-fit performance and creative agencies, engage strategy, planning, insights and growth decision-makers, and demonstrate Lumina through their existing client campaigns. We also use direct founder-led outreach to D2C brands and marketing teams. A key demand-generation mechanism is the free blind back-test, where we predict the ranking of a customer's past campaigns without seeing the actual results and compare our predictions against their reporting. This creates a low-friction proof of value before conversion. We use an agency-led, product-led proof strategy. We begin with performance agencies managing multiple D2C and consumer brands, where one partnership can provide access to an entire client roster. We use campaign back-testing and pilots to demonstrate measurable value, then convert successful pilots into recurring accounts and expand across the agency's brands. In parallel, we acquire high-spend D2C and in-house marketing teams directly. We are initially focused on India and will expand into the US, while extending the platform beyond Meta into Google, YouTube and TikTok and adding video creative scoring. Our long-term vision is for Lumina to become the world model for go-to-market decisions. Today, Lumina simulates a brand's audience to validate marketing decisions before money is spent. Over time, we plan to build a calibrated model of both every brand's audience and the real-world context in which that audience operates, incorporating market shifts, cultural context, trends and external events. Lumina will become the second brain that businesses consult before major marketing and go-to-market decisions, continuously learning from real-world outcomes and helping them understand what is likely to work before they commit resources. Private Limited company, incorporated in 2026. Bootstrapped Yes We are applying to IITACB to accelerate Lumina's transition from early commercial validation to scalable growth. We see strong value in IITACB's combination of IIT alumni, technical mentors, industry connections, research ecosystem and investor access. As an AI-first company building proprietary models and decision-intelligence technology, access to this ecosystem can help us strengthen the technology, validate enterprise use cases, build strategic partnerships and prepare for the next stage of growth. During the programme, we want to strengthen Lumina's technology and product, deepen our AI and research capabilities, accelerate enterprise and agency adoption, and build strategic relationships with potential customers and partners. We also want to leverage IITACB's mentorship and investor network to refine our growth strategy and prepare the company for larger-scale expansion. Yes Bangalore provides access to one of India's strongest technology and enterprise ecosystems, with a dense concentration of startups, D2C brands, technology companies, agencies and potential enterprise customers. We can use the Bommasandra industrial ecosystem and Bangalore market to build customer relationships, run pilots, develop industry partnerships and access technical talent. IITACB can help us connect with relevant companies, IIT alumni, mentors, researchers and investors, accelerating both customer validation and technology development. Yes We would use the incubator primarily as a base for focused product and technology development, team collaboration and customer meetings. Access to meeting and conference facilities would help us engage with customers, mentors and partners, while the incubator's technical and research ecosystem would support our work on Lumina's proprietary AI models and decision-intelligence platform. The physical presence would also help us build stronger connections across the Bangalore startup and enterprise ecosystem. Yes Core engine Lumina is built as a multi-stage decision-intelligence system. A marketer provides the copy, creative, target audience, platform and objective. A privacy-preserving knowledge pipeline ingests the brand's own documents, product information and website, strips personal data and grounds extracted knowledge to source sentences. Lumina then generates a synthetic audience with demographic and psychological attributes and positions personas within a social graph to model individual reactions and message spread. Our in-house marketing-specialised models, Lumina-mini and Lumina-hilux, power audience reaction prediction and brand-grounded content generation. The system scores the original creative, generates improved variants, re-tests them against a fresh panel and applies a statistical guardrail before promoting a variant. Live Meta performance data is synced back as ground truth to continuously calibrate predictions. Our key data advantage comes from combining proprietary ad-performance data with each customer's first-party brand data. Our models have been trained on more than ₹5 crore of live Meta ad-spend data, while each customer is grounded through its own product information, website, documents and customer knowledge. Live campaign outcomes are synced back as ground truth, allowing predictions to be calibrated against what actually happened. As more campaigns are connected, the system builds a growing corpus of real advertising outcomes and improves its understanding of audience response. Our defensibility comes from the combination of proprietary models, customer-specific grounding and closed-loop calibration. Lumina-mini and Lumina-hilux are in-house models trained specifically for marketing simulation rather than general-purpose reasoning. Our customer-voice grounding pipeline builds synthetic audiences from each brand's own data, while live campaign outcomes continuously calibrate predictions. Our variant tournament then re-tests improvements against fresh persona panels and refuses to promote variants that do not outperform the original. Together, the specialised models, proprietary data, customer-specific calibration and validation methodology create a compounding advantage that is difficult to replicate by simply using a general-purpose AI model. We evaluate Lumina using a marketing-specific internal evaluation suite based on held-out real human studies and production tasks. Our models are evaluated on audience synthesis, persona integration, insight quality and society simulation, along with structured-output reliability. LuminaAI-v1-mini-1.1 achieved 96.1% overall on the Marketing Simulation Intelligence Benchmark and 100% valid, schema-correct structured output across 200 held-out production tasks. Our newer Lumina-hilux and Lumina-mini models are also evaluated against held-out real human studies using identical prompts and scoring criteria. We additionally measure prediction performance against actual campaign outcomes, making real-world calibration an ongoing evaluation signal. Lumina is designed around privacy-preserving data handling. Our ingestion pipeline uses a dual-pass sanitisation process to remove personal information before knowledge is used for simulation, and extracted facts are traced back to their source sentences. Personas used for simulation are synthetic rather than real individuals. Our Meta integration is strictly read-only, with no write endpoints, custom audiences or retargeting, and data is deleted when an account disconnects. We operate under India's DPDP Act and IT framework and are building toward GDPR and CCPA requirements as we expand into international markets. Customer data and proprietary model assets are maintained in access-controlled infrastructure. India's growing support for AI research, deep-tech innovation, startup incubation and domestic technology development is favourable to Lumina. Government initiatives around AI, startup recognition, research and high-skill technology development can support our efforts to build proprietary AI capabilities and retain technology and IP in India. We also see value in India's evolving digital and data-protection framework as it creates clearer expectations for responsible handling of business and customer data. ### Are there any regulatory risks that could impact your product? > Lumina's primary regulatory considerations relate to data privacy, AI governance, advertising regulations and third-party platform policies as we expand globally. Our Meta integration has undergone Meta's app review process and uses approved API access, with no write operations on clients' data. We currently operate within the applicable Indian data protection and IT framework. As we expand internationally, GDPR, CCPA and other regional privacy requirements will become relevant. We are building toward these requirements and will formalise and strengthen our compliance processes as the company scales. We also continuously monitor changes in AI regulation, advertising standards and platform policies that could affect the product. At 10x scale, the main challenges would be inference capacity, simulation throughput, data ingestion and storage, and maintaining prediction quality across a much larger number of brands and campaigns. The architecture is designed to scale horizontally, but substantially higher simulation volume would require additional compute capacity and optimisation of model serving, caching and orchestration. The other key challenge is maintaining per-brand calibration quality as the number of connected advertisers grows. Our in-house specialised models are important here because they give us greater control over inference economics and system performance than relying entirely on external frontier-model APIs. Yes. Lumina has an in-house technical team covering AI research, model development, data systems, security and product engineering. Shivang Kumar leads technology and brings experience in AI security, enterprise LLM security and startup engineering. Kumar Shubham brings AI research experience, including IEEE-published work and data-driven intelligence systems. The team has built and fine-tuned Lumina's own marketing-specialised model family, including Lumina-mini and Lumina-hilux, alongside the synthetic-audience, social-simulation, grounding and validation systems. Our core proprietary assets include our live Meta advertising-performance dataset, customer-specific knowledge and grounding pipeline, synthetic-audience and social-simulation systems, model weights, and variant-tournament methodology. Lumina's in-house models are trained on proprietary ad-simulation data. We also use standard third-party infrastructure and open-source components where appropriate for model serving, orchestration and application infrastructure, subject to their respective licences. Our proprietary model weights, software, customer-voice grounding pipeline and validation methodologies are maintained in access-controlled private repositories. No patents have been filed currently; our primary IP is maintained as trade secrets and software IP, with selective patent filing planned for parts of the methodology. We improve Lumina through a closed-loop system connecting simulation with real campaign outcomes. Every connected campaign provides additional ground-truth data that can be used to calibrate predictions. We will continuously expand and retrain our specialised model family, improve synthetic-persona and social-dynamics modelling, strengthen the grounding pipeline and expand our evaluation suite using held-out human studies and production outcomes. We also plan to expand the measurement layer beyond Meta to Google, TikTok and other platforms, giving the models broader and more platform-independent ground truth. Both 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/jBxK8nRg9sWh-Lumina-Pitch-Deck_compressed.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/jBxK8nRg9sWh-Lumina-Pitch-Deck_compressed.pdf https://www.youtube.com/watch?v=k8TFZL3coxE Yes. Lumina aims to make high-quality market and customer intelligence more accessible to businesses by reducing the cost, time and resources required to validate important decisions. By enabling companies to test ideas and campaigns before committing real budgets, Lumina can help businesses make more informed decisions while reducing wasted marketing spend and experimentation. NA Avi Dutt Aroha Research Private Limited is building Lumina as a global AI-first product from India. We have built our own marketing-specialised AI models, Lumina-mini and Lumina-hilux, and are already validating the product with paying customers and agency partners. We are particularly interested in leveraging IITACB's technical, research and industry ecosystem to deepen our AI capabilities and accelerate enterprise adoption. checked
Aug 25, 2026 @ 10:34 AM Rajdeep Dewangan rajdeep@dfmeatechnosol.com https://www.linkedin.com/in/rajdeep-dewangan-67454b2a/ https://dfmeatechnosol.com/ +919902070932 With 17+ years of experience in engineering leadership across power generation, automotive, and turbomachinery, I bring deep expertise in systems engineering, product development, simulation-driven design, and team leadership. I am passionate about driving innovation-led decision-making in every project I take on. Beyond industry, I actively mentor student and faculty-led startups, nurturing the next generation of innovators and entrepreneurs. Currently, I am also building my own startup, leveraging AI, innovation-first processes, and a growth mindset to create impactful solutions. My other co-founder is my wife but she is part time 1 Its 6 member team DFMEA TECHNOSOL PRIVATE LIMITED https://dfmeatechnosol.com/ BANGALORE We are on Engineering Service along with one Medical tech Product development Millions of patients worldwide depend on life-saving, temperature-sensitive medicines such as insulin, biologics, vaccines, and specialty drugs that must be maintained within a strict 2–8°C range to preserve efficacy. Even minor temperature deviations can render these medicines ineffective or unsafe. While refrigeration is accessible at home and in clinical settings, maintaining precise temperature control during travel remains a major challenge. Patients, caregivers, and healthcare providers currently rely on passive cooling methods such as gel packs, insulated pouches, and evaporative cooling systems. These solutions: Do not actively regulate temperature Cannot adapt to fluctuating ambient conditions Provide limited cooling duration Offer no real-time temperature visibility Lack alerts for temperature excursions As a result, medicines are frequently exposed to temperature instability, leading to spoilage, reduced therapeutic effectiveness, financial loss, and serious health risks. There is a critical unmet need for a smart, portable, energy-efficient active cooling solution that ensures reliable medical-grade temperature stability, real-time monitoring, and intelligent alerts during mobility. Medi Smart Cool is a portable, USB-powered, Medical-grade cooling device that:  Maintains precise 2–8°C range  Provides real-time temperature tracking  Offers intelligent alerts for excursions BLE-enabled active cooling with precise 2–8°C medical-grade control Real-time temperature tracking via mobile dashboard Intelligent cooling & adaptive fan optimization for energy efficiency Portable, USB-powered, rechargeable battery backup (up to 72 hrs) Temperature alerts & data logging for safety assurance Reliable alternative to passive gel-pack systems MVP Pilots MediSmart Cool can leverage the Bommasandra industrial hub and Bengaluru’s strong healthcare, electronics, engineering and manufacturing ecosystem to accelerate product validation, manufacturing readiness and market adoption. Bommasandra provides proximity to a large base of engineering, electronics, manufacturing and healthcare-related companies, which can help us identify manufacturing partners, component suppliers, testing facilities and potential B2B customers. Bengaluru also provides access to hospitals, clinics, pharmacies, diabetes-care networks and technology companies, enabling us to conduct structured user validation and pilot deployments for MediSmart Cool. IITACB can play a critical role in our next stage of growth by providing access to experienced IIT alumni, technical mentors, healthcare experts, industry partners and investors. We particularly seek support in medical-device product validation, regulatory strategy, thermal/electronics engineering, design-for-manufacturing, clinical/user validation and go-to-market strategy. We would also like to use the IITACB ecosystem to build partnerships with hospitals, diabetes-care organizations and pharmaceutical/healthcare companies, while leveraging Bengaluru’s deep-tech and manufacturing ecosystem to reduce product development and commercialization time. IITACB's existing portfolio already includes healthcare, MedTech and deep-tech startups, making the ecosystem relevant to our journey. Our objective is to use IITACB and the Bengaluru ecosystem as a launchpad to take MediSmart Cool from validated prototype to a regulatory-ready, commercially scalable medical device for India and subsequently global markets. Yes We wish to leverage IITACB’s infrastructure as a product development and commercialization base for MediSmart Cool. The incubation facility will provide us with a professional workspace for our engineering and product team, while enabling us to work closely with mentors, researchers, industry experts and other startups within the IIT ecosystem. We plan to utilize the infrastructure and facilities for: Product development and engineering: Design optimization of the thermal, mechanical, electronics and IoT systems of MediSmart Cool. Prototype development and testing: Assembly, functional testing, thermal performance validation and reliability testing of prototypes. Medical-device validation: Support for temperature validation (2–8°C), safety testing, risk management and preparation for regulatory compliance. Industry collaboration: Meetings and technical discussions with hospitals, healthcare organizations, electronics manufacturers and potential customers. Pilot production readiness: Design-for-manufacturing, vendor development, component sourcing and preparation for small-batch production. Mentorship and technical expertise: Access to IITACB/IIT ecosystem experts in medical devices, electronics, thermal engineering, business strategy and regulatory pathways. Investor and market connect: Utilize the incubator ecosystem for investor interactions, industry partnerships and customer discovery. Our objective is to make the IITACB facility a central engineering, validation and commercialization hub for MediSmart Cool, helping us transition from our current validated prototype stage toward a regulatory-ready, pilot-manufactured and commercially scalable medical device. Yes Core engine 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/hjesKYTzVUjU-DFMEA-Technosol.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/hjesKYTzVUjU-DFMEA-Technosol.pdf NA checked
Aug 24, 2026 @ 11:14 PM AAGASH O K aagashok1209@gmail.com https://www.linkedin.com/in/aagash-ok-1209ak2006/ http://NA +91 6381587978 **Founder / Team Lead** – Responsible for overall startup strategy, product development, team coordination, and execution. Strong interest in technology, innovation, and building practical solutions to real-world problems. **Technical Team Member** – Responsible for software development, AI/technology integration, system architecture, and implementation of the proposed solution. **Research & Product Team Member** – Responsible for research, problem analysis, product ideation, validation, documentation, and improving the solution based on user and market requirements. As a team, we combine technical knowledge, research capabilities, and entrepreneurial thinking to develop and validate our solution and work toward building it into a scalable startup. We met through our academic journey and have been working together on technical projects, innovation initiatives, and startup ideas. Over time, we have developed a strong understanding of each other's strengths and working styles. Our collaboration has helped us effectively divide responsibilities, solve problems, and work together toward building and validating our startup idea. 1 Our biggest strength is our ability to combine different technical skills, creative problem-solving, and teamwork. We communicate effectively, divide responsibilities based on our strengths, and stay focused on solving real-world problems. We are adaptable, committed to learning, and capable of turning ideas into practical and scalable solutions. VFAM Solutions Ptd Ltd https://vfamsolutions.com/ Tiruchengode, Tamil Nadu, India Roteen is an education platform designed to make learning simpler, faster, and more effective for students by combining structured notes, video explanations, quizzes, recall questions, previous-year questions, and native-language learning in one platform. Students spend a significant amount of time understanding individual questions, searching for learning resources, and repeatedly memorizing content. This makes learning time-consuming and can reduce effective understanding and recall. Roteen addresses the need for a faster and more effective learning approach that helps students understand concepts, retain knowledge, and spend less time on each learning task. Roteen is designed to reduce the time students need to understand and learn concepts without compromising understanding. It brings structured notes, friendly video explanations, quizzes, recall questions, previous-year questions, and native-language learning content into one platform. By combining understanding, practice, and recall in a single learning ecosystem, Roteen helps students learn more efficiently, improve memory retention, and spend less time searching and memorizing. Roteen focuses on reducing learning time while improving understanding and memory retention. Instead of simply providing answers or study materials, it combines simplified learning content, practice, recall, and revision in one ecosystem. Its time-efficient learning approach, recall-based methodology, and native-language support create a more personalized and student-friendly learning experience. MVP Signups School students, particularly students preparing for school examinations who want to understand concepts faster, reduce learning time, improve memory retention, and learn more effectively. NA — unless you have a reliable market-size calculation. NA NA Freemium model with free basic learning content and premium features for advanced learning, practice, recall, and personalized learning support. Physics Wallah (PW), Khan Academy, Vedantu, and other school-focused digital learning platforms. We plan to acquire school students through social media, student referrals, school outreach, educational communities, demonstrations, and partnerships with schools and educational institutions. We will initially target school students through digital platforms, school communities, social media, and partnerships with schools. We plan to offer accessible learning content to encourage adoption, collect student feedback, continuously improve Roteen, and gradually expand across schools and regions. Our long-term vision is to make Roteen a trusted learning ecosystem for school students that helps them reduce learning time, understand concepts better, improve memory retention, and gain knowledge rather than simply memorize answers. We aim to make school education simpler, faster, more effective, and accessible through technology and native-language learning. Private Limited Company – VFAM Solutions Private Limited NA We are applying to IITACB Incubator to receive expert mentorship, validate and strengthen Roteen's business model, improve our product and technology, and gain access to experienced mentors, investors, industry networks, and the IIT ecosystem. We also want to expand Roteen from an early-stage product into a scalable education technology startup focused on improving learning efficiency for school students. During the programme, we aim to validate Roteen with more school students, improve the product based on real user feedback, strengthen our technology and business model, develop a scalable go-to-market strategy, and build partnerships with schools and educational organizations. We also seek mentorship and investor connections to support the growth and expansion of Roteen. Yes We can leverage the Bengaluru ecosystem to connect with education technology companies, technology partners, investors, mentors, and educational institutions. IITACB can help us with expert mentorship, product validation, industry connections, investor access, and opportunities to build partnerships. This ecosystem can help Roteen strengthen its technology, validate its business model, and scale our solution to more school students and schools. Yes We would use the IITACB infrastructure and facilities as a professional environment for product development, team collaboration, testing, demonstrations, mentor interactions, and startup activities. Access to the incubator ecosystem would also help us connect with mentors, investors, industry partners, and other startups while working toward scaling Roteen. Yes Not applicable Roteen is designed as a modular digital learning platform consisting of a student-facing application, backend services, database, content management, learning resources, quizzes, recall-based learning modules, and analytics. The architecture is designed to support structured educational content, video delivery, assessments, user management, and future personalization features. The technology stack will be continuously improved to support scalability, security, and reliable performance. At the current stage, Roteen does not claim a proprietary data advantage. As the platform grows, anonymized learning interactions, quiz performance, recall patterns, and student feedback can help us understand learning behavior and improve the effectiveness of our learning approach. Roteen's defensibility comes from its integrated learning approach focused on reducing learning time while improving understanding and recall. Instead of providing only videos, notes, or questions, Roteen combines structured learning, practice, recall, revision, and native-language content into one ecosystem. Over time, our learning methodology, educational content, user feedback, and accumulated learning insights can strengthen the product's differentiation. We evaluate the platform using metrics such as application response time, uptime, page and content loading time, quiz response time, error rates, user completion rates, learning-session engagement, and system stability under increasing user loads. As the product develops, we will also track learning-focused metrics such as time required to understand content, quiz performance, recall accuracy, and retention. Roteen is designed to minimize unnecessary collection of student information and protect user data through appropriate access controls, secure data storage, authentication, and controlled access to sensitive information. As Roteen scales, we will strengthen our privacy and security practices in accordance with applicable Indian data-protection and child-safety requirements, particularly because our primary users are school students. NA The key regulatory considerations are student data privacy, child data protection, consent and parental considerations, cybersecurity, and intellectual-property rights related to educational content. We plan to address these requirements as the platform scales and establishes partnerships with schools and educational institutions. At 10x scale, the main challenges would be increased server and database load, video and educational-content delivery, concurrent user traffic, storage requirements, and maintaining fast response times. We would address these through scalable cloud infrastructure, database optimization, caching, content delivery networks, monitoring, load testing, and modular system architecture. No. Roteen currently focuses on education technology and learning methodology rather than deep-tech research. Our technical team handles product development, platform engineering, and implementation. Roteen does not currently rely on proprietary datasets or proprietary AI models. The platform uses standard software development components and libraries as required for application development. Any third-party or open-source components used will be reviewed for applicable licenses and compliance before deployment. We plan to continuously improve Roteen through user feedback, performance monitoring, load testing, bug tracking, security improvements, database and API optimization, and regular product iterations. We will also use learning-related metrics such as time efficiency, quiz performance, recall accuracy, and student engagement to improve the platform's effectiveness. Tamil Nadu, India — currently focused on the Tamil Nadu school education market, with plans to expand to other Indian states in the future. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/wQBUC0ulIERp-Roteen_IITACB_Pitch_Deck.pptx, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/wQBUC0ulIERp-Roteen_IITACB_Pitch_Deck.pptx http://NA Yes. Roteen is an impact-focused education startup aimed at improving the way school students learn. Our mission is to reduce the time students spend understanding and searching for learning resources while improving concept clarity, recall, and knowledge retention. We want to move students from memorization-based learning toward understanding-based learning by providing simple, structured, and accessible learning resources in one platform. Our focus is initially on school students in Tamil Nadu, with the goal of making effective learning more accessible and student-friendly. NA NA Roteen is currently focused on school students in Tamil Nadu. Our key objective is to make learning more time-efficient without compromising understanding. We are developing Roteen as an integrated learning ecosystem that combines structured content, video explanations, quizzes, recall-based learning, previous-year questions, and native-language support. We are looking for mentorship, product validation, educational partnerships, and opportunities to scale the platform and create meaningful impact in school education. checked
Aug 24, 2026 @ 10:49 AM Sanglap Saha sanglap@xfrate.com http://%20https://www.linkedin.com/in/sanglapsaha/ https://xfrate.com 0422218389 CEO - Sanglap, AI head- Subrat Subrat and I go back to IIT Kharagpur — we were batchmates, and wingmates in our first year, sharing the same hostel wing. I actually wanted to bring him into Xfrate much earlier, but at the time he was CTO at AGNEXT. I told him what we were building anyway, and we kept talking about it — multiple conversations over time. I'd spent 20 years in supply chain consulting and running my own transport company, so I knew exactly how broken freight coordination was. I just needed the right technical partner. 2 Our biggest strength is that we're not guessing at the problem — we're solving it from both ends. I spent 20+ years in supply chain consulting and ran my own transport company, so I know exactly where freight breaks operationally. Subrat brings deep AI expertise from NVIDIA and CTO experience scaling AI at AGNEXT, another traditionally offline, real-world industry. That combination means we build AI that actually works on messy, real operational data — not AI that looks good in a demo but falls apart in the field. It's also a long-standing partnership: we were batchmates and wingmates at IIT Kharagpur, so there's real trust and shared history underpinning how we work together. The other BIg strenth is resilience - I had to PiVOT the business and keep it afloat though tough times. Xfrate https://xfrate.com Sydney and Kolkata AI-native freight software that helps businesses cut freight spend, manpower and operational costs Freight is manually run on calls, excel, WhatsApp and legacy tech leading to overspeand and no intelligence Xfrate is AI-native freight software that replaces manual, WhatsApp-and-Excel-driven logistics coordination with structured, intelligent workflows. Businesses can plan, create and manage freight orders, run competitive allocation among transporters, track shipments in real time, and automatically reconcile purchase orders against invoices — all from a single system, without needing a dedicated logistics team. Underneath, Xfrate uses AI for order extraction from unstructured documents, automated load and dispatch planning, and PO-to-invoice reconciliation — turning work that used to take hours of manual coordination into an automated process. Xfrate also integrates directly with the systems businesses already run — ERP and accounting platforms, WhatsApp for transporter communication, and third-party systems via API — so it fits into existing operations rather than forcing a rip-and-replace. We're listed as a transactable solution on Microsoft Azure Marketplace under the "AI in Logistics" category, and deploy on dedicated cloud infrastructure per market for data sovereignty Our defensibility isn't the AI itself — it's who built it. Most freight software comes from technologists who've never run freight operations, or operators without real AI depth. We have both: 20+ years running supply chain and a transport company, paired with AI expertise from NVIDIA and AGNEXT. That combination means our AI solves real operational problems — messy document extraction, load planning, invoice reconciliation — not just clean demos. The proof is in outcomes: 8–10% freight cost reduction . We're also structurally hard to replicate fast: dedicated cloud infrastructure per market for data sovereignty, deep integration with the ERP, accounting and communication tools businesses already use, and third-party validation as a transactable Microsoft Azure Marketplace solution under AI in Logistics. Freight is manual, fragmented, and unglamorous — exactly the kind of problem well-funded generalist platforms tend to skip or solve shallowly. Founder-market fit most competitors don't have is our real moat. Revenue Revenue Mid-sized manufacturers and distributors that send goods regularly but aren't logistics companies — still running freight on Excel, calls and WhatsApp. "AI in Logistics market: ~$21.7B (2025), projected to reach $435B+ by 2033 at ~42% CAGR OOTB license+ implementation fee, plus usage-based add-ons and annual support Broader logistics platforms like Enmovil, Locus, BlackBuck and Rose Rocket — mostly funded, generalist players vs. our focused approach Organic — word-of-mouth, SEO, and direct outreach; no paid CAC. Now building partner-led sales support across India, Australia and ME. Organic to date (zero CAC), targeting mid-market shippers directly. Now shifting to partner-led sales "In the near term, we're expanding beyond road freight into air and sea, so Xfrate becomes the single AI-native layer businesses use to manage freight across every mode, not just trucking. Longer term, our vision is for Xfrate to be the default intelligence layer for how goods move globally — the system that plans, predicts, and optimizes freight the way an experienced logistics operator would, but at software speed and accessible to any business, not just large enterprises with dedicated logistics teams. Beyond software orchestration, we see a further horizon where AI extends into the physical layer of logistics itself — smarter, more autonomous coordination between the digital and physical movement of goods. We're not there yet, but it's the direction the industry is heading, and we want to be building toward it rather than reacting to it Incorporated 200000K Yes We're applying to IITACB because it's a direct extension of who we already are — both founders are IIT Kharagpur alumni, and our India base already operates from the IIT Kharagpur Research Park. IITACB's alumni-led mentorship, its network of angel investors and PE firms, and its focus on deep-tech and AI ventures make it a natural next step to formalize and deepen that IIT connection at a national level. We're not looking for generic startup support — we're looking to plug into a network of IIT alumni who understand deep technical ventures and can open doors we can't open alone, particularly as we scale our India go-to-market. Convert our pipeline (Encon, Hyundai, pharma) into signed revenue, build real sales capacity, and access IITACB's investor and alumni network. Yes Bommasandra and the broader Bangalore industrial corridor are, quite literally, our target customer base — pharma manufacturers (Biocon, Micro Labs, and dozens of others), automotive component makers, and precision engineering firms that ship constantly but have no dedicated logistics function, exactly the profile we've already validated with customers like Encon and our current pharma prospect. Being physically embedded in this hub through IITACB gives us direct, warm access to decision-makers at these companies — not cold outreach, but introductions through the IIT alumni network many of these companies' leadership likely sit within. IITACB can help us in two concrete ways: first, as a source of pilot customers and enterprise references drawn straight from this hub, accelerating the mid-market traction we're already building; second, through alumni mentorship from people who've built and scaled B2B ventures serving exactly this kind of industrial base. Rather than treating Bangalore as one market among several, we see it as a proving ground we can go deep in — dense enough to build repeatable enterprise sales motion before expanding it elsewhere. No We wouldn't take up incubator seats — our team is distributed across India, Australia, with our India delivery base already anchored at the IIT Kharagpur Research Park. What we're seeking is the mentorship and investor-connect specifically, not physical office space." Yes Core engine Cloud-native: Angular + .NET Aspire backend, Azure SQL + Cosmos DB, Event Hubs tracking ingestion. AI: LLM-based document extraction and OCR, plus clustering algorithms for load/route planning. Rest confidential Our proprietary advantage isn't a massive historical dataset — we're early-stage — it's the operational data generated through live customer usage that isn't publicly available anywhere: actual bidding outcomes, lane-level rate patterns, transporter reliability and performance history, and reconciliation patterns across real freight orders. This data compounds as we onboard more customers, since each new account adds lane, rate, and transporter behavior data that improves matching, planning, and prediction across the platform — a flywheel that generic AI platforms without real freight customers simply don't have access to. We see this as an advantage that strengthens meaningfully with scale, not one we're claiming is already dominant Founder-market fit rivals lack: 20+ yrs freight ops + deep AI expertise Proof: 8-10% cost cuts, 90% retention. Focus beats funded generalists in this unglamorous, fragmented space Dedicated cloud infra per market for data sovereignty, Key Vault-managed secrets, Azure AD/SSO with RBAC, rate-limited endpoints Low overall regulatory risk — freight software isn't heavily regulated. Main exposure is cross-border data residency (DPDP, Australia Privacy Act), mitigated via dedicated regional infrastructure." Load-planner's 5-job concurrency cap would need re-architecting. Real constraint is ops bandwidth on our lean team, not product design Yes. Sanglap: supply chain domain (20+ yrs). Subrat: AI/ML, ex-NVIDIA, ex-CTO AGNEXT. Sudipta: product, ex-IBM/Capgemini. Satyajit (IIT kgp): full-stack engineering. Domain, AI and build depth in-house Open-source frameworks (Angular, .NET, LangGraph, scikit-learn) + licensed cloud/AI APIs. Core app logic is owned, proprietary code. No patents filed — moat is product, data and team Usage itself improves our AI — every bid, shipment and reconciliation refines matching and prediction. Known scaling constraints are already identified and queued for re-architecture as we grow. Both. We found AI adoption in India is still low while selling here, so we built Xfrate global-first — dedicated infra across India, Australia and the Gulf, with ME traction now emerging 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/JI47sgAbpDcu-Xfrate_Investor_Deck_v4.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/JI47sgAbpDcu-Xfrate_Investor_Deck_v4.pdf https://www.youtube.com/watch?v=mNjsX9CiCYc&t=25s NA NA checked
Aug 24, 2026 @ 12:44 AM AKSHAY SHRIDHAR HEGDE akshay@finndot.com https://www.linkedin.com/in/akshayshridhar http://www.finndot.com +919483280080 AKSHAY CEO, ARUN CTO We know each other from 12+ years we met after our highschool All Akshay brings the experience of Business and Operations Arun Brings experience of Tech and Subject Expertise This complementary skills helping us to grow FINNDOT PRIVATE LIMITED www.finndot.com Bangalore Empowering the Next Billion with smarter finance Alternative Credit solutions for underserved segment AI-powered financial health platform based in Bengaluru, India, that helps gig workers and new-to-credit users build alternative credit profiles and manage their money. It analyzes SMS and financial data to track cash flow and offer personalized guidance Data Network Effects Revenue Revenue Underserved people who are not served by legacy financial institutions 3 Billion USD 600M USD 120M USD referral commissions and B2B Licensing Good Score, ET Money, Perfios Social media marketing Freelancers to deploy our products Empowering the Next Billion with smarter finance PRIVATE LIMITED NA Yes Mentorship, Networking Scale the Finndot Yes Building helpful product which will be used by MSME's and underserved segments Yes Utilising the best minds and excellent network of IITACB Yes Core engine 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/o1xqEh1ra5gK-Finndot_20260824_004332_0000.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/o1xqEh1ra5gK-Finndot_20260824_004332_0000.pdf NA checked
Aug 23, 2026 @ 1:53 AM Akshita akshita@iitbhilai.ac.in https://www.linkedin.com/in/akshita-766a1722b +91 6200344756 Pratik Raj and Akshita are the co-founders of ContextShield AI, combining strong expertise in Artificial Intelligence, Machine Learning, Cybersecurity and software engineering. Pratik Raj leads cybersecurity architecture, threat modelling, privacy-by-design, product strategy and partnerships, while Akshita leads AI/ML model development, scam-pattern detection, data pipelines, model evaluation and end-to-end engineering. Both founders are Chanakya Fellows in the AI/ML domain and secured National Rank 1 in the PSB Hackathon, demonstrating their ability to solve complex problems under pressure. Pratik was also awarded Overall Best Intern at TCS in the Cybersecurity domain. Together, the team combines technical depth, practical experience and a shared mission to build privacy-first solutions that protect people and organisations from emerging digital, financial and AI-driven threats. Pratik Raj and Akshita connected through their shared interest in Artificial Intelligence, Machine Learning, Cybersecurity and engineering. Their collaboration strengthened through the Chanakya Fellowship in AI/ML, the PSB Hackathon where they secured National Rank 1 and subsequent technical projects. They have worked together for approximately 2 years , developing a strong working relationship built on complementary skills, shared learning and a common mission to solve meaningful real-world problems. 2 Our biggest strength is the combination of complementary technical skills, a shared vision and the determination to solve real-world problems. Pratik Raj and Akshita bring experience across Cybersecurity, Artificial Intelligence, Machine Learning and software engineering, enabling us to build solutions at the intersection of these critical domains. Both founders are Chanakya Fellows in AI/ML and secured National Rank 1 in the PSB Hackathon, demonstrating strong technical capability, innovation and execution under pressure. Pratik was also awarded Overall Best Intern at TCS in the Cybersecurity domain. Through hackathons, internships, projects and practical problem-solving, we have learned to experiment quickly, adapt to challenges and convert ideas into practical solutions. Most importantly, we share a common purpose: using technology to protect people and organisations from emerging digital, financial and AI-driven threats. Admas Bhilai ContextShield AI is a privacy-first cybersecurity platform that prevents manipulation-based payment scams and unsafe financial actions by people and AI agents before money or sensitive data moves. Existing security systems often fail when a genuine user is manipulated into authorising a fraudulent payment or when an authorised AI agent is tricked into performing an unsafe action. Digital-arrest scams, fake investments, deepfake impersonation, malicious QR codes and AI-driven fraud require protection before financial loss occurs. ContextShield AI analyses voluntarily shared messages, screenshots, links, QR codes and payment requests to identify coercion, impersonation, urgency and scam patterns before payment. It provides an explainable risk alert and recommends stopping, verifying independently or contacting a trusted person. For businesses, it checks high-risk AI-agent actions, enforces permissions and limits, and requires human approval when needed. Existing security systems often fail when a genuine user is manipulated into authorising a fraudulent payment or when an authorised AI agent is tricked into performing an unsafe action. Digital-arrest scams, fake investments, deepfake impersonation, malicious QR codes and AI-driven fraud require protection before financial loss occurs. Idea Testimonials Initial users are Indian smartphone-payment users, especially families and senior citizens. Paying customers will be banks, fintech and UPI platforms, telecom providers, cyber-insurers, and enterprises using AI agents for sensitive financial or data-related actions. 500M+ Indian digital-payment users and 1,000+ potential institutional buyers across BFSI, fintech, telecom, insurance and AI-enabled enterprises. Initial focus: 50M urban smartphone-payment users and 100+ banks, fintechs, insurers and AI-enabled enterprises in India. Three-year target: 100,000 protected users and 10–20 institutional pilots or paying customers in India. Freemium consumer protection with an optional family-safety subscription; annual B2B licensing and usage-based SDK/API pricing for banks, fintechs and enterprises; partnership revenue through telecom and cyber-insurance providers. Indirect competitors include Truecaller, bank and UPI fraud-control systems, mobile-security products, and enterprise AI-security platforms. ContextShield differentiates through manipulation-context detection before payment and security controls for high-risk AI-agent actions. We will acquire early users through universities, senior-citizen communities, digital-safety campaigns, referrals and cybercrime-awareness partners. Institutional customers will be acquired through direct pilots with banks, fintechs, telecoms, insurers and enterprise AI teams. We will first launch a privacy-first share-to-scan MVP for suspicious text, screenshots, links and QR codes. We will validate it through user interviews and early feedback from students, families and senior citizens, then offer a fraud-prevention SDK to fintech and payment platforms. Enterprise AI-agent security will follow as phase two. To become the trusted safety layer for high-risk digital decisions. ContextShield will protect people from manipulation-based scams and organisations from unsafe AI-agent actions before money or sensitive data moves, through a multilingual and privacy-preserving platform integrated with financial institutions, telecom networks and enterprise AI systems. Pre-incorporation. We are a founding team validating the problem and designing the initial product. We plan to incorporate an Indian Private Limited Company after early validation and mentor guidance. ₹0 external funding raised. The founding team is currently bootstrapped. Yes We seek IITACB’s mentorship, investor-readiness support and Bengaluru ecosystem access to validate our problem, refine our business model, strengthen our cybersecurity and privacy approach, and connect with fintech, enterprise and investor partners. We aim to validate the problem with target users, refine our MVP and go-to-market plan, develop a clear privacy and compliance roadmap, build a strong investor pitch, and secure introductions for pilot conversations with fintech, enterprise or cybersecurity partners. Yes. Our team can participate consistently in all virtual mentoring, investor sessions and programme activities. Bengaluru offers access to fintech, cybersecurity, SaaS and AI talent, while the Bommasandra industry hub offers potential enterprise users for our AI-agent security use case. We can use this ecosystem for pilot discovery, customer interviews and partnerships. IITACB can help through introductions to industry, fintech and enterprise decision-makers, mentors, legal and compliance experts, and relevant investors. No At the initial stage, we will participate remotely and leverage IITACB’s virtual mentoring, workshops, investor network and ecosystem access. As we grow and begin pilots, we may consider physical workspace for focused development, customer meetings and collaboration. Yes Core engine Proposed MVP architecture: a mobile/web client collects only user-selected content; on-device OCR, QR parsing and basic PII masking minimise exposure. A secure API backend performs multilingual text analysis, link/QR reputation checks, scam-pattern classification and explainable risk scoring. Encrypted storage retains only minimum required metadata, and raw content is deleted after analysis unless the user explicitly opts in. The enterprise phase adds an API/MCP policy gateway to validate AI-agent tool calls, enforce permissions and transaction limits, redact sensitive fields and require human approval for high-risk actions. At the idea stage, we do not claim a proprietary dataset. Our future advantage will come from a consented and de-identified multilingual dataset connecting scam narratives, risk signals, user feedback and confirmed outcomes, along with enterprise AI-agent action patterns and security policies. Our defensibility comes from combining human-scam context analysis and AI-agent action control in one Context–Intent–Action engine. Over time, consented de-identified data, explainable risk models, organisation-specific policies, trusted fintech integrations and feedback loops will make the system more accurate and difficult to replicate. Before pilot deployment, we will evaluate precision, recall, F1-score, false-positive rate, false-negative rate, PR-AUC, detection latency, user override rate and uptime. We will compare our system against rule-only keyword/link scanners and standard scam-reporting tools. We are designing privacy by default. Users will voluntarily select what they want scanned; the product will not read messages, monitor calls or access financial credentials in the background. We will minimise collection, process locally where possible, encrypt necessary processing, separate consent for analysis and model improvement, delete raw content by default, provide deletion and consent-withdrawal controls, and apply role-based access, audit logs and incident response. We do not depend on a specific policy intervention. India’s Digital India and cyber-awareness ecosystem supports adoption of safer digital practices. Any direct bank or UPI integration will be pursued only with appropriate partner approvals and alignment with applicable RBI, NPCI and data-protection requirements. Yes. Key risks include personal-data obligations, processing third-party information appearing in user-submitted content, consent management, children’s data and sector-specific requirements if we integrate with payment systems. We will begin as an independent warning and verification tool, avoid collecting OTPs, PINs and bank credentials, and obtain legal and compliance review before regulated payment integrations. The main risks are model-inference latency and cost, traffic spikes, false positives, quality variation across Indian languages, secure data deletion and support operations. We will mitigate these through on-device preprocessing, autoscaling infrastructure, model monitoring, multilingual testing, privacy-preserving retention controls and phased rollout. Yes. Our founding team combines complementary skills in cybersecurity, AI/ML and software development. We can build secure application workflows, develop and evaluate machine-learning models, analyse threats, design privacy-aware data pipelines and rapidly prototype full-stack solutions. At the idea stage, no proprietary dataset, production model or filed IP is claimed yet. For the MVP, we will use appropriately licensed public benchmark data, open-source security/OCR/NLP components and commercial APIs where terms permit. We will maintain a licence register, preserve required attribution and seek legal review before production use. We will use versioned models, offline evaluation datasets, privacy-preserving opt-in feedback, human review of disputed cases, error analysis, multilingual testing, monitoring for model drift and staged deployments. Every update will be evaluated against accuracy, false-positive impact, latency, security and privacy requirements before release. India first, with global potential. We will initially focus on Indian scam patterns, multilingual communication, UPI-related social engineering and local privacy requirements. Our architecture can later adapt to other markets, languages, payment systems and enterprise AI-agent workflows. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/GkntoCpE24RN-2026_compressed.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/GkntoCpE24RN-2026_compressed.pdf Yes. ContextShield AI is mission-driven because it aims to protect people from emerging digital and financial threats before they lose money or sensitive data. Our initial focus includes families, senior citizens and digitally vulnerable users who are frequently targeted by manipulation-based scams. We are building privacy-first protection that empowers users to make safer decisions without turning security into surveillance. NA Ravi Teja Villa Our team brings complementary cybersecurity, AI/ML and software-development skills, along with practical learning from hackathons, internships and project work. We are committed to building a privacy-first and socially meaningful solution, and we seek IITACB’s mentorship to turn early problem validation into a scalable, investor-ready startup. checked
Aug 23, 2026 @ 1:37 AM Akshita akshita@iitbhilai.ac.in https://www.linkedin.com/in/akshita-766a1722b +91 7042349740 Pratik(Me) is from BTech 4th year a EE Student and have hands on Experience in AI/ML,EXPERT in Security Engineering and a Recipient of National Chanakya fellowship in AI-IoT domain and secured the best overall intern in Biometrics at Tata Consultancy Services and Secured National Rank 1 in PSB Bank of Baroda Hackathon for Security engineering best idea and implementation . Akshita is a final-year student at IIT Bhilai and a recipient of the Chanakya Fellowship 2026. She completed a summer internship at DRDO, working in the domains of cybersecurity and cryptography. She secured Rank 1 in the National PSB Hackathon 2026, organized by Bank of Baroda. She is proficient in C++, Python, and SQL, with strong expertise in Machine Learning, Generative AI, and Large Language Models (LLMs). We met in our BTech 2nd year and we started working on the required skills to built something meaningful and since the very starting of our BTech journey we were very much attracted in building something that can help other people whether in terms of their normal livelihood or something that we can prevent them from being get trap in scams or other thing that can harm their financial status that they developed by their hard work .Despite of being from Electrical and MSME branch we gave our best in developing some meaningful skills to fulfil these needs of people that we dreamed and with the passage of time we achieved some recognition from college Best student award to State recognition to National Recognition and there after we gained so much of confidence that made us to start something meaningful. 2 Our biggest strength as a team is the combination of complementary technical skills, a shared vision, and the determination to solve real-world problems. We have developed strong expertise in Cybersecurity, Artificial Intelligence, Machine Learning, and software development, and the intersection of these domains gives us a unique advantage. Our strength is not limited to technical knowledge. Through hackathons, internships, projects, and practical problem-solving experiences, we have learned to work under pressure, experiment, adapt quickly, and convert ideas into practical solutions. We complement each other’s strengths and continuously learn from one another, allowing us to approach problems from multiple perspectives. Most importantly, we share a common purpose: to use technology to create meaningful and measurable impact. We are particularly motivated to build solutions that can protect people from emerging digital and financial threats while making technology more accessible and useful. We believe that the combination of Cybersecurity + AI, strong execution, continuous learning, and a shared purpose gives us the potential to move beyond conventional solutions, build something scalable, and create meaningful change in society. Admas Bhilai,Chhattisgarh,491001 ContextShield AI is a privacy-first, multilingual cybersecurity platform that prevents unsafe financial actions before they occur. It protects individuals from manipulation-based payment scams and protects businesses by controlling sensitive actions performed by AI agents. Its Context–Intent–Action Engine detects coercion, impersonation, malicious instructions and abnormal behaviour, then explains the risk and requests verification before money or sensitive data is moved. Existing security systems primarily examine login credentials and transaction patterns. They often fail when a genuine user is psychologically manipulated into authorising a fraudulent payment or when an authorised AI agent is tricked into performing a dangerous action. With digital-arrest scams, deepfake impersonation, malicious QR codes, prompt injection and autonomous AI tools increasing, people and organisations need protection at the moment of decision—not only after fraud or data loss has occurred. Existing security systems primarily examine login credentials and transaction patterns. They often fail when a genuine user is psychologically manipulated into authorising a fraudulent payment or when an authorised AI agent is tricked into performing a dangerous action. With digital-arrest scams, deepfake impersonation, malicious QR codes, prompt injection and autonomous AI tools increasing, people and organisations need protection at the moment of decision not only after fraud or data loss has occurred. Most fraud tools evaluate phone numbers, individual links or transaction patterns, while AI-security tools protect models separately. ContextShield combines both into one zero-trust financial-action firewall. It evaluates the complete context, the apparent intent and the proposed action before allowing a decision to proceed. Its defensibility will grow through a consented and de-identified multilingual dataset of scam journeys, agent-action patterns, confirmed outcomes and organisation-specific security policies. Privacy-first processing, explainable decisions and integrations with banks, fintech platforms and AI-agent frameworks will create additional barriers to replication. Idea Testimonials Our initial users are digitally active individuals, families and senior citizens vulnerable to online payment scams. Our paying customers will be banks, fintech and UPI platforms, telecom providers, cyber-insurers and enterprises using AI agents for sensitive financial or data-related actions. India’s digitally active payment users, banks, fintech platforms, telecom providers and enterprises adopting AI-enabled financial workflows. Initial focus: smartphone payment users in Indian cities, senior-citizen and family-safety communities, and Indian fintech, banking and AI-enabled enterprises needing fraud prevention. Initial 3-year target: 100,000 protected users and 10–20 institutional pilot or paying customers in India.(further we will discuss with the mentor about this) Freemium consumer protection with an optional family-safety subscription, combined with annual B2B licensing and usage-based SDK/API pricing for banks, fintech platforms and enterprises. Additional revenue will come through cyber-insurance and telecom partnerships. Indirect competitors include Truecaller, bank transaction-fraud systems, mobile-security products and enterprise AI-security platforms such as Lakera and Protect AI. ContextShield differs by detecting manipulation before payment and by securing high-risk actions proposed by both people and AI agents. We will acquire early users through universities, senior-citizen communities, digital-safety campaigns, referrals and cybercrime-awareness partners. Institutional customers will be acquired through direct pilots with fintech companies, banks, telecom providers, insurers and enterprise AI teams. We will first launch a privacy-first share-to-scan MVP for suspicious text, screenshots, links and QR codes. We will validate it through controlled user interviews and early feedback from students, families and senior citizens. Using this evidence, we will offer a fraud-prevention SDK to fintech and payment platforms, followed by AI-agent security for enterprises. Our long-term vision is to become the trusted safety layer for every high-risk digital decision. ContextShield will protect people from manipulation-based scams and organisations from unsafe AI-agent actions before money or sensitive data moves. We aim to build a multilingual, privacy-preserving platform that integrates with financial institutions, telecom networks and enterprise AI systems across India and globally. Pre-incorporation. We are a founding team validating the problem and building the initial product; we plan to incorporate an Indian Private Limited Company after early validation and mentor guidance. ₹0 external funding raised. The team is currently bootstrapped. Yes We seek IITACB’s mentorship, investor-readiness support and access to a strong Bengaluru network to validate our problem, refine our business model, strengthen our cybersecurity and privacy approach, and connect with fintech, enterprise and investor partners. We aim to validate the problem with target users, refine the MVP and go-to-market plan, develop a clear privacy and compliance roadmap, build a strong investor pitch, and secure introductions for pilot conversations with fintech, enterprise or cybersecurity partners. Yes. Our team can participate consistently in all virtual mentoring, investor sessions and programme activities. Bengaluru offers access to fintech, cybersecurity, SaaS and AI talent, while the Bommasandra industry hub offers potential enterprise users for our AI-agent security use case. We can use this ecosystem for pilot discovery, customer interviews and partnerships. IITACB can help through introductions to industry, fintech and enterprise decision-makers, mentors, legal and compliance experts, and relevant investors. No We will participate remotely while using IITACB’s virtual mentoring, investor network, workshops and ecosystem access. We may consider physical workspace as the team grows and pilot opportunities require a Bengaluru presence. Yes Core engine Proposed MVP architecture: a mobile/web client collects only user-selected content; on-device OCR, QR parsing and basic PII masking minimise exposure. A secure API backend performs multilingual text analysis, link/QR reputation checks, scam-pattern classification and explainable risk scoring. Encrypted storage retains only minimum required metadata; raw content is deleted after analysis unless the user explicitly opts in. The enterprise phase adds an API/MCP policy gateway to validate AI-agent tool calls, enforce permissions and transaction limits, redact sensitive fields and require human approval for high-risk actions. Services will be containerised and deployed in an India cloud region. At the idea stage, we do not claim a proprietary dataset. Our future advantage will come from a consented and de-identified multilingual dataset connecting scam narratives, risk signals, user feedback and confirmed outcomes, along with enterprise AI-agent action patterns and security policies. We will build this only with explicit opt-in, data minimisation and strong privacy controls. Our defensibility comes from combining human-scam context analysis and AI-agent action control in one Context–Intent–Action engine. Over time, consented de-identified multilingual data, explainable risk models, organisation-specific policies, trusted fintech integrations and feedback loops will make the system more accurate and difficult to replicate. Before pilot deployment, we will evaluate precision, recall, F1-score, false-positive rate, false-negative rate, PR-AUC, detection latency, user override rate and uptime. We will compare our system against rule-only keyword/link scanners and standard scam-reporting tools. We will prioritise low false negatives for high-risk scams while ensuring explanations are understandable and actionable for users. We are designing privacy by default. Users will voluntarily select what they want scanned; the product will not read messages, monitor calls or access financial credentials in the background. We will minimise collection, process locally where possible, encrypt necessary server-side processing, separate consent for analysis and model improvement, delete raw content by default, provide deletion and consent-withdrawal controls, and apply role-based access, audit logs and incident response. We will design for compliance with India’s DPDP framework and seek specialist legal review before financial-institution integrations. We do not depend on a specific policy intervention. India’s Digital India and cyber-awareness ecosystem supports adoption of safer digital practices. Any direct bank or UPI integration will be pursued only with appropriate partner approvals and alignment with applicable RBI, NPCI and data-protection requirements. Yes. Key risks include personal-data obligations, processing third-party information appearing in user-submitted content, consent management, children’s data and sector-specific requirements if we integrate with payment systems. We will begin as an independent warning and verification tool, avoid collecting OTPs, PINs and bank credentials, and obtain legal and compliance review before regulated payment integrations. The main risks at 10x scale are model-inference latency and cost, sudden traffic spikes, false positives, quality variation across Indian languages, secure data deletion and support operations. We will mitigate these through on-device preprocessing, asynchronous queues, autoscaling infrastructure, caching, model monitoring, multilingual testing, privacy-preserving retention controls and phased rollout. Yes. Our founding team combines complementary skills in cybersecurity, AI/ML and software development. We can build secure application workflows, develop and evaluate machine-learning models, analyse threats, design privacy-aware data pipelines and rapidly prototype full-stack solutions. Our hackathons, internships and practical projects have strengthened our ability to experiment, adapt and convert ideas into usable products. At the idea stage, no proprietary dataset, production model or filed IP is claimed yet. For the MVP, we will use only appropriately licensed public benchmark data, open-source security/OCR/NLP components and commercial APIs where terms permit. We will maintain a licence register, preserve required attribution, avoid using user submissions for third-party model training by default, and seek legal review before using any external dataset or model in production. We will use versioned models, offline evaluation datasets, privacy-preserving opt-in feedback, human review of disputed cases, error analysis, multilingual testing, monitoring for model drift and staged deployments. Every model or rule update will be evaluated against accuracy, false-positive impact, latency, security and privacy requirements before release. India first, with global potential. We will initially focus on Indian scam patterns, multilingual communication, UPI-related social engineering and local privacy requirements. Our underlying Context–Intent–Action architecture can later be adapted for other markets, languages, payment systems and enterprise AI-agent workflows. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/ed4D8hz0ygVw-2026_compressed.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/ed4D8hz0ygVw-2026_compressed.pdf Yes. ContextShield AI is mission-driven because it aims to protect people from emerging digital and financial threats before they lose money or sensitive data. Our initial focus includes families, senior citizens and digitally vulnerable users who are frequently targeted by manipulation-based scams. We are building privacy-first protection that empowers users to make safer decisions without turning security into surveillance. NA Ravi Teja Vila Our team brings complementary cybersecurity, AI/ML and software-development skills, along with practical learning from hackathons, internships and project work. We are committed to building a privacy-first and socially meaningful solution, and we seek IITACB’s mentorship to turn early problem validation into a scalable, investor-ready startup checked
Aug 21, 2026 @ 8:57 PM Divyansh Chhabria chhabriadivyansh@gmail.com https://www.linkedin.com/in/divyanshchhabria/ +919399258709 We both graduated from IIT Kanpur with a B.Tech in CSE (2021). Divyansh worked at Databricks for 1 year on the Observability team; Rajeev worked at Stripe for 1 year on the Batch Compute team. We both have a background in systems and performance from IIT Kanpur: CS610 (Programming for Performance), the ISC Student Cluster Competition (2024, 2025), and the AMD x GPU MODE hackathon, where we worked on optimizing LLM inference kernels (MXFP4 MoE, MLA Decode, MXFP4 GEMM) on AMD GPUs. We met in our first year at IIT Kanpur in 2021 — we were wingmates in the same hostel wing. We've known each other for about five years and have collaborated on multiple projects together, both during and after college. 2 We're early enough in our careers to stay close to the latest developments in AI and move fast without being anchored to older tools or ways of working. That's combined with a year each of hands-on industry experience (Databricks, Stripe) and a background in performance engineering from our time at IIT Kanpur, so we're not starting from zero - we can build on solid systems fundamentals while adapting quickly to a fast-moving space. Abhigya.ai https://www.abhigya.ai/ Bengaluru We're building a managed inference platform for open-weight AI models (e.g. DeepSeek, Kimi). Enterprises access these models through a router with an API compatible with their existing workflows, getting lower-cost inference than proprietary model APIs, with rupee-denominated pricing to remove FX exposure, and without needing to run their own infrastructure. Enterprises running AI inference face two compounding cost problems: proprietary models are significantly more expensive per token than open-weight alternatives, and most inference options (proprietary or open) are billed in dollars, adding FX exposure and unpredictability on top of the already-high cost. Open-weight models can close the capability gap at a fraction of the cost, but enterprises still need a reliable inference layer to run them. We host open-weight AI models (e.g. DeepSeek, Kimi) and serve them through a router with an OpenAI-compatible API, giving enterprises lower-cost inference than proprietary APIs without deploying or managing infrastructure themselves. We also list on model routing/aggregator platforms (e.g. OpenRouter) for discoverability. Target market Both India and global. India is a specific advantage (rupee billing, local support), but the core value proposition, lower-cost open-weight inference without infrastructure overhead, applies to any enterprise, anywhere. We offer a model-agnostic, ready-to-call inference API for open-weight models with rupee-denominated pricing, removing FX exposure for Indian enterprises. Unlike infra-first providers (E2E, Krutrim) that require customers to deploy models themselves, or Sarvam, which is primarily a model company, we focus purely on being a neutral managed inference layer. Our team has hands-on experience in inference kernel optimization and HPC systems engineering from IIT Kanpur (AMD x GPU MODE hackathon, ISC Student Cluster Competition, CS610). Idea Global AI inference market: $117.80B in 2026, projected to reach $312.64B by 2034 (CAGR 12.98%, 2026-2034). Source: Fortune Business Insights. The market for managed, hosted inference of open-weight models specifically, the segment we operate in. Reliable third-party sizing for this narrower segment doesn't exist, so we anchor on real company performance instead: Together AI, a direct comparable, reported $1.15B in annual bookings in mid-2026, with open-weight model usage tripling year over year, indicating a large and fast-growing addressable segment. Realistically, in our first 1-3 years we'd target a small share of inference volume routed through aggregator platforms like OpenRouter (which already route billions of tokens monthly across providers), competing on price for open-weight models, before expanding into direct enterprise relationships. We'd expect this to translate to low single-digit millions of dollars in annual revenue in the early stage, growing as usage and reliability track record build. Usage-based pricing, charging per token for inference. Initially distributed through OpenRouter, where we set our own per-token pricing and receive it in full (OpenRouter's fee is charged to the buyer on credit purchases, not deducted from our rate). As we build direct enterprise relationships, we'd also offer direct billing and custom pricing for larger customers. Baseten, Together AI, Fireworks AI, Sarvam We start by listing on OpenRouter, where developers and enterprises already discover and route requests to inference providers, giving us initial traffic without needing a direct sales motion from day one. As we build usage and reliability track record, we add direct enterprise relationships and billing for larger customers. Launch by listing on OpenRouter to get discovered by developers and enterprises already routing traffic through the platform, competing on price and reliability for open-weight models. Use that initial usage as a track record to move into direct enterprise relationships and billing, starting with India-based enterprises where we can also offer local support, while continuing to serve international customers through OpenRouter and direct channels. Long-term, we want to build sovereign AI inference infrastructure for India, serving not just enterprises but also government and defence institutions, and universities/students, so that critical data and AI workloads stay within India rather than routing through foreign providers. As adoption grows, we see this extending beyond cost savings into being trusted infrastructure for sectors where data residency and control matter most. Not yet incorporated. NA Yes We're IIT Kanpur graduates building an inference platform for open-weight AI models, and we're looking for mentorship, investor access, and infrastructure to help us go from idea to a validated product. IITACB's focus on deep-tech, its IIT-alumni network, and its Bommasandra facility are a strong fit for a team with our background in systems and performance engineering, and its investor connections are especially relevant given our near-term need for capital to cover GPU costs. We want to validate our idea with real enterprise customers, get our first pilot users onto the platform, and refine our go-to-market strategy. GPU rental cost is our primary near-term expense as an inference business, so investor connections and access to capital through the programme are a key priority, alongside mentorship on product and go-to-market. Yes Bangalore has a dense concentration of enterprises and startups that are exactly our target customers, companies building AI-powered products who need cost-effective inference. Being embedded in the Bommasandra hub gives us direct access to potential pilot customers, technical talent, and other founders solving adjacent problems. We'd want IITACB's help with mentor introductions, investor connections, particularly given our near-term need for capital to cover GPU costs, and introductions to enterprises in the hub who could be early design partners or pilot customers. No NA Yes Core engine We plan to serve open-weight models (e.g. DeepSeek, Kimi) using open-source inference serving frameworks (e.g. vLLM, SGLang), exposed through an OpenAI-compatible API and a router layer for model selection. Hardware choice (GPU vendor/cloud) will be based on price-performance for each model rather than a single fixed vendor. None at this stage. We're an inference infrastructure business, not a data or model company, our advantage is in serving efficiency and cost, not proprietary training data. A model-agnostic, ready-to-call inference API, distributed initially through OpenRouter, combined with our team's hands-on background in inference kernel optimization (AMD x GPU MODE hackathon) and HPC systems engineering (ISC Student Cluster Competition, CS610 at IIT Kanpur). We're honest that established players (Together AI, Fireworks, Baseten) are ahead on raw inference engine maturity; our near-term edge is focus, cost, and India-specific reach as we build track record. We plan to benchmark using standard inference metrics: time-to-first-token, tokens-per-second throughput, uptime, and cost per million tokens, benchmarked directly against Together AI, Fireworks, and Baseten on the same models. At this stage, our plan is to not retain customer request/response data beyond what's needed to serve the request, encrypt data in transit, and align with India's Digital Personal Data Protection (DPDP) Act as we build. We don't yet have formal compliance certifications (e.g. SOC 2), which we'd pursue as we onboard enterprise customers who require them. The IndiaAI Mission, which has deployed 38,000 GPUs domestically at subsidized rates (~₹65/hour), lowers the cost of building inference infrastructure in India and is directly relevant to our business. India's DPDP Act and evolving AI-specific regulation could impose compliance requirements on how we handle enterprise customer data. Export controls on GPUs/AI chips could also affect hardware availability and cost. At 10x scale, we'd expect GPU capacity and availability to become the primary constraint, along with router/routing-layer latency under higher concurrent load, and our own team's ops bandwidth, since we're currently two founders with no dedicated infrastructure/SRE team. Yes, both co-founders. Our background includes inference kernel optimization (MXFP4 MoE, MLA Decode, MXFP4 GEMM, from the AMD x GPU MODE hackathon), HPC systems engineering (ISC Student Cluster Competition 2024/2025, CS610 Programming for Performance at IIT Kanpur), plus industry experience in observability (Databricks) and batch compute systems (Stripe). We use open-weight models under their published licenses (e.g. DeepSeek under MIT, Kimi K3 under a Modified MIT license permitting commercial use), and open-source serving frameworks (e.g. vLLM, SGLang, both Apache 2.0). We don't own or claim IP over any of these; we have no proprietary datasets or filed IP at this stage. By adopting new open-weight models quickly as they're released, continuing to optimize serving performance at the kernel/inference-engine level, and benchmarking against competitors on an ongoing basis. Both. We launch globally via OpenRouter, while also building India-specific enterprise relationships and, longer-term, India-specific value (e.g. lower FX exposure). 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/O264eLyTQqcj-Abhigya-Pitch-Deck.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/O264eLyTQqcj-Abhigya-Pitch-Deck.pdf http://NA Yes. Our core mission is reducing India's reliance on foreign, dollar-denominated AI infrastructure, by making it easier and cheaper for Indian enterprises to run inference on open-weight models domestically. Beyond the cost savings, this also means Indian enterprise data and workloads can stay within India rather than routing through foreign providers. We also see this as lowering the barrier for smaller Indian enterprises and startups, who can't afford proprietary API costs the way large companies can, to build with AI. https://www.pranavhari.com/writing/indias-inference-needs-are-a-ticking-time-bomb-for-our-account-deficit NA NA NA checked
Aug 20, 2026 @ 1:22 PM Arpan Banerjee arpanb2006@gmail.com http://www.linkedin.com/in/arpanb http://NA +91 9845024959 CEO and Director My wife Sudarsana and I are the founders of the startup and we have worked together before. 2 Our biggest strength is deep business and technology experience combined with a strong understanding of how enterprises actually operate. With 30+ years across strategy, sales, operations, technology we bring a business-first perspective, strong industry networks and the ability to translate real business problems into scalable technology solutions. As a team we are meticulous, resourceful, ambitious with ability to get things done. Arisanaa Technologies Private Limited www.arisanaa.com BENGALURU Arisanaa Technologies is a technology solutions company building intelligent solutions that help businesses improve revenue, operations and decision-making. We combine AI, data intelligence and modern software engineering to turn complex business problems into measurable outcomes. Mid-sized businesses have fragmented data across CRM, ERP, sales and customer systems, making it difficult to identify revenue leakage, growth opportunities and emerging risks. Arisanaa aims to use AI to turn this fragmented data into actionable revenue intelligence and recommended decisions. Arisanaa is exploring an AI-native Revenue Intelligence platform that connects data from CRM, ERP, sales and customer systems to identify revenue leakage, growth opportunities and risks, and provide actionable recommendations to business teams. We are at the ideation and validation stage (not reached the MVP build stage). Our differentiation is a business-first, AI-native approach focused on mid-market companies, rather than another CRM or dashboard layer. We aim to combine fragmented revenue data with contextual business intelligence to move beyond reporting toward identifying opportunities, predicting risks and recommending actions. Idea Our initial target customers are mid-sized B2B companies and GCCs with established sales operations and fragmented data across CRM, ERP, customer and operational systems. We will initially focus on manufacturing, automotive, consumer products, healthcare and other industries where improving revenue growth, retention and forecasting has a measurable business impact. US$3B in India. Globally US$10B+ US$1B in India. US$5B+ US$50M (1% of global SAM) Initially, we plan to use a B2B SaaS model with annual subscriptions priced according to company size, data volume and functionality. We may also offer paid implementation and integration services during the initial deployment, with the long-term model focused on recurring subscription revenue. Global: Gong, Clari, Salesforce, 6sense and People.ai. India: Zoho, LeadSquared, Freshworks, MoEngage and Salesforce. We see the current market as fragmented between CRM, sales intelligence, customer engagement and revenue orchestration platforms, leaving an opportunity to build a simpler AI-native revenue intelligence solution for mid-market businesses. We will initially acquire customers through the founders’ enterprise network, industry relationships, alumni networks and strategic referrals, using focused problem-led engagements to establish early customers and validate the product. As the platform matures, we plan to scale through channel/technology partners, targeted account-based sales and industry-focused digital marketing. We will begin with a founder-led, consultative GTM focused on mid-market B2B companies and GCCs, using our enterprise networks, industry relationships and strategic partners to identify high-value revenue problems. Initial engagements will help validate use cases and build reference customers; we will then scale through industry-focused sales, channel partnerships and targeted account-based marketing, with a recurring SaaS model as the product matures. Our long-term vision is to build an AI-native business intelligence and decision platform for mid-market enterprises—moving beyond reporting and CRM analytics to continuously identify growth opportunities, risks and inefficiencies and recommend actions. We aim to build a globally scalable SaaS company, starting with revenue intelligence and expanding into broader business decision intelligence. Arisanaa got incorported on 18th Aug 2026 NA Yes Arisanaa is at an early stage of validating an AI-native Revenue Intelligence platform, and we want to sharpen the product thesis, business model and investment story before building the MVP. The programme will help us learn from experienced mentors, validate our market opportunity and connect with relevant VCs and angel investors who can support product development and global scale. We want to validate and sharpen our Revenue Intelligence product thesis, define a clear path to MVP and early customers, and strengthen our investor pitch and business model. We also hope to build relationships with relevant investors and potential mentors who can help us scale the product into a global SaaS business. Yes We see Bengaluru, particularly the Bommasandra–Electronic City industrial corridor, as an ideal market for customer discovery and validation, given its concentration of manufacturing, automotive, engineering, healthcare and technology companies. We plan to leverage this ecosystem to identify recurring revenue and operational challenges, validate our AI solution with early customers and build industry-specific use cases. IITACB can help us access its alumni and industry network, connect us with relevant founders and enterprises, sharpen our product and investor proposition, and facilitate introductions to mentors and investors as we move from ideation to MVP and early traction. No NA. At this stage, we do not need physical office seats as we are building a lean company with minimal infra costs. Yes Core engine A cloud-native, modular architecture with secure connectors to CRM, ERP and operational data sources; an AI/ML intelligence layer for analysis and prediction; and an API-driven application layer for insights, recommendations and workflows. Currently none. We are at the planning/validation stage. Over time, we aim to build a proprietary advantage through anonymized, aggregated customer data, industry-specific benchmarks and learnings generated from the platform's usage across customers. Our defensibility will come from proprietary industry-specific intelligence built on fragmented CRM, ERP, customer and operational data, combined with domain-specific AI models and workflows. As adoption grows, anonymized usage data, benchmarks and customer learnings can create a compounding data and intelligence advantage that is difficult to replicate. As we are currently at the planning/validation stage, we do not yet have product performance benchmarks. For the MVP, we plan to measure prediction/insight accuracy, recommendation relevance, response latency, system availability, data processing accuracy and scalability, and benchmark these against relevant industry solutions and customer baselines. The platform will follow a security-by-design approach, with encrypted data in transit and at rest, role-based access controls, tenant-level data isolation, secure API integrations, audit logging and controlled data retention. We will design for applicable privacy regulations such as India’s DPDP Act and GDPR where relevant, with customer data used only for agreed purposes and not for training shared models without explicit consent. No specific policy intervention is currently critical to our business. However, India's growing focus on AI adoption, digitalisation, data protection and technology-led productivity provides a supportive environment for our planned solution. The key regulatory risks relate to data privacy, cross-border data transfers, AI governance and sector-specific data regulations. We plan to address these through privacy-by-design, appropriate data governance, security controls and compliance with applicable regulations such as India’s DPDP Act and GDPR where relevant. As we scale 10x, the main challenges would be data ingestion and processing volumes, AI inference costs/latency, database performance and maintaining tenant-level security and reliability. We therefore have to design the architecture to be modular and cloud-native, with independently scalable data, AI and application layers. Yes. The founding team is supported by experienced technology leaders and specialists with expertise in AI/ML, data engineering, analytics, cloud and modern software architecture. The team is being assembled in a lean, senior-led model, with additional specialist talent brought in as the product moves from validation to MVP. We are currently not using any proprietary datasets or custom code components, as the product is still at the planning/validation stage. The planned MVP will use commercially licensed/open-source AI/ML frameworks and standard cloud components, together with customer-authorized data through secure integrations. No proprietary IP reference is currently available. We plan to continuously improve the platform through customer feedback, monitoring AI accuracy and recommendation quality, model evaluation, performance monitoring and regular optimisation of data pipelines and infrastructure. As usage grows, anonymized learnings and industry-specific benchmarks will help improve the relevance and reliability of the platform. Both. We plan to use India as our initial market for customer validation and product development, while designing the platform from the outset for global markets, particularly the US, UK and other English-speaking markets. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/yBHFMGhk1wDr-Arisanaa_AI_Revenue_Intelligence_Concept_Note.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/yBHFMGhk1wDr-Arisanaa_AI_Revenue_Intelligence_Concept_Note.pdf http://NA Its a mix of both. Our mission is to make advanced AI and data-driven decision intelligence accessible to mid-market businesses that often lack the resources and capabilities of large enterprises. By helping businesses improve productivity, reduce revenue leakage and make better decisions, we aim to enable sustainable growth and more efficient use of resources. NA TAAB BLR LIFE MEMBERS What'sapp group. Arisanaa Technologies has just got incorporated (18th Aug 2026). We are particularly interested in IITACB's mentorship, industry access and investor network to validate the opportunity, develop the MVP and build a globally scalable product. checked
Aug 20, 2026 @ 12:58 PM Manoj Agarwal manoj@agarwalestates.com https://www.linkedin.com/in/trustredefined/ http://agarwalestates.com +91 Manoj Agarwal — Founder & CEO Owns product vision, business strategy, and investor and partner relationships. Brings 13+ years of real estate investment experience across Indian and US markets, and lived the problem ZeroChaos solves from both the owner and operator side. Ankita Agarwal — CTO Owns architecture, engineering and the AI layer. Ten years in IT, including seven at Coforge BPS as an AI/ML and Automation Developer and Team Lead, working on agentic AI and RAG systems and leading an in-house AI platform on Azure, OpenAI GPT and Streamlit for client POCs in intelligent document processing and contextual automation. M.Tech in Data Analytics, BITS Pilani (WILP), 2025. At Agarwal Estates she has put renewal, move-out, CRM and email-tracking automation into production. Puja Agarwal — Brand Manager Owns brand, positioning and go-to-market communication. Brand Partner at Agarwal Estates across property management, commercial real estate and digital marketing, with a management degree from HHL Leipzig Graduate School of Management. Esha Karda — Sales Owns customer discovery, onboarding and account relationships. With Agarwal Estates since 2014, 10+ years in real estate, MBA from Amity Business School Lucknow, and pioneered the firm's sales process. Pragya Agarwal — Co-founder/Program Coordinator; Coordination and follow-through across the team — keeps engineering, sales and brand moving against the same plan and makes sure things don't stall between functions. Bachelor's in Business Administration from IESEG School of Management, France; at Agarwal Estates she works across the operation rather than inside a single function. We all met at Agarwal Estates, the Bengaluru real estate services firm Manoj founded in 2012. We didn't come together to chase a startup idea — we run an operating business, and ZeroChaos is being built inside it because we are the ones living the problem. Esha joined in 2014 and has worked with Manoj for over eleven years, building the sales function from scratch. Pragya, Manoj's daughter, grew up around the business and now works across it as Chief of Staff, keeping the functions aligned and moving. Puja joined three years ago to own the brand as the firm scaled. Ankita is the most recent addition, coming on in mid-2026 with seven years of applied AI and automation engineering — hired specifically because we knew what capability we were missing, and within her first months she moved our core operational processes from manual to automated. So we bring more than a decade of working together inside a live operation, with real customers and real deadlines, and a problem we experience daily rather than one we researched. We've already worked through the unglamorous parts — missed targets, disagreements, process rebuilds — long before deciding to turn this into a product. 2 We are the customer we are building for. We run a Bengaluru real estate services business, and the chaos ZeroChaos addresses is chaos we manage every day — the requirements weren't researched, they were lived. We've already proved the thesis inside our own operation. Before designing ZeroChaos we built and put into production the automation our business needed: tenant renewal workflows with auto-generated agreements and email, move-out process automation, a CRM migration, and an email delivery and tracking pipeline. Those run against real customers today. ZeroChaos is the productisation of what we learned building them — the architecture and design are complete and we are moving into build. The team makes that possible because domain and engineering sit at the same table. Manoj and Esha bring over a decade each of frontline real estate operations, Ankita brings seven years of applied AI and automation engineering including agentic AI, RAG and intelligent document processing, Puja owns positioning and go-to-market, and Pragya keeps the functions aligned as Program Co ordinator. Nothing is lost in translation between the people who feel the problem and the people building for it. And we've worked together long enough to know how we behave under pressure — this team has shipped, missed targets and rebuilt processes together while keeping a business running. ZeroChaos zerochaos.in Bengaluru, Karnataka ZeroChaos is a transaction-management platform for Indian residential property deals. It brings buyers, sellers and the professionals around them — lawyer, CA, agent, PoA holder, bank loan officer — onto a single shared workflow that runs from offer through MoU, title verification, sale agreement, sale deed and registration, with milestone-linked escrow. It is not a marketplace: it serves parties who have already found each other and now face months of paperwork with no system of record. A rental track (agreement, deposit escrow, renewal) runs on the same engine. A resale deal in India isn't one transaction — it's thirty small ones across seven parties coordinated over WhatsApp and email. Money moves before title is verified, documents live in someone's inbox, and nobody can answer "what's blocking us, and whose move is it?" ZeroChaos puts the deal on a single shared state driven by a configurable stage machine — Onboarding → MoU → Legal Verification → Sale Agreement → Sale Deed → Registration, with the home loan as a parallel track. Each stage has role-scoped tasks, a document checklist and a gated exit. Escrow makes it binding. Buyer token and earnest money sit in a regulated third-party escrow and release only on verified milestones — token on title clearance, balance on confirmed registration. Escrow is scoped to token and earnest money, never full consideration; home loans disburse directly to the seller at registration. Disputes become a procedure. Title verification runs a typed checklist that aggregates deterministically to Approved / Conditional / Rejected. Exits are adjudicated against a closed list of legal reason codes mapped to those checks — a genuine title defect refunds, a change of mind forfeits — with a fixed rebuttal window and a neutral panel only for genuinely contested cases. Coordination, not enforcement. Buyer obligations are escrow-enforceable; seller penalties are contractual, evidenced by the platform rather than collected by it. That boundary is stated openly. What both sides get is an immutable audit trail of every edit, approval, signature and payment. Documents. Templates generate the agreements, edits surface as diffs before re-signoff, e-stamp and e-sign via SignDesk, with the sale deed handled as an explicit wet-signature state. KYC is progressive, collected before first escrow funding. Built on MERN, role-parameterised rather than duplicated per role, with per-state stamp and registration rules as a pluggable module — Karnataka first for sale, multi-state for rental. We start where the portals stop. Listing platforms hand over a phone number and walk away. The three to six months that follow — where deals actually die — has no product. We serve pre-matched parties through that window, so we're not competing for discovery spend. The moat is encoded legal procedure, not code. Anyone can build a workflow tool. The slow asset is the adjudication layer: a typed title checklist that aggregates deterministically, a closed list of legal reason codes mapped to each check, and an evidence-and-rebuttal procedure with bounded windows. Screens can be cloned in a quarter; a defensible answer to "does this exit refund or forfeit?" takes domain access we've already paid for. Escrow scoping is a hard-won position. Token and earnest money only, milestone-released, with loan disbursement staying bank-to-seller. It's the only version Indian sellers accept and the only one that keeps us a coordinator rather than a regulated custodian — most attempts either over-reach into licensing or under-reach and add no trust. Switching costs are structural. Nobody moves a live deal mid-flight once the audit trail, signed instruments and escrow instructions sit with us. Compounding assets: a state-pluggable stamp and registration module built for portability from day one, a lawyer/CA network that gets stickier per deal, and a rental track on the same engine that turns a once-a-decade product into a repeat-use one. MVP Users, Pilots Poperty Onwers/Buyers/Sellers/Tenants/Brokers/Property Consultants Four lines, three of which your schema already supports: Transaction fee — platform fee at onboarding, configurable with waiver support, paid by buyer/seller/agent Escrow service fee — bps on escrowed token + earnest money, charged at release Document & agreement fees — template generation, e-stamp, e-sign, per instrument; the primary rental revenue line SaaS subscription — agent/broker orgs and developers running many deals; the B2B2C path and the most durable line Realtimate, Legality Our first channel is the business we already run. Agarwal Estates has operated in Bengaluru since 2012 with an established client base, an active content and search presence, and ongoing apartment-association partnerships — a warm route to the owners, landlords and management firms who share our problem. Second, we sell from a working reference: we run these systems in our own operation, so the pitch is a demonstration, not a deck. Early customers are onboarded hands-on by the team that built the workflows, which keeps acquisition cost low and feeds product feedback back in the same conversation. Third, real estate runs on referral and reputation, and eleven years of relationships across agencies, associations and owners is our distribution advantage, supplemented by content-led inbound. We are pre-launch, so the immediate step is a small set of design partners outside our own operation, using ZeroChaos free in exchange for structured feedback, before we open paid acquisition. Wedge with rental, monetise with resale To become the system of record for property transactions in India — the layer where the deal state, the money and the evidence all live in one place. Today a property's history is scattered across a sub-registrar's ledger, a lawyer's filing cabinet and a family's document box, and every transaction rebuilds that picture from scratch. ZeroChaos accumulates a structured, verified transaction and title record with every deal it closes. Over time that becomes the more valuable asset than the workflow itself: faster diligence, cheaper title insurance, better loan underwriting, and eventually a portable property record that makes the next transaction on the same asset dramatically cheaper than the last. Not yet incorporated as a separate entity No external funding. Self-funded through Agarwal Estates' operating revenue Yes We have built and run production automation inside our own real estate operation, and ZeroChaos is the productisation of that work. What we lack is not domain knowledge or engineering capability — it's the outside view. We're applying for structured mentorship from people who have taken a product from internal tool to market, access to the IITACB alumni and investor network, and the discipline of building alongside other founders rather than inside our own company where every assumption goes unchallenged. The risk we're trying to avoid is building something that works beautifully for us and for nobody else. Three things. First, get from completed architecture to a working product with external design partners — real users outside our own operation, giving us feedback we can't generate internally. Second, validate the business model: who the buyer is, what they'll pay for and on what unit, tested against real conversations rather than our assumptions. Third, prepare for external capital — sharpen the pitch, the metrics and the founder-team structure so that when we approach investors we're ready, not learning on the call. Yes — virtual participation is what works for us. Our team is based in north Bengaluru and runs a live real estate operation alongside building ZeroChaos, which makes regular travel to Bommasandra impractical. We are fully committed to the programme's substance: mentoring sessions, reviews, workshops and investor conversations attended remotely, with in-person attendance for key milestones such as pitch days or demo sessions where physical presence matters. The Bommasandra and Electronic City corridor concentrates tens of thousands of employees across biotech, pharma, electronics and manufacturing, and that concentration creates the exact demand ZeroChaos serves: high-volume rental housing, employee relocation, and landlords and management firms handling heavy tenant churn on largely manual processes. Every company in that hub has an HR or admin function dealing with employee accommodation, and every one of them is a potential channel to our end users. It is the densest cluster of our customer in Bengaluru, and IITACB's standing within it gives us a credible route to those conversations. Bengaluru more broadly is India's most active rental market — the volume, the churn and the fragmentation that make this problem worth solving are all concentrated here, which is why we are launching in our home market rather than treating it as a test bed for somewhere else. Where IITACB helps us most is not physical space but access and challenge. First, mentorship from founders who have taken an internal tool to market — the specific transition we are making, and the one we are most likely to get wrong. Second, introductions through the alumni and corporate network to early design partners, including within the hub itself. Third, investor-connect at the point where we have external validation and are ready to raise. Fourth, the discipline of building alongside other founders who will question assumptions that go unchallenged inside our own company. No We are applying for virtual participation and would not initially rent seats. If we later establish a build team requiring dedicated space, we would use the co-working facility for focused development away from our operating business, and the meeting and conference facilities for design-partner and investor sessions. In the near term the value we seek from IITACB is mentorship, network and investor-connect rather than physical infrastructure. Yes Supporting feature MERN — React/Redux frontend, Node/Express/TypeScript API, MongoDB via Mongoose, Redis cache, S3 for documents, JWT auth. Layered as UI → business layer → data access. The business layer is decomposed into a configurable workflow/stage engine, a role-and-access engine, a document template and generation engine, escrow and payment orchestration, a termination/penalty engine, and a single third-party integration façade over e-sign, e-stamp, escrow, bank and payments. Stages, sub-stages, actions, permissions and notification rules are configuration rather than code. Today: none — pre-launch, no data. What accumulates is the asset: a structured, evidence-linked record of every title check, defect, exit reason and stall point across deals. Over time that yields the only dataset of its kind in Indian resale — which defects actually kill deals, where transactions stall, real cycle times by city and property type. That's what eventually powers underwriting, title risk scoring, and the OCR/extraction models above. Worth stating as a build-up, not a claim. The adjudication layer — typed title checklist, closed and versioned legal-reason codes mapped to each check, bounded evidence-and-rebuttal procedure. Screens can be cloned in a quarter; a defensible answer to "does this exit refund or forfeit?" requires legal domain access. Plus a state-pluggable stamp/registration module, switching costs from the audit trail and escrow instructions on live deals, and a rental track on the same engine that supplies frequency. No benchmarks yet — nothing is live, and there's no competitor baseline to measure against since incumbents are lawyers and WhatsApp. The metrics we'll instrument from day one: deal cycle time versus the offline baseline (~90–150 days), stage-level stall rate and drop-off, escrow reconciliation accuracy (target 100%, zero unreconciled), release-trigger latency, e-sign and e-stamp completion rate, document extraction accuracy once OCR ships, API p95 latency, and uptime. Cycle time and stall rate are the ones that matter commercially. Handled: JWT auth, role-scoped access, S3 for documents, immutable audit trail, escrow held by a regulated bank so we never take custody of funds, KYC collected only where legally required rather than at signup. Known gaps under remediation, flagged in our own schema review: Aadhaar, PAN and bank details currently stored as plain strings — moving to field-level encryption or a PII vault with masked values; binary documents stored inline in MongoDB — moving to S3-with-reference; document retention and deletion lifecycle undefined; RBAC designed but not fully implemented. DPDP Act 2023 obligations — consent, purpose limitation, breach notification, retention limits — need a formal mapping. Aadhaar e-Sign and DigiLocker make legally-strong digital execution and document pull possible. The IT Act gives e-signatures statutory validity. State e-stamping regimes make stamp duty payable digitally. RERA raised transparency expectations across the sector. DPDP creates a compliance burden that favours platforms over informal WhatsApp-based practice. Client-funds licensing — whether we need a licence to be in the escrow flow, or whether we're a tech layer on a bank-trustee account. Open, legal-counsel question, and material to the whole funds module. Payment aggregator regime — whether RBI PA norms apply to our fee and escrow orchestration. Registrable instruments still require physical execution and registration — the sale deed cannot be e-signed away. We model it as a wet-signature state rather than pretending otherwise; if that changes, it's upside. State stamp and registration variance — mitigated by the rules module, but each state is real work. Adjudication liability — if the platform decides disputed outcomes, we own that risk. Hence the neutral-panel escalation. Honestly, several things, and we know where: binary documents inside MongoDB hit the 16MB document limit and blow up working-set memory; the Property document is a single hub with unbounded embedded arrays and concurrent multi-party writes — contention and document growth both bite; recommended indexes aren't all in place, so stage dashboards degrade; escrow reconciliation is the highest-consequence path and needs idempotency and a replay ledger before volume; email-only notifications won't sustain completion rates; the rental module bypasses the shared workflow engine, so it diverges structurally as both grow; and concierge ops don't scale past a few dozen concurrent deals without the ops console. Yes. Our CTO, Ankita Agarwal, brings ten years in IT, including seven at Coforge BPS as an AI/ML and Automation Developer and Team Lead. Her core expertise — intelligent document processing, OCR and RAG systems — maps directly onto the AI surface our product needs: extraction and verification from title deeds, encumbrance certificates and khata records. At Coforge she led development of an in-house AI platform on Azure and OpenAI models, delivered client POCs in intelligent document processing and contextual automation, and contributed to an in-house OCR product. She holds an M.Tech in Data Analytics from BITS Pilani (WILP, 2025). Critically, she has already shipped production automation inside our own real-estate operation — tenant renewal workflows, move-out processing, CRM migration and an email delivery and tracking pipeline — several of which are modules on the ZeroChaos roadmap. None registered. Protection today is copyright in the codebase and trade secret in the adjudication rulebook and title checklist. The immediately actionable step is a trademark filing for ZeroChaos; a process patent is unlikely to be worth pursuing in this domain in India. Instrument the deal funnel from day one and treat stall points as the product roadmap — where deals stop is where the next feature goes. Version the legal-reason codes and checklist so the rulebook improves as real disputes surface. Build the OCR and anomaly-detection models on our own accumulated document corpus once volume exists, with accuracy measured against lawyer verdicts. India-first and India-deep. Stamp duty, sub-registrar workflow, khata and EC, Aadhaar e-sign, TDS under 194-IA, RERA — the product is the local regulation. The transferable asset is the engine architecture; the eventual path is other high-friction, low-trust registration regimes in South and Southeast Asia, not the US or EU where title insurance already solved this. Not a near-term claim. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/TuLk6Ybn1elJ-ZeroChaos_Pitch_novideo.pptx, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/TuLk6Ybn1elJ-ZeroChaos_Pitch_novideo.pptx https://drive.google.com/file/d/1mb_n5OmL3aX0jJyVPTWxK_aJZDTL2dyB/view?usp=drive_link Property is the largest transaction most Indian families ever make, and it is conducted with almost no procedural protection — no verification standard, no escrow, no record. When a title defect surfaces years later, the buyer absorbs the loss entirely. ZeroChaos puts a fixed, evidenced title-verification standard and milestone-released escrow on every deal, so the protection currently available only to buyers who can afford the right lawyer becomes the default. Secondarily, it moves transactions toward formal, documented, tax-compliant records. First generation entrepreneurs NA checked
Aug 20, 2026 @ 7:11 AM Cdr Arun Ravindranathan (Retd) natzaerotech@gmail.com https://www.linkedin.com/in/arunrnathan/ http://NA 918805266842 Founder and Managing Director The partner is My father 1 The founding team brings complementary expertise across aerospace, maritime navigation, naval operations and underwater warfare. The Founder is a retired Indian Navy aerospace and surface combatant specialist, with extensive experience in naval aviation and Defence systems. The Partner brings deep operational expertise in surface naval operations and Special Forces, including diving and underwater operations. Together, the team spans the full spectrum of naval operations—from air and surface to underwater domains—providing a unique operational perspective for the design and development of mission-ready Defence systems, with a specific focus on next-generation maritime and naval applications. NATZAERO Tech Pvt Ltd NA Kozhikode The start up caters for the development of Defence systems and solutions for problems faced in the Armed forces. Development of unmanned Wing in Ground Effect Crafts Wing-in-Ground Effect (WIG) craft offer a unique combination of high speed, long endurance, low-altitude operation and significantly greater payload efficiency than conventional UAVs and fast patrol craft. Operating just above the sea surface, WIG craft exploit ground effect to reduce induced drag and improve aerodynamic efficiency, enabling them to cover large maritime areas rapidly while consuming substantially less energy than comparable airborne platforms. Their low-altitude flight profile can also reduce radar visibility against the sea background, creating opportunities for maritime surveillance, reconnaissance, coastal patrol, search and rescue, logistics and rapid-response missions. For Defence forces, WIG craft can bridge the operational gap between aircraft, UAVs and surface vessels. They can provide persistent surveillance over India's extensive coastline, island territories and maritime approaches, while potentially operating from dispersed locations and selected naval platforms. Their ability to carry meaningful payloads over long distances makes them attractive for ISR sensors, communications relays, electronic surveillance, resupply and rapid deployment of personnel or equipment. For the Indian Navy and Coast Guard in particular, WIG systems could provide a cost-effective means of extending maritime domain awareness and responding rapidly across large areas, while offering the potential for unmanned operation and lower operating costs than conventional aircraft. The concept has not yet been explored in the country and also the world as such. WIG craft occupy a largely underserved space between conventional UAVs, aircraft and high-speed surface vessels. By exploiting ground effect, the platform combines the speed and range of an aircraft with the payload efficiency and lower operating cost of a maritime platform. Unlike conventional UAVs that must continuously generate lift in free air, a WIG craft operating close to the surface can achieve improved aerodynamic efficiency, enabling longer endurance and greater payload capability for a given propulsion system. This creates a distinct value proposition for maritime missions where range, endurance, speed and payload must be achieved simultaneously. Our differentiation lies in developing WIG technology as an unmanned, modular and mission-configurable defence platform. The architecture can be adapted for ISR, maritime surveillance, logistics, search and rescue, communications relay and other specialised missions, while being designed for operation from coastal bases, islands and potentially naval platforms. This creates a new category of affordable, persistent maritime capability between drones and conventional patrol vessels—offering Defence users a scalable platform with lower operating and deployment costs and the potential to address missions that are currently expensive or inadequately served by existing systems. MVP Users Indian Navy, Indian Coast Guard, BSF, Coastal Police, NDRF, ₹2625 Crore ₹656 Crore ₹ 112.5 Crore ( 5 yrs conservative estimate) We generate revenue through platform sales and mission-system integration, complemented by recurring lifecycle support, upgrades, licensing and international exports None in India yet Direct pitch to Defence customers, IDEX and TDF route Defence-led, demonstration-driven and partnership-enabled strategy Our vision is to create a new category of autonomous maritime capability from India—bridging the gap between UAVs and surface vessels. We aim to evolve from a WIG platform developer into a global maritime autonomy company, delivering indigenous, scalable and mission-configurable systems for Defence, security and commercial maritime applications 20 March 2025 10 L Govt grant from SISFS No For better reach, incubation possibilities and partnership with relevant players in the field More insight on the how to go about the journey of growing as a company and the various options available to introduce and market my unique product in the market yes I am preently looking at incubation support to set up my design facilities as well as a production facility in Bangalore. The association with IIT ACB will help me establish a design facility at the center and also help me connect with relevant market players for setting up my manufacturing facility. Yes I intend to set up my design team at IIT ACB as well as my marketing team so as to help expand my operations as well as improve networking to connect with potential users. Yes Supporting feature WIG platform is conceived as a modular, autonomous maritime system integrating an aerodynamically efficient WIG airframe with distributed propulsion, autonomous flight controls, navigation, communications and mission payloads. The architecture is designed around a common core platform that can be scaled across multiple sizes and configured for different Defence missions. Presently the Indian Market does not have any player in this field. Also, our competitive advantage is not simply the WIG configuration—it is the combination of operational Defence expertise, proprietary WIG aerodynamics and autonomy, mission-system integration, accumulated flight data and customer-validated platforms The present impetus for drone procurement by the defence forces helps this concept as it is a unique product which fills a very important gap presently available between airborne and maritime drones as well as a gap in environment of operation. Since the product is a first entry product in the Indian market, regulatory compliances will be there. Most importantly, the regulator as well as the designer will have to move hand in hand as it would be a first experience for both the parties. However, being a marine craft, the process are mostly known and set. Further, the involvement of the Indian Navy and the Coast Guard will help speed up the requirements. Presently the manufacturing capability. However, the company plans to use methods like offloading part manufacture contracts to external agencies to mitigate the shortcomings. The team is presently concentrating on the development of a working prototype. The team would be expanded for further product refinement as well as AI use once the prototype completes testing. This is done specifically due to the reason that, being a new segment, user need is of utmost importance prior to development of a solution. The company aims to develop 4 limited scale prototypes of different types and sizes for continuous flying and performance evaluation. The data obtained from these would be utilized to reach an optimum sellable product. the product will first see the Indian markets. Slowly the products will be opened up for global markets depending on the need and the standards needed for the same. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/6lnE0LyxP0ej-NATZAERO-TECH-PVT-LTD-IRONFISH-PITCH-DECK.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/6lnE0LyxP0ej-NATZAERO-TECH-PVT-LTD-IRONFISH-PITCH-DECK.pdf We are a mission-driven deep-tech Defence company developing autonomous Wing-in-Ground Effect platforms to address critical maritime surveillance, security, logistics and search-and-rescue challenges. Our mission is to deliver indigenous, cost-effective and scalable maritime capabilities while reducing risk to personnel and strengthening India's strategic and technological autonomy Mr Mohit Malhotra ( IIT Mandi Sec at IIT-ACB) checked
Aug 19, 2026 @ 7:44 PM Nikhil Patra nikhil@vidhikai.com https://www.linkedin.com/in/nikhil-patra/ http://NA 9556679622 Nikhil Patra – Co-founder & CEO: Leads the overall vision, product strategy, business development, customer discovery, partnerships, fundraising, and go-to-market strategy. He has a background in MCA and focuses on building Vidhik AI as an accessible AI-powered LegalTech platform. Lingaraj Senapati – Co-Founder & CTO: Leads technology strategy, product architecture, AI/technology roadmap, and technical execution. He has an MCA and 15+ years of experience in product development and technology. We have known each other for around 5 years and first met while working at a business training and consulting firm in Bhubaneswar. Over the years, we developed a strong understanding of each other's strengths and began working together on technology and business initiatives. We later combined our complementary skills to build Vidhik AI, with Nikhil focusing on product, business, and growth and Lingaraj leading technology and product development. All Our biggest strength is the combination of business, product, and technology expertise. Nikhil focuses on product vision, customer needs, business development, and growth, while Lingaraj brings 15+ years of technology and product development experience. This allows us to move quickly from identifying real-world legal problems to designing, building, and improving practical technology solutions. We also have a strong long-term commitment to building Vidhik AI and are working full-time toward making legal assistance more accessible and affordable. Vidhik AI https://vidhikai.com/ Bhubaneswar Vidhik AI is an AI-powered LegalTech platform that helps startups, MSMEs, freelancers, and businesses generate, review, understand, and manage legal documents and get AI-powered legal guidance. We are building specialized AI capabilities for Indian legal use cases to make legal assistance faster, more affordable, and accessible. Legal services are often expensive, time-consuming, and difficult to access for startups, MSMEs, freelancers, and individuals. Businesses frequently struggle with drafting agreements, reviewing contracts, understanding legal clauses, and identifying potential risks. Existing AI tools are often generic and may not be sufficiently adapted to Indian legal workflows. Vidhik AI addresses this accessibility, affordability, and efficiency gap. Vidhik AI provides an integrated AI-powered legal platform where users can generate legal documents, review contracts, ask legal questions, understand complex legal language, and securely manage their documents. Our platform combines AI-assisted document generation and review with a legal AI assistant and access to verified human lawyers when professional consultation is required. We are also planning a domain-specific Small Language Model (SLM) focused on legal use cases to improve accuracy, cost efficiency, and performance for Indian legal workflows. Our differentiation comes from combining multiple legal workflows into a single platform rather than offering only document generation or a generic AI chatbot. We are building specialized legal workflows, structured legal data, domain-specific evaluation processes, and user feedback loops around Indian legal use cases. MVP Pilots Lawyers, Startups, MSMEs, small and mid-sized businesses, freelancers, corporate teams, HR professionals, and individuals $50B+ $8.2B $320M SaaS Subscriptions, Consultation Revenue and Extra AI Credits Harvey, Spellbook, Genie AI We use a combination of organic content and SEO, LinkedIn and social-media education, startup and MSME communities, partnerships with incubators and business ecosystems, referrals, direct B2B outreach, and product-led acquisition through our freemium model. We also plan to develop partnerships with lawyers, consultants, accountants and other business-service providers who can refer customers to the platform. We follow a product-led, India-first go-to-market strategy. We initially target startups, MSMEs and freelancers with a freemium offering that allows users to experience AI-powered document generation, contract review and legal assistance. We then convert active users into paid subscribers and expand into B2B plans for companies and corporate teams. Customer acquisition will be supported by SEO, educational content, startup ecosystem partnerships, lawyer and professional-service partnerships, and direct enterprise sales. After establishing product-market fit in India, we plan to expand into international markets with localized legal workflows. Our long-term vision is to build a trusted AI-powered legal infrastructure platform that makes legal assistance as accessible and affordable as other digital services. We aim to develop specialized legal AI and Small Language Models (SLMs) capable of understanding and assisting with complex legal workflows, while combining AI with verified human legal professionals when expert intervention is required. We want Vidhik AI to become the go-to legal platform for startups, MSMEs, businesses, professionals, and individuals—helping them draft, review, understand, manage, and act on legal matters efficiently. Starting with India and its diverse legal ecosystem, we plan to expand into other markets through localized legal AI models and workflows, ultimately making reliable legal assistance accessible globally. Private Limited 1,50,000 Yes Access strong technology mentorship, industry connections, business guidance, and the Bengaluru startup ecosystem. During the programme, we aim to strengthen Vidhik AI's product and technology, develop and validate our legal-focused AI/SLM capabilities, acquire early customers and enterprise pilots, and establish repeatable product-market-fit and go-to-market processes. We also want to build strategic partnerships, receive mentorship on scaling and fundraising, and use the Bengaluru ecosystem to connect with technology companies, legal professionals, investors, and potential enterprise customers. Yes We aim to leverage the Bommasandra and Bengaluru ecosystem to connect with MSMEs, manufacturers, startups, and enterprises as potential customers and pilot partners. IIT ACB can support us through industry connections, mentorship, technology partnerships, and access to investors and the wider Bengaluru startup ecosystem. No We plan to use IITACB’s workspace, meeting facilities, high-speed infrastructure, and shared incubation resources for product development, team collaboration, customer meetings, and industry networking. We also aim to leverage the incubator environment for AI/SLM development, mentorship, and building partnerships with startups and enterprises. Yes Core engine Vidhik AI uses a modular web-based architecture consisting of a frontend application, backend services, database, secure document storage, and an AI integration layer. User requests are processed through our backend, relevant document/context information is prepared, and requests are sent to third-party AI models such as OpenAI through APIs. The AI output is then processed and presented through our application. Our architecture is designed to support multiple AI providers and future integration of our own domain-specific model. Currently, we do not have a large proprietary AI dataset or proprietary trained model. Our data advantage is still being developed through our legal workflows, document structures, user interaction patterns, feedback, and task-specific evaluation data generated through the platform. As the product scales, we plan to build legally permissible and appropriately anonymized datasets that can support future development and evaluation of our own legal AI models. Our current defensibility comes primarily from our product workflows, legal-focused user experience, integration of multiple legal services, domain-specific application logic, and the data and feedback generated through product usage. Our long-term defensibility will come from building proprietary legal datasets, evaluation benchmarks, specialized workflows, and eventually a domain-specific legal AI model. Since we currently use third-party AI models, we evaluate the overall product based on task-level performance rather than claiming ownership of the underlying model. Key metrics include response accuracy, relevance, document-generation quality, clause identification, risk identification, hallucination/error rate, response time, API cost per task, user feedback, and system uptime. We also compare outputs across models and prompts to identify the most suitable approach for specific legal tasks. We follow a privacy and security-focused approach for handling user information and legal documents. We use secure authentication, access controls, encrypted data transmission, secure document storage, and controlled access to user documents. When using third-party AI APIs, we follow the applicable provider terms and data-processing policies and design our system to minimize unnecessary exposure of sensitive information. We also plan to implement stronger privacy, retention, audit, and compliance controls as the platform scales. At 10x scale, the primary challenges would be increased AI API costs, concurrent requests, document-processing workloads, database load, storage requirements, and response latency. We plan to address these through scalable backend infrastructure, caching, asynchronous processing, queue-based workloads, optimized API usage, model selection based on task complexity, and efficient document processing. In the future, our own domain-specific model could also help reduce dependency and inference costs. We currently do not have a dedicated in-house deep-tech or AI research team. Our technical team focuses on product development, software architecture, AI API integration, and product execution. We currently rely on third-party foundation models rather than developing our own models. As part of our technology roadmap, we plan to build an AI/deep-tech team with expertise in NLP, legal AI, model training, fine-tuning, evaluation, and SLM development. We currently use third-party AI APIs, primarily foundation models such as OpenAI, along with standard software frameworks, libraries, databases, cloud infrastructure, and document-processing components under their respective licenses and service terms. Currently, we have a trademark. We plan to improve performance through continuous user feedback, error analysis, prompt optimization, retrieval and context optimization, model comparison, structured evaluation, and human-lawyer validation. We are initially focusing on Indian startups, MSMEs, businesses, and legal workflows because of our understanding of the Indian market and legal requirements. After establishing product-market fit in India, we plan to expand internationally through jurisdiction-specific workflows, localized legal content, and appropriate AI models and integrations for different markets. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/38qBEspNQxSJ-Vidhik_AI_Pitch_Deck.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/38qBEspNQxSJ-Vidhik_AI_Pitch_Deck.pdf NA NA checked
Aug 19, 2026 @ 5:55 PM Hemant Gupta hemant@urbanwild.in https://www.linkedin.com/in/hemant-gupta1989/ http://www.guptahemant.com +91-7763807469 Hemant Gupta – Founder & CEO: IIT Bombay alumnus with 15+ years of experience building and scaling sports and outdoor ecosystems. Former Head – Sports & Adventure Ecosystem at Tata Steel, managing large-scale sports infrastructure, academies, programs and teams. Mountaineer and Everest summiteer with deep expertise in climbing, adventure and outdoor experiences. Akanksha Goyal – Co-founder: Leads brand, community and creative experience design at UrbanWild, with a strong focus on building engaging, accessible outdoor experiences and communities. We are husband and wife and have known each other for several years. UrbanWild is our first venture together. We bring complementary strengths—Hemant leads strategy, outdoor/sports expertise, partnerships and business development, while Akanksha brings creativity, brand and community-building. I would not artificially claim years of “working together” if UrbanWild is genuinely your first professional collaboration. Incubators value straightforward answers. All Our biggest strength is the combination of deep domain expertise and execution capability. We understand the outdoor and climbing ecosystem from the ground up—from infrastructure and safety to training, community and large-scale operations. Having built and managed sports and adventure programs at scale, we know how to turn an outdoor experience into a safe, repeatable and scalable business. This is complemented by strong capabilities in brand, creativity and community building. Urbanwild Bangalore UrbanWild is building India’s next-generation outdoor sports and adventure platform, making climbing and outdoor experiences more accessible through climbing infrastructure, training, communities and curated expeditions. Outdoor sports and adventure in India remain fragmented, inaccessible and largely limited to a small enthusiast community. There is a shortage of quality climbing infrastructure, trained professionals and structured pathways for people to safely discover and progress in outdoor sports. UrbanWild brings the outdoor ecosystem together through modular climbing infrastructure, training programs, community-led experiences and curated expeditions. We are starting with climbing and adventure experiences, while building the technology and operating ecosystem to make participation more accessible, safe and scalable across schools, residential communities, gyms and corporate environments. Our advantage is deep domain expertise combined with execution capability. The founding team brings experience of building and managing large-scale sports and adventure ecosystems, climbing infrastructure, athlete development and outdoor expeditions. We are combining this expertise with modular infrastructure, technology, community and a strong consumer brand—creating an ecosystem rather than a single adventure product. Revenue Revenue, Signups Primary: Urban millennials, Gen Z, families and fitness/outdoor enthusiasts looking for accessible adventure and outdoor experiences. B2B: Schools, residential communities, corporates, hotels/resorts and gyms seeking climbing infrastructure and outdoor programs. 10B USD 2B USD 100M UDS Multiple revenue streams: climbing infrastructure sales/installation, memberships and training programs, curated outdoor experiences and expeditions, corporate/school programs, and outdoor gear & merchandise. Over time, technology and community subscriptions will add recurring revenue. Direct: Climbing gyms and adventure operators across India. Indirect: Trekking/adventure platforms, fitness chains, outdoor camps and recreational experience companies. Our differentiation is building an integrated outdoor ecosystem across infrastructure, experiences, training and community. Community-led growth, founder-led storytelling and content, partnerships with schools, corporates, residential communities, gyms and hotels, referrals, events and curated outdoor experiences. Digital marketing and social media will increasingly scale customer acquisition. Start with Bengaluru as the launch market, using climbing infrastructure and experiences as the entry point. Build a strong local community, validate repeat participation and unit economics, then expand to other major Indian cities through owned, partnered and asset-light models. To make outdoor sports and adventure a mainstream part of everyday life in India. UrbanWild aims to build the largest outdoor participation ecosystem in the country—connecting people to climbing, training, communities and experiences through accessible infrastructure and technology. We envision a network of climbing and outdoor centres across cities, thousands of modular walls in schools and communities, and a strong community of millions of active outdoor participants. Private Limited Company 75 Lacs Yes IIT Alumni is a natural ecosystem for myself as a founder from IIT Bombay and venture built around sports, technology and outdoor experiences. We are looking for mentorship, access to the IIT ecosystem, industry connections and strategic support to build UrbanWild into a scalable outdoor sports platform. We also see strong value in connecting with IIT alumni, technology talent and potential investors. Validate and strengthen our business model, build our first scalable climbing and outdoor experience centres, develop the technology layer, establish strong unit economics and expand our customer and institutional partnerships. We aim to use the programme to move from early validation to a repeatable and scalable business model. yes Bengaluru offers a strong combination of affluent consumers, fitness and sports communities, schools, corporates, technology talent and a large industrial ecosystem. We can use Bengaluru as our pilot market for climbing infrastructure, corporate programmes and outdoor experiences before expanding to other cities. IITACB can help us access relevant industry partners, corporates, technology talent, mentors and investors, enabling us to validate and scale the model faster. Yes We would use the incubator as our Bengaluru base for focused work, mentor and investor meetings, team collaboration and business development. We would particularly value access to meeting spaces, networking with other founders, IIT alumni and industry partners, and the broader IITACB ecosystem for partnerships, technology development and fundraising. Yes Supporting feature Modular climbing hardware integrated with sensors and connected devices, supported by a cloud-based application layer. The planned platform will include user profiles, activity and performance tracking, route management, gamification and analytics. AI/ML APIs can be integrated for personalised recommendations, training insights and route/content recommendations. We are building a proprietary dataset around climbing routes, user performance, progression, engagement and training behaviour. As the network scales across climbing walls and centres, this data can create a feedback loop for personalised training, route recommendations, benchmarking and product optimisation. Our defensibility comes from the combination of domain expertise, physical infrastructure, technology, community and data. Unlike a standalone climbing gym or adventure operator, UrbanWild is building an integrated ecosystem. A growing network of walls and users creates proprietary operational knowledge, community effects and performance data, while our modular infrastructure and technology layer can be continuously improved. Key metrics will include system uptime, sensor accuracy, app response time, route-setting efficiency, data accuracy, user engagement, repeat usage and system reliability across installed locations. For the physical infrastructure, we will also track durability, safety incidents, maintenance requirements and utilisation. We follow a privacy-by-design approach, collecting only data required for the product experience and operations. User consent, secure data storage, access controls and responsible handling of personal information will be built into the platform. For school and youth programs, additional safeguards will be implemented for consent and handling of minors' data. No specific policy dependency at present. Government initiatives promoting sports participation, fitness, youth development and outdoor recreation can support the broader growth of the sector. Key regulatory considerations include safety standards for climbing infrastructure, permissions for installations, insurance and liability, and applicable regulations for outdoor/adventure activities. We plan to work with qualified technical and safety partners and build compliance and risk management into our operations from the beginning. The biggest challenges at 10x will be maintaining consistent safety and service quality, installation and maintenance of physical infrastructure, training qualified personnel, and managing a growing community. We plan to address these through standardised operating procedures, modular infrastructure, technology-enabled monitoring, partner networks and a centralised training and quality framework. Not currently. Our core founding strength is in sports, outdoor experiences, operations and business development. We plan to build the technology team through hiring and strategic partnerships, particularly in IoT, software, data and AI, as the product develops. We are currently at an early stage of technology development and do not rely on proprietary third-party datasets or significant open-source components. The initial technology layer will use standard cloud, software and IoT components, with appropriate licensing. Proprietary datasets will be generated through our own climbing routes, user activity, performance and engagement data as the network scales. We will use user feedback, usage analytics and performance data to continuously improve the product. Key focus areas will include sensor accuracy, system reliability, route management, user experience, personalised recommendations and gamification. As the user base grows, data-driven insights and AI will increasingly support product optimisation. Both. India is our initial market, where we will build and validate the model starting with Bengaluru and then expand to other cities. The modular infrastructure, technology platform and operating model are designed to be adaptable to international markets, particularly emerging outdoor and climbing markets in Asia and other regions. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/DmDlKIGqTDek-Investor-Deck_UrbanWild.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/DmDlKIGqTDek-Investor-Deck_UrbanWild.pdf Yes. UrbanWild aims to make outdoor sports and adventure more accessible, safe and inclusive in India. We want to move outdoor participation beyond a small enthusiast community by bringing climbing and adventure infrastructure into cities, schools, communities and workplaces. Our long-term impact is to create a culture where millions of people can regularly participate in outdoor sports, while creating pathways for youth, athletes and professionals to develop skills and careers in the sector. NA Sunil Bhaskaran NA checked
Aug 19, 2026 @ 5:54 PM Suprabhat Tripathi suprabhattpt@gmail.com http://www.linkedin.com/in/suprabhat-tripathi http://www.idlerobotics.com +91 8000937147 CEO; CTO; CBO, Background in product management and decision analysis ; PhD in cyber physical systems, Consulting Background Met at IIT Kgp, KRSSG. Also part of the same hall. Worked together briefly on different Tech/Social events and in KRSSG 2 Balanced strengths and skills that cover all our bases eliminating major weaknesses. Bodh Robotics Pvt. Ltd. www.idlerobotics.com Bengaluru Spatial intelligence systems for robots Making robots/drones reliable in real world environments We have build a Visual-Inertial based positioning system that allows drones to navigate in GPS denied environments. It uses live feed from multiple sensors, fuses it using an on board computer, and helps the platform calculate its current location without needing any RF signals. Satellite map based navigation, Multi sensor fusion for reliability, Developed in India (Aatmanirbhar) MVP Pilots Drone OEMs 270 150 15 Module sales + Software license Stride Dynamics Outbound, word of mouth, customer inbounds Going for partners with existing sales channels to end users (Military) We want to build plug and play intelligence layer for robots that allows the machine to understand the world around it. The intelligence layer will allow for robots that can perform tasks reliably in the real world. This will convert currently available robots from a fascinating toy to a useful machine. Incorporated 1 Cr Yes Exploring potential Mentorship, Guidance, Incubation Yes Helps us source parts, achieve faster prototypes, collaborate with other startups in the area. Yes Maybe Yes Core engine 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/pbI7GoOT9gQI-pitch_deck_short.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/pbI7GoOT9gQI-pitch_deck_short.pdf https://drive.google.com/file/d/1VOVlCsyg9my4lfLaTuUqKIkJcyFSrSy-/view?usp=sharing Mission Driven : Building useful robots is very hard, and everyone has to reinvent the wheel. We wish to enable the builders to accelerate the robot age. Zaman Khan checked
Aug 19, 2026 @ 4:10 PM Mr. Vivek Maurya vivek.m@omnifyxbharat.com https://www.linkedin.com/in/vivek-maurya-founder/ http://www.omnifyxbharat.com +91 76663 87134 Vivek Maurya - Founder and CEO Our founding member, Anand Kumar, and I were introduced through a mutual friend — my close friend Mohan, who has known Anand as a childhood friend from class 6. Mohan vouched strongly for him as a genuine, hardworking, and long-term-committed person, and recommended I bring him on board. When Anand and I met, he learned about the work I was doing and the product I was building, and was impressed enough to want to contribute. He shared his thought process and the value he could add — and then, without any expectation, he offered to start helping right away. He supported us for a full month without asking for anything in return. After that month, we spoke about making it official, and given his commitment and the value he brought, we decided to bring him on board. Today, he is our founding member, and we've been building Omnifyx Bharat together since. 2 Our biggest strength is the pairing of deep BFSI domain insight with proven large-scale delivery experience. I bring nearly 10 years of hands-on experience in the fintech and loan industry, having worked closely with MSME owners and consulted over 1,000+ MSMEs on their lending needs. This gave me a firsthand understanding of the document and compliance pain that banks, NBFCs, and borrowers face daily — and I've converted that insight into filed patents (UDT and UDC, in India and the US) and a working prototype of our consent-and-custody document rails. My founding member, Anand Basutkar, brings 17+ years of IT program and project delivery, having led 20+ projects and cross-functional teams of up to 40 people across banking and other regulated sectors, with PMP, Scrum, and SAFe credentials. Together we combine intimate knowledge of the customer's problem with the discipline to actually build and ship regulated-grade, real-world infrastructure. Omnifyx Bharat Digital Infra Pvt. Ltd. www.omnifyxbharat.com Pune Omnifyx Bharat is building the trust and document infrastructure for India's digital economy — a consent-based rail that lets individuals own and securely share their documents, and lets institutions like banks and NBFCs access them instantly, with consent and full audit trails. India runs on endless document-chasing. Every loan, KYC, or verification means people repeatedly submitting the same documents, and institutions manually collecting, storing, and verifying them — slow, insecure, and non-compliant. There is no trusted, consent-based rail to move documents between people and institutions. We are building UDT (Universal Document Transfer) — a consent-and-custody rail that lets individuals securely own and share their documents, and lets institutions receive them instantly with consent and a full audit trail. When someone shares a document, it's protected end-to-end: AES-256 encryption, time-bound share tokens, owner approval before any download, visible and invisible watermarking to trace misuse, and a tamper-evident, hash-chained evidence trail that records every access. Individuals share once, with consent; institutions get verified documents without the endless back-and-forth of collecting, storing, and checking files manually. UDT is designed to sit alongside Aadhaar, UPI, and Account Aggregator as the missing "document rails" of India's digital infrastructure. Globally, companies like Plaid (consent-based financial data sharing) and DocuSign (trusted document workflows) have proven the value of secure data-and-document rails; in India, players like Leegality and Digio are building document and eSign infrastructure for banks — UDT extends this category into consent-based document ownership and custody for both individuals and institutions. Our core technology is complete patent-filed (UDT in India and the US), covering consent artifacts, tamper-evident packaging, and audit trails. We're purpose-built for Indian compliance (DPDP, Account Aggregator, DigiLocker) rather than adapted from generic tools & our design combines deep BFSI domain knowledge with regulated-grade security architecture. The consumer free layer feeds institutional adoption, creating a network effect that's hard to replicate. MVP Users We serve three customer segments, and UDT has to win all three in order- 1.Consumers — individuals who own and share their own documents: salaried employees, students, MSME owners, professionals, freelancers, and citizens. They are our free network layer.- 2.Small Organisations - MSMEs, hospitals, colleges, schools, and coaching institutes that issue documents all day (bonafide letters, salary slips, experience letters) and lose track of them the moment they leave on paper or WhatsApp.- 3. Large Entities — banks, NBFCs, insurers, enterprises, and government bodies that receive and verify documents at scale, and pay for every document twice — once to collect, once to verify. $150 Billions $50 Billions $1.5 Billions We earn from three segments, in different ways: Consumers — Free. They can save and share their documents at no cost. Only heavy users pay a small fee for extra storage. Consumers are our network layer, not our income. Small Organisations — They pay a yearly subscription, priced by their size and how many documents they issue. Large Entities (banks, NBFCs, insurers) — They pay a one-time setup fee, then a small fee for every document they receive or verify through UDT. In India: They are all our indirect competitiors, not direct - Perfios, signzy and Digio (eSign and document workflow tools for banks). Globally: Plaid (consent-based data sharing) and DocuSign (document signing). But here's the key difference: most of them only verify documents — you send a number, they check if it's genuine. We don't just verify. With the owner's consent, UDT lets institutions fetch and collect the actual document directly from its issuer (like Aadhaar, PAN, GST, bank statements), and the owner keeps control even after sharing — with full history, consent, and the power to revoke. So we're not a verification tool. We are the document rail — fetch once, share with consent, stay in control forever. That is what makes us different. Top-down, credibility-first. We start with regulated enterprises and BFSI institutions through direct pilots and design partnerships, partner with fintech and compliance platforms, and use regulatory tailwinds (DPDP, Account Aggregator) as a wedge. Trust infrastructure sells top-down. Phase 1- land design partners and pilots in the Indian lending/BFSI ecosystem (our beachhead). Phase 2- expand across banks, NBFCs, and fintechs via API integration. Phase 3- extend into adjacent regulated sectors (insurance, HR, government) & prepare for global markets, where the same document-control problem exists. To become the Trust layer of the digital world — where every individual owns their documents and data, and every institution can access them instantly, with consent and zero friction. Just as UPI became the rail for money, UDT aims to be the missing document rail of India & world digital infrastructure. Our target is Just like we say "Google it" to search, "WhatsApp it" to message, and "Xerox it" to copy — soon, to send a document, The World & you'll say just "UDT it." Incorporated as a Private Limited Company - Omnifyx Bharat Digital Infra Pvt Ltd (CIN: U63111PN2026PTC255527), registered in Pune, May 2026. Our start up is DPIIT-recognised startup. 0000000 Yes We are building deep-tech document infrastructure for India's BFSI ecosystem, and we're at the stage where the right mentorship and investor access matter most. IITACB gives us structured pitch coaching, feedback from experienced mentors, and direct access to VCs and angel investors as we prepare our pre-seed round. The IIT ecosystem's credibility and network in deep-tech and enterprise infrastructure aligns closely with what we're building. We want Three things: (1) sharpen our investor pitch and narrative for a deep-tech infrastructure play; (2) get honest feedback from mentors to strengthen our GTM and fundraising strategy; and (3) connect with investors aligned to our pre-seed round. We also want guidance on landing our first design partner / pilot in BFSI, which is our highest-priority milestone Yes Bangalore has India's biggest cluster of banks, NBFCs, and fintechs — exactly the customers UDT is built for. Being close to this market helps us find early pilot partners. IIT ACB can help by opening doors to these institutions and its investor network & its credibility makes it easier for large BFSI buyers to trust an early-stage startup like us. Yes its depend on you Yes Supporting feature Because of confidentiality we cannot give this information in this form. A few things make us hard to copy: 1. Patent-filed protocol — Our UDT technology is complete patent-filed in India and the US, giving us priority-date protection. 2. Network and data effect — Every document fetched and shared makes our consent-and-custody graph stronger. A person's document history and an organisation's issuance ledger can't be carried over to a competitor, so switching away means losing everything. 3. Infrastructure position — We're not a feature. We're the document rail inside India's digital public infrastructure, alongside Aadhaar, UPI, and Account Aggregator. - In short: patents protect the tech, the network gets stronger with every document, and switching cost keeps customers in so the longer we run, the harder we are to replace. Yes, several policy and regulatory trends directly support us: 1. DPDP Act 2023 & DPDP Rules 2025 — India's new data-protection law makes consent, audit trails, and controlled data sharing mandatory. UDT is built exactly for this — consent travels with every document, with a full record. As enforcement rolls out through 2026–27, demand for our kind of infrastructure grows. 2. Digital Public Infrastructure (DPI) push — The government is actively building India's DPI stack — Aadhaar, UPI, Account Aggregator, DigiLocker. UDT positions itself as the missing "document rail" in this stack, which aligns us with national policy direction. 3. DigiLocker & issuer APIs — Government-backed document issuers (DigiLocker, Aadhaar, PAN, GST, ITR) let us fetch documents directly from the source, with consent. Wider API access is a direct enabler for our product. In short: every new data-protection rule and every step of India's DPI push increases the need for exactly what we're building — a trusted, consent-based document rail. No because we are building our UDT which is align with ISO 27001, SOC 2 Type 2 and CERT-IN so we are following all audit compliance. Currently we don't know. Yes Yes We are building UDT for India and Global both just like WhatsApp and Gmail are build for global. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/wWpvoCjYaNlX-UDT-—-The-Trust-Layer.pdf.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/wWpvoCjYaNlX-UDT-—-The-Trust-Layer.pdf.pdf Yes. This is deeply personal to me. For 10 years I watched ordinary people — MSME owners, borrowers, families — struggle and lose control over their own documents, and I couldn't unsee it. Solving this is my life's mission. Today, documents are the one part of our digital life that stays unorganised. Just like WhatsApp became the rail for communication, UPI for payments, and Google for search, there is still no single trusted rail for documents. This creates two big problems I've seen firsthand. First, once a document is shared, it is not secure and cannot be traced — you lose all control over where it goes. Second, every document lives on a different platform: ITR on the income-tax portal, GST on the GST portal, electricity bills on another site. If you need any document, you have to chase it from a different place every time. Our mission is to fix this — to give every individual one place to own and share every document of their life with consent, and every institution one trusted way to receive it. Just as Amazon organised shopping and UPI organised payments, we want to organise and secure documents for a billion people. That is the impact I am building toward — and I won't stop until it's real. No Dr ARKS Srinivas [ IIM Calcutta alumnus, Startup Coach ] No checked
Aug 19, 2026 @ 2:37 PM K N Shivananja B.E Mech, DCBT (England) G.D.M.M.,M.I.E, F.I.V., C.E., knshivananjaa@gmail.com https://www.linkedin.com/feed/ http://N%20A +91 9448001490 Worked in Various capacity in Production LIne Company like ,M/s BFW, Kirloskar & ABB, Chartered Engineer, Consultant & Goverment Registered Valuer We are Ex Colleagues in M/s ABB INDIA LTD., 2 I AM TECHINICALLY SOUND IN MANUFACTURING ACTIVITIES, Mr Narayana is having very good experience Stores activities like Dispatch, Accounts, Customer follow-up, Imports and Exports in getting advance Licenses with Customs. Keenness Bengaluru, Karnataka I have my own Prime Place in Peenya Industrial Estate with 25HP Power and 51x100 ft and Sheds to start up immediately Bottle Neck of Manufacturing and developing Vendors for the Imports Substitute. I have developed 55 PCB Boards in house development 19 inch Rack as an import substitute with all our Vendor Developments. For the Flight Nickle Cadmium Battery in HAL, we have Developed Battery Analyzer. I have capacity of Developing Import Substitute like Make in India. Idea Signups Depends on the product we get Technical Know how and collobration or Joint Ventures NA NA NA NA NA NA NA What ever the items have demand inside the country and outside the country for export to Manufacture in India. NA NA Yes To know how or Technical Collabration or for Joint Venture To know more about Technicla know how to Start to Manufacture in India and export to other countries. Yes If any one interested to have joint Venuture or an ancillary unit to develop their Product as an import substitute, I am interested Yes By new Vendors Development Program. Yes Core engine 55 PCB, 19 inch Rack and some of the Relay Components, Aluminum Heat Sink and PCB Holding Profile was developed and I am in Specialized in AC, DC Motors and Commutator Manufacturing. In developing Vendors for specialized parts, Plating and Powder Coatings. Technical know how & Manufacturing method to Manufacture. Import substitute and Cost Saving and dependability and Service. Service and Confidence in using our Products. Introducing Cyber Security and Key Passwords for our Processing. Yes, If any one suggest or able to guide, We will take his guideness Yes, it may or may not I will take Guidelines or Support. Yes, I have worked in various field, I will take support from my Ex-Colleagues At presently you have 2. NA By the Customer feed back and what they need or improvements are required. Yes 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/nVncsPg00Bqt-IMG_20260819_142903.jpg, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/LCZGyCpNgNkH-IMG_20260819_1427551.jpg, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/nVncsPg00Bqt-IMG_20260819_142903.jpg, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/LCZGyCpNgNkH-IMG_20260819_1427551.jpg https://www.indiamart.com/kenness-engineering/govt-approved-valuer.html Yes, I have been the First Mechanical Engineer to Appoint in ABB India Ltd., Developed More than 200 to 300 Components, Which we are importing has been developed indigenous. NA NA I am Chartered Engineer and Valuer for Plant & Maachinery Empanneled with SBI, PNB, UBI and Canara Bank for their New Projects Appproval and Sized Units Valuation work . checked
Aug 18, 2026 @ 10:01 PM Nitin Goel nitingoel608@gmail.com https://www.linkedin.com/in/nitin-goel-8a51b0115/ +919454271962 CEO I am a solo founder. All High-Velocity Execution: As a full-stack engineer and solo founder, I can design, build, and deploy features rapidly without coordination bottlenecks. Authentic Domain Empathy: My drive stems from firsthand experience navigating modern arranged matchmaking, giving me clear intuition for user trust, safety, and family dynamics. End-to-End Ownership: Complete accountability across engineering, product strategy, and user feedback ensures relentless focus and adaptability. clubRishta https://clubrishta.com/ NCR clubRishta is a modern, trust-first matrimonial platform designed to bring authenticity, seamless onboarding, and high-intent matchmaking to modern Indian singles and families. Legacy matrimonial platforms suffer from fake profiles, unverified credentials, and overwhelming match fatigue caused by generic filtering. We solve trust and relevance through verified social footprints (LinkedIn/Instagram), strict fraud prevention, and value-based compatibility questions that surface high-intent, meaningful matches. clubRishta is a mobile-first, trust-centric matrimonial platform engineered to streamline arranged matchmaking through rigorous verification and high-relevance curation: Multi-Layered Trust & Verification: We authenticate user identity, professional credentials, and income levels using verified social footprints (LinkedIn, Instagram) and document/income verification to eliminate fake profiles, exaggerated claims, and fraud. Value & Compatibility-Driven Matching: Moving beyond basic biodata and superficial filters, our system uses structured compatibility questions (lifestyle, personal values, and expectations) to connect high-intent singles. Curation Over Fatigue: We replace infinite-scroll directories with curated, high-relevance match feeds, dramatically reducing match fatigue and improving response rates. Seamless, Modern Experience: A frictionless, privacy-focused mobile interface built for both independent professionals and involved families. Our defensibility lies in a high-trust verification moat combined with curation-driven network effects. While legacy platforms monetize low-intent volume and infinite browsing, clubRishta focuses on verified authenticity—validating income, professional credentials, and social footprints (LinkedIn/Instagram) upfront. This creates a scam-free environment with significantly higher response rates, while our proprietary value-based compatibility engine drives superior match quality that compounds retention over time. MVP Signups Primary: Educated, working professionals (aged 24–36) seeking serious, marriage-minded matchmaking with verified identity, career, and income backgrounds. Secondary: Modern, tech-savvy parents and families actively involved in finding trusted, culturally aligned matches without the spam of legacy platforms. $3.5B+ (India & Global Indian Diaspora) | Total addressable user base of ~100M+ active matrimonial seekers across India and overseas diaspora. ~$900M (Internet-savvy, urban & tier-1/2 educated working singles and modern families in India + top NRI corridors). ~$25M–$30M (Capturing 3–5% of verified, premium, high-intent urban professionals over the next 3–5 years). Freemium subscription model (monthly/quarterly plans for direct chat & advanced filters), microtransactions (profile boosts, instant match unlocks), and premium verified concierge/assisted matchmaking tiers. Legacy incumbents (Shaadi.com, Jeevansathi, BharatMatrimony) and modern/niche players (Betterhalf.ai, IITIIMShaadi, Aisle). Organic social content & relationship-focused storytelling (Instagram/YouTube), targeted performance marketing on Meta & Google Ads, community referral loops, and verified professional network outreach (alumni & corporate channels). Phased rollout starting with closed, trusted micro-communities, scaling through organic relationship-driven content on Instagram/YouTube, and expanding across Tier-1/2 urban metros via targeted digital performance campaigns Category Leadership: Become the default, high-trust matchmaking platform for educated Indian professionals and the global diaspora. Deep Tech Integration: Build advanced, value-based compatibility and fraud-detection models to redefine digital matchmaking precision. Ecosystem Expansion: Evolve from a matchmaking app into an integrated relationship lifecycle platform covering pre-marital counseling, event planning, and family networking. In Process / Unregistered (Sole Proprietorship currently; planning Pvt Ltd incorporation upon incubation/funding) None Yes To leverage IITACB’s high-impact alumni and investor network for early-stage capital access and fundraising guidance, while tapping into experienced mentor connects to accelerate our go-to-market strategy, product-market fit, and corporate/alumni distribution channels. Validate product-market fit with early active users, refine our monetization funnel, achieve initial paid subscription traction, and successfully raise our pre-seed/seed round through IITACB investor demo days. yes Bengaluru and the Bommasandra industrial corridor host India’s densest concentration of educated professionals, tech talent, and corporate enterprises—our exact primary target demographic. We will leverage this market to drive concentrated user acquisition through corporate outreach, workplace communities, and alumni networks. IITACB can facilitate direct introductions to enterprise networks, provide strategic mentorship on scaling local density, and connect us with regional angel/VC investors to fuel expansion across Bengaluru’s tech ecosystem. No Not applicable as I am participating virtually; however, if physical access is required later, I will utilize the conference rooms and networking spaces for investor discussions and mentor check-ins. Yes Core engine Our defensibility stems from a strict verification moat and proprietary compatibility data. By enforcing multi-layered identity, income, and social credential verification, we eliminate fraud and build an exclusive, high-trust network. Additionally, our value-based compatibility engine captures deep lifestyle and family alignment data, creating high-intent matching algorithms and organic network effects that legacy directory platforms cannot easily replicate without breaking their volume-based ad models. Unlike legacy platforms built on aging, resource-heavy monolithic stacks, we leverage a high-performance Rust backend to deliver sub-50ms p99 query latencies, zero garbage collection pauses, and superior concurrent throughput. We measure performance using standard reliability metrics: p95/p99 API response times, 99.9% service uptime, error rate under 0.01%, and server resource utilization per active user session—ensuring ultra-fast matching, real-time messaging, and high fault tolerance at a fraction of legacy operational costs. We prioritize privacy and security by adhering to India's DPDP Act and modern data-protection standards. All sensitive personal identifiable information (PII), verification documents, and chat records are encrypted at rest (AES-256) and in transit (TLS 1.3). We implement zero-knowledge verification pipelines where sensitive documents are validated securely without public exposure, combined with granular user privacy controls (visibility toggles, contact blurring, screenshot protection) and strict role-based access control to prevent unauthorized data access or scraping. At 10x scale, the primary bottlenecks would be database query contention under heavy concurrent matching, third-party verification API rate limits (document/social lookups), and real-time WebSocket connection density for chat. We have architected our roadmap to mitigate these by introducing Redis caching layers and read replicas, offloading third-party verification to asynchronous worker queues, and transitioning matching logic to distributed pre-computed vector embeddings. Yes. As a solo technical founder and IIT alumnus with 9+ years of experience designing, architecting, and building large-scale distributed systems from scratch, our deep-tech engineering is managed completely in-house. Core expertise spans high-performance systems programming (Rust), distributed microservices, scalable database design, real-time event-driven architectures (Kafka/Redis), asynchronous data pipelines, and machine learning/vector-based matching algorithms. We maintain a continuous feedback loop driven by real-time telemetry (p95/p99 latency tracking, memory profiling, error rate monitoring) to catch performance regressions early. As user activity scales, we will continuously optimize our Rust backend with load-testing benchmarks, fine-tune our compatibility and vector-matching models based on conversion/response signals, and offload read-heavy workloads to distributed Redis caching layers and edge CDN nodes to ensure sub-50ms query response times. We are building for both. Our immediate go-to-market focuses on urban Indian professionals and tier-1/2 metropolitan hubs to establish strong local density and product-market fit. Simultaneously, our platform is architected to serve the high-intent global Indian diaspora (US, UK, Canada, UAE, and Singapore), where the demand for verified, trust-first matchmaking and cross-border compatibility is exceptionally high, yielding higher ARPU. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/PWBj91Yho3Zq-clubRishta-Pitch-Deck.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/PWBj91Yho3Zq-clubRishta-Pitch-Deck.pdf Yes. Our mission is to eliminate rampant fraud, identity spoofing, and financial vulnerability in modern digital matchmaking by establishing a zero-trust, privacy-first matrimonial ecosystem. Marriage is one of the most critical socio-economic life decisions in India, yet millions face emotional distress and scams on legacy platforms. By enforcing rigorous identity and income verification while prioritizing deep value-based compatibility over superficial catalogs, we are creating a safer, transparent, and dignified matchmaking space for young professionals and families. NA NA NA checked
Aug 18, 2026 @ 4:45 PM Dimple Shah dimple@converso.life https://www.linkedin.com/in/dimplenshah/ +919558819097 Seasoned business leader with 20+ years of experience in finance, operations, governance, and organizational management. Proven track record in building scalable processes, driving business execution, and enabling sustainable growth. As Co-Founder of Converso, leads strategy, finance, operations, and organizational growth, complementing the technical founding team in building a sustainable global Introduced by Jaidev Shah. Since Nov 2025 1 Ashna is based out of San Francisco and active member of startup ecosystem, she participates IN NUMBER OF hackathons, and the broader AI community, which aligns well with Converso’s initial target customer base. Many startups need to conduct market research, making Converso a valuable solution for them. In India, we have the majority of our engineering team and are actively exploring enterprise use cases across sectors such as manufacturing, universities, and other organizations. This combination gives us strong technical execution capabilities in India while leveraging strategic market access and early customer opportunities in the San Francisco ecosystem. Converso https://converso.life/ Ahmedabad Converso is an AI-powered voice interview platform that helps businesses conduct interviews at scale. It uses AI and GenAI to conduct natural conversations and understand respondent feedback. The platform automatically generates transcripts, summaries, and actionable insights. Converso helps businesses move beyond traditional surveys and understand the deeper “why” behind responses. Traditional surveys and manual interviews are time-consuming and difficult to scale. Surveys often capture what people say but fail to uncover the deeper reasons behind their answers. Manual interviews require significant effort for scheduling, conducting, transcribing, and analyzing conversations. Converso solves this by making qualitative interviews faster, scalable, and more insightful. Converso uses AI to conduct natural voice interviews with customers, employees, prospects, and other stakeholders. The AI can ask intelligent follow-up questions based on each person's responses. After the interview, it automatically generates transcripts, summaries, and AI-powered insights. This enables businesses to collect deeper feedback and understand conversations at scale. Converso combines voice-based AI interviews, adaptive conversations, intelligent follow-ups, and automated analysis in one platform.Unlike traditional surveys, the AI can explore responses and ask relevant questions to uncover deeper insights.It transforms conversations into structured transcripts, summaries, and actionable intelligence. This combination helps businesses move from simply collecting answers to truly understanding their customers and stakeholders. Users Users Anyone with customers (could be students for the college) who needs data from effective market research, and gain insights/feedback i.e Manufacturers, FMGC, Colleges, Lawyers, Doctors/Hospitals Our target customers include businesses, researchers, hospitals, startups, marketers, product teams, educators, and organizations. Converso helps them understand people through real conversations instead of traditional surveys Our estimated global TAM is ₹13,000+ crore, covering qualitative research, AI interviews, customer feedback, and research technology. This represents the broader opportunity for AI-powered research and conversational insights globally. Our estimated SAM is ₹2,600–₹4,350 crore, focused on organizations actively using interviews, qualitative research, and customer feedback. We will initially target customers who already use research and feedback tools and can benefit from AI-powered conversations. Our target SOM is ₹43–₹130 crore ARR within 3–5 years. We plan to start in India with researchers, SMBs, and product teams before expanding into larger organizations and global markets Converso follows a subscription + usage-based model, where customers pay according to their plan and interview usage. We will offer flexible plans for individuals, teams, and enterprises, with additional usage-based credits. Who are your main competitors? Our main competitors include Listen Labs, Outset, Conveo, Voxpopme, Strella, GetWhy, UserTesting, Maze, and Qualtrics. Converso differentiates itself through AI voice interviews, intelligent follow-ups, and automated insights in one platform. Our main competitors include Listen Labs, Outset, Conveo, Voxpopme, Strella, GetWhy, UserTesting, Maze, and Qualtrics. Converso differentiates itself through AI voice interviews, intelligent follow-ups, and automated insights in one platform We acquire customers through direct outreach, LinkedIn, email, product demos, trials, referrals, and partnerships. We also use content and collaborations with researchers and organizations to build awareness and adoption. We will initially target researchers, SMBs, marketers, and teams that regularly conduct interviews or collect feedback. After proving value in India, we plan to expand into larger organizations and international markets. Our vision is to make AI-powered conversations a simpler and more human way to understand people. Converso aims to help organizations move beyond forms and surveys toward meaningful, scalable conversations and actionable insights. NA NA Yes Brand of IIM bangalore and local ecosystem of Bangalore Access to wider client base, connections with broader ecosystem of other startups, where we can be integral part of their success stories YES Scale this startup with infrastructure, high level mentorship and networking support No NA Yes Core engine 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/bLnKbtEfwjBa-Converso_Platform_Deck_v3.pptx, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/bLnKbtEfwjBa-Converso_Platform_Deck_v3.pptx https://youtu.be/pgKiRPGS6OQ?si=H2MCCWMmOkPJDrAT NA NA checked
Aug 18, 2026 @ 4:30 PM Altamash M altamesh.k@gmail.com https://www.linkedin.com/in/altamash-m +91 7411521619 Altamash - sales Co founder Rajeev Kumar - tech cofounder We met through YC cofounder connect. And it’s been more than 2 years we know each other working together from 1.5 years. 2 Deep enterprise sales experience combined with strong AI and technology execution—turning complex problems into revenue-generating products. Ohuru https://ohuru.xyz/ Bangalore Ohuru is an AI Revenue OS that turns company knowledge into intelligent agents that drive growth. We solve revenue leakage and slow sales execution by turning a company’s scattered knowledge into an AI Brain that helps every rep execute like the best. Ohuru gives every revenue team a private AI Brain, a workforce of specialized agents, and an Agent Marketplace to scale execution without scaling headcount. Ohuru combines a private company Brain with 3,000+ specialized sales agents, giving teams a continuously learning AI workforce that understands their unique data, processes, and customers—and gets harder to replicate with every interaction. MVP Pilots Mid-market and enterprise B2B companies with 100–5,000+ employees, starting with revenue teams—CROs, VP Sales, RevOps and Sales Enablement leaders. $50B+ — AI sales, revenue intelligence, sales engagement and workflow automation market opportunity. $10B+ — Mid-market and enterprise B2B revenue teams where AI agents can automate sales execution $100M — Initial target across 500–1,000 high-fit companies in the US, GCC and India. Annual SaaS subscription based on platform usage, number of users/agents, with premium pricing for enterprise deployments and private environments. Salesforce Agentforce, Microsoft Copilot, Gong, Clari, Outreach, 11x and emerging AI sales-agent platforms. Founder-led enterprise sales, targeted outbound, design partners, strategic partnerships and the Agent Marketplace as a distribution channel Start with a high-value revenue use case—pipeline coverage and revenue leakage—land with one team, prove measurable ROI, then expand across the organization through additional AI agents. To become the AI Operating System for enterprises—where every company has its own private Brain and thousands of specialized AI agents working across the organization. Pvt ltd 0 Yes We are applying to IITACB to accelerate Ohuru from product validation to enterprise scale by accessing strong industry networks, enterprise design partners, mentors, investors, and IIT’s technology ecosystem. Bangalore’s enterprise and technology ecosystem also gives us an ideal market to validate and scale our AI Operating System. Validate Ohuru with enterprise customers, secure 3–5 design partners, refine our GTM and pricing, build strategic partnerships, and prepare for our next funding round. Yes Bangalore gives us access to a dense ecosystem of enterprises, technology companies and talent. We want to use IITACB’s industry network to secure enterprise design partners, run pilots and build strategic relationships. IITACB can accelerate us through mentorship, customer introductions, investor access and technical ecosystem support. Yes We would use the infrastructure as our Bangalore base for customer meetings, enterprise pilots, product demonstrations, team collaboration and partner/investor meetings. We also want to leverage IITACB’s ecosystem to connect with technical talent, enterprises and strategic partners as we scale Ohuru. Yes Core engine Ohuru uses a modular, cloud-native AI architecture built around LLMs, RAG, a knowledge graph/memory layer, and multi-agent orchestration. The stack includes Python/FastAPI for backend services, PostgreSQL/vector storage, Redis, REST APIs/webhooks for integrations, and Docker/Kubernetes on AWS. We use model-agnostic LLM APIs (e.g., OpenAI/Anthropic) with routing based on task, cost and performance. A secure orchestration layer connects the company Brain to 3,000+ specialized agents and enterprise systems such as CRM, email, Slack and Teams. Our primary advantage is customer-specific organizational context, not a proprietary foundation model. Ohuru builds a private knowledge graph/memory from each customer’s data, workflows, historical interactions and outcomes. Over time, this creates a highly personalized intelligence layer that improves relevance and execution. Our defensibility comes from the combination of private company Brain + agent orchestration + 3,000+ specialized sales agents + proprietary customer context. As the system learns each organization’s workflows and outcomes, switching becomes harder and the system becomes increasingly personalized. We measure: * Agent task completion rate * Accuracy/relevance of retrieved information * Hallucination/error rate * Tool-call success rate * Response latency * Human approval/rejection rate * Automation rate * Uptime and failure recovery * Business outcomes such as pipeline coverage, sales productivity and revenue recovered. We benchmark these against existing manual workflows and relevant AI/agent platforms rather than relying only on model benchmarks. Ohuru follows a security-by-design architecture, including encryption in transit and at rest, tenant-level data isolation, role-based access controls, least-privilege access, audit logging and controlled agent permissions. Customer data is logically isolated and is not exposed across organizations. For enterprise deployments, we support private/self-hosted environments where required. We are building toward relevant enterprise security and compliance certifications as we scale. India’s growing focus on AI adoption, digital transformation, data security and enterprise technology supports our market. Government and institutional programs supporting AI startups, enterprise digitization and deep-tech innovation can also accelerate adoption. Yes. Key risks include evolving data-protection, AI governance, cross-border data transfer and sector-specific regulations. We mitigate these through consent-aware data access, tenant isolation, configurable retention, auditability, human approval for sensitive actions and deployment options aligned with customer requirements. The biggest challenges would be data ingestion volume, agent orchestration, inference cost, third-party API limits and observability. We are designing for horizontal scaling using containerized services, asynchronous processing, caching, model routing and queue-based workloads so individual components can scale independently. Yes. Our founding team combines 15+ years of technology experience and 15+ years of enterprise sales/marketing experience. The technical team focuses on AI/LLM applications, RAG, knowledge graphs/memory, agent orchestration, integrations, cloud infrastructure and enterprise security. We use a combination of customer-authorized enterprise data, public/licensed datasets and open-source components, alongside commercial APIs/models where appropriate. We do not claim ownership of third-party foundation models or open-source components; our IP is primarily in the product architecture, orchestration, agent workflows, proprietary prompts/logic, integrations and customer-specific intelligence layer. All third-party components are used subject to their applicable licenses. We continuously evaluate agents using production feedback, automated evaluations and human feedback. We improve retrieval quality, agent planning, tool selection, prompts, workflows and model routing, while monitoring latency, accuracy, cost and task completion. Customer outcomes feed back into the system without exposing one customer’s confidential data to another. Both. We are building Ohuru as a global enterprise AI platform, with India as an important product-development and talent hub and the US, GCC/MENA and other global markets as key commercial markets. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/G1me9CmTdbfd-Ohuru-PitchDeck-v3.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/G1me9CmTdbfd-Ohuru-PitchDeck-v3.pdf Yes. Ohuru’s mission is to make enterprise AI accessible to lean teams—not just large companies with massive headcount. We aim to help organizations eliminate revenue leakage, reduce repetitive work, and give every employee access to an AI workforce that amplifies their capabilities. NA Nikhil Kumar - IIT Bombay We are building Ohuru from India for the global enterprise market, with the vision of creating an AI Operating System where every company has its own private Brain and access to thousands of specialized AI agents. We are looking to leverage IITACB for enterprise validation, strategic partnerships, mentorship and investor access checked
Aug 18, 2026 @ 12:42 PM Col KS Jayandhan(Retd) ceo@ostera.ai https://www.linkedin.com/in/jayandhan-shridharan/ https://mission.ostera.ai/home +91 9428728709 Col KS Jayandhan (Retd) Founder & CEO Defence veteran with over 30 years of service. Recipient of Army Chief Citation. Experience in leadership, training, psychological assessment, and organizational systems. Alumni of IIM Lucknow. Full-time entrepreneur and AI enthusiast. Prajwal Prabhalash Co-Founder & CTO B.Tech in Computer Science Engineering. Experience as DevOps Engineer with scalable application deployments, including Kerala Government projects. Expertise in AI orchestration and leading cross-functional technical teams. Full-time entrepreneur. We are relatives and have known each other closely for many years. Because of this long-standing personal connection, we understand each other’s strengths and weaknesses well and complement one another effectively as a team. This strong foundation of trust and mutual understanding has helped us work together seamlessly on building Mission Control. 2 1. Never Giving Up Attitude 2. Work Relentlessly 3. Same Vision Ostera AI https://ostera.ai/ Bangalore Ostera AI is building Mission Control, an AI-powered platform that brings project management, personal tasks, and team communication (text, audio, and video) into one simple system. It helps startups and growing teams stop switching between multiple tools, stay aligned, and execute work with greater clarity and speed. We are solving the problem of fragmented work. Teams use multiple tools for tasks, chat, notes, and meetings, which creates confusion, lost decisions, and wasted time. Most existing solutions are complex and hard to adopt. Mission Control brings everything into one simple system so teams can stay aligned and execute faster. Mission Control is an AI-powered platform that unifies Project Management, Personal Management, Communications, Meetings, and Notes into one simple, connected system. Most growing teams struggle because these essential functions live in separate tools. Projects are managed in one app, personal tasks in another, conversations and meetings happen across different platforms, and notes are scattered elsewhere. This fragmentation creates confusion, lost context, and slower execution. Mission Control solves this by bringing everything together: Project Management – Set goals, break them into tasks, track progress, and keep the entire team aligned. Personal Management – Allow every individual to manage their own tasks, priorities, and responsibilities without losing connection to team goals. Communications – Collaborate through fully inbuilt text chat, audio, and video calling. Meetings – Conduct discussions and video meetings directly within the platform, keeping conversations linked to projects and tasks. Notes – Capture ideas, meeting points, and decisions in the same place, ensuring important information is never lost. Because everything operates within one system, teams no longer need to switch between multiple tools. The result is clearer ownership, faster decision-making, and significantly better execution. Mission Control is built for startups and growing organizations that want simplicity, speed, and alignment — without the complexity of traditional platforms. Most tools are built as separate products that are later connected through integrations. Mission Control is designed from the ground up as one unified system, where projects, personal tasks, meetings, communication, and notes share the same data and workflow layer. This creates three real barriers for competitors: Architectural depth – Rebuilding a truly native system (not stitched integrations) takes significant time and engineering effort. Simplicity discipline – Most companies keep adding features. Maintaining extreme simplicity while staying powerful is difficult to copy culturally and product-wise. Usage behavior – Once teams start working inside one connected system, switching away becomes harder because their goals, tasks, conversations, and decisions are already linked together. Users Pilots Our target customers are startups and mid-sized organizations (typically 10–200 employees). We focus on digitally active growing teams that are frustrated with using multiple disconnected tools for projects, tasks, communication, and meetings, and are looking for a simple, all-in-one platform to improve clarity and execution. $50–70 Billion $8–12 Billion $50–100 Million ARR Mission Control follows a freemium B2B subscription model. Organizations can start on a Free plan They upgrade to paid plans as they grow: Standard – ₹580 per user / month Premium – ₹699 per user / month Revenue is generated through recurring monthly subscriptions paid by the organization, and individual users. Our main competitors are traditional project management and collaboration tools such as: Asana Jira Monday.com ClickUp Combination of Slack + Zoom + Notion We acquire customers primarily through a high-touch pilot-led approach. We start by offering free or premium access to startups through institutional partners like TECHIN IIT Palakkad and IIT Madras RTBI. Once teams experience the product and see value, we convert them into paying customers. We also expand through institutional partnerships and direct outreach to mid-sized organizations looking for simpler work management solutions. Our GTM is built around high touch pilots and institutional partnerships. We start by onboarding startups through incubators such as TECHIN IIT Palakkad and IIT Madras RTBI, offering free or premium access. Once teams experience real value, we convert them into paying customers. From there, we expand through institutional partnerships and targeted outreach to mid-sized organizations, focusing on building a repeatable process for customer acquisition and conversion. Our long-term vision is to make Mission Control the default work operating system for growing teams. We aim to become the simple, AI-powered platform that startups and mid-sized organizations rely on to plan, collaborate, communicate, and execute — without the complexity of multiple tools. Over time, we want to expand across India and global markets, helping teams work with greater clarity, speed, and alignment. Ostera AI Private Limited is an active Private Limited Company. CIN: U47413KA2025PTC209721 Incorporation Date: 14th October 2025 Status: Active Registered in: Karnataka (RoC-Bangalore) NA Yes We are applying to IITACB Incubator to strengthen our next phase of growth. Mission Control is already live with early institutional pilots, including TECHIN IIT Palakkad. At this stage, we need structured support, mentorship, and ecosystem access to convert pilots into paying customers and refine our go-to-market strategy. IITACB’s strong technology and startup ecosystem will help us improve product maturity, gain relevant industry connections, and accelerate our path from early traction to sustainable revenue. During the programme, we want to: Strengthen product-market fit through deeper user feedback and product improvements. Convert early pilots into paying customers and achieve initial revenue. Build a clear and repeatable go-to-market process. Expand from current pilots to a stronger base of active organizations. Gain mentorship and strategic guidance to scale effectively beyond the early stage. Our goal is to move from early traction to a more stable and growth-ready stage during the programme. Yes, we are open to virtual participation. The Bommasandra industrial hub and Bangalore market have many growing companies that struggle with managing work across multiple tools. These teams need something simple to plan, communicate, and execute better. Mission Control fits this need well. We can start by working with mid-sized companies in this region, learning from real usage, and then expanding further in Bangalore. IIT ACB can help us by connecting us to the right companies, providing mentorship, and giving us the credibility needed to convert early users into paying customers faster. Yes If we rent seats at IITACB, we will use the infrastructure for focused product work, team collaboration, and client meetings. Having a proper workspace in Bangalore will also help us hire local talent, conduct interviews, and build our team more effectively. In addition, we will use the facilities for demos, discussions, and regular coordination while staying closely connected with the incubator’s mentorship and support system. Yes Other: We have filed an IPR application for “DECENTRALIZED OFFLINE AI SYSTEM AND METHODS THEREOF” (Application No. 202641034020). Next Js , NLP, AWS(S3 , EC2, Transcribe),Postgre SQL, High-efficiency on-device inference optimisation Mission Control is defensible because everything is built-in and works together natively: Project Management, Personal Management, Communications, Meetings, and Notes. Most competitors rely on separate tools or external integrations for chat and video. In Mission Control, all these functions are fully built-in and connected within one system. This creates a seamless workflow where teams plan, communicate, and execute without switching tools. Features can be copied, but building a truly unified system where everything works together from the ground up is much harder to replicate. How we evaluate technology performance & reliability: We evaluate Mission Control on both performance and reliability, while staying true to our core principle: Keep it Super Simple. Key metrics we focus on: - System response time: Speed of loading tasks, projects, and communication modules - Uptime / Availability: Platform stability and consistent accessibility - Video call quality & latency: Performance of inbuilt audio/video communication - Context switching time: Time saved by keeping projects, tasks, meetings, and notes in one system - User adoption & engagement: How easily and consistently teams use the platform daily - Error rate / Stability: Frequency of bugs, crashes, or failed actions Unlike competitors that add complexity through multiple tools and integrations, we measure success by how simple, fast, and reliable the experience remains for users. Our goal is not just strong technical performance, but a system that teams can use easily every day without friction. We take data privacy and security seriously as Mission Control handles team communication, tasks, and work data. Our approach includes: Secure access controls and role-based permissions so only authorized users can view relevant information Data protection practices aligned with standard industry guidelines Hosting with trusted cloud providers, supported by AWS and Google Cloud credits through IIT Madras Continuous monitoring of system access and activity Focus on keeping the platform simple, which also reduces unnecessary data exposure risks As we scale, we will continue strengthening compliance and security measures to meet the needs of growing organizations and institutional clients. NO No At 10x scale, the primary pressure points in our system will be the real-time communication layer (inbuilt video, audio, and messaging), database performance due to the tightly connected nature of projects, tasks, notes, and conversations, and the notification system handling high volumes of updates. As concurrent users, media usage, and activity increase, these areas will require infrastructure optimization and stronger performance monitoring. We are aware of these scaling challenges and will prioritize strengthening them as usage grows. Yes, we have strong in-house deep-tech capability within our lean team of 3, led by our CTO, Prajwal Prabhalash. His expertise spans: -High-performance distributed system architecture Real-time communication systems -AI orchestration and intelligent workflow automation -Scalable full-stack engineering and DevOps for production environments We primarily use standard open-source technologies and cloud infrastructure components to build Mission Control. These include commonly used open-source frameworks and libraries for backend systems, frontend interfaces, and real-time communication features, all under standard open-source licenses (such as MIT, Apache, etc.). We do not currently rely on proprietary third-party datasets. The platform is built using our own application logic and system architecture. Regarding IP: We have filed an IPR application for “DECENTRALIZED OFFLINE AI SYSTEM AND METHODS THEREOF” (Application No. 202641034020). In addition, the core intellectual value of Mission Control lies in our proprietary system design specifically the unified architecture that natively integrates project management, personal management, communications, meetings, and notes into one connected platform. We will improve technology performance through a continuous cycle of measurement, optimization, and user-driven iteration. Both 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/SdtgGqiF0OeI-Hyderabad.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/SdtgGqiF0OeI-Hyderabad.pdf https://mission.ostera.ai/walkthrough Yes, we are building a mission-driven startup. Our mission is to bring clarity and simplicity back into the way teams work. Today, growing teams lose significant time and energy switching between multiple tools for projects, tasks, communication, meetings, and notes. This reduces focus, slows execution, and creates unnecessary complexity. We believe work systems should enable people, not overwhelm them. Mission Control is built on a clear purpose: Help teams execute better by keeping work simple, connected, and visible. By unifying project management, personal management, communications, meetings, and notes into one system, we aim to reduce tool fatigue, improve alignment, and help startups and growing organizations perform with greater focus and efficiency. Our impact lies in enabling teams to spend less time managing work and more time doing meaningful work. NA NA checked
Aug 18, 2026 @ 1:21 AM Deepesh Chaudhari deepesh@blockstash.in https://www.linkedin.com/in/amideepesh/ https://deepeshchaudhari.github.io/ +91-8808682517 Deepesh Chaudhari (Co-Founder & CEO, MTech CSE IIT Kanpur), Aman Tiwari (Co-Founder & CTO, BTech ECE, IIT Kanpur) , Amit Tiwari(Co-Founder & Cheif of AI, MS AI, Liverpool John Moore University, London) We have been working together for the past two years as co-founders, building our company and working closely across technology, AI, and business. Deepesh Chaudhari is the Co-Founder & CEO, with an MTech in Computer Science & Engineering from IIT Kanpur. Aman Tiwari is the Co-Founder & CTO, with a BTech in Electronics & Communication Engineering from IIT Kanpur. Amit Tiwari is the Co-Founder & Chief of AI, with an MS in Artificial Intelligence from Liverpool John Moores University, London. Over the past two years, we have worked closely together on product development, technology, AI, and overall company strategy, building a strong working relationship and complementary expertise. 2 Our biggest strength as a team is the combination of complementary skills and a strong sense of ownership. We bring together expertise in business and leadership, deep technology and engineering, and AI. Over the last three years, we have developed a strong understanding of each other’s strengths and work closely to make fast, informed decisions. This allows us to move from ideas to execution quickly while challenging each other’s thinking and staying focused on building a strong product and company. Blockstash Intelligence Private Limited https://blockstash.in/ Kanpur Blockstash is an AI-first cybersecurity company building the intelligence infrastructure for the digital world. We empower governments and enterprises with blockchain analytics, cyber intelligence, OSINT, threat intelligence, and digital risk management. The digital world is becoming increasingly complex, while governments and enterprises struggle to make sense of fragmented cyber, blockchain, and open-source intelligence. Critical signals are spread across thousands of data sources, making it difficult to identify threats early, connect entities, investigate incidents, and assess digital risk in real time. Blockstash is solving this intelligence gap. We are building an AI-first cybersecurity intelligence infrastructure that unifies blockchain analytics, cyber intelligence, OSINT, threat intelligence, and digital risk management into a single platform. Our goal is to help organizations move from fragmented data and reactive investigations to real-time, AI-driven intelligence and proactive risk management. Blockstash Intelligence offers an integrated crypto forensics and blockchain investigation suite purpose-built for law enforcement, regulators, and compliance teams: Sherlock — the core blockchain analysis engine. Traces on-chain fund flows across wallets and exchanges, clusters addresses, and visualizes transaction paths to support investigations into fraud, money laundering, and other crypto-enabled crime. PocketHunter — a forensic artifact extraction tool for seized hardware (phones, hardware wallets, storage devices). Recovers crypto-relevant evidence such as wallet keys, seed phrases, and transaction history from physical devices during raids or digital forensic exams. Shadow — an OSINT analysis engine that correlates open-source intelligence (social media, forums, marketplaces, darknet sources) with blockchain data to attribute wallet activity to real-world identities and entities. Snyper — an IP protection and threat intelligence product, monitoring for brand/asset infringement and surfacing external threats targeting an organization's digital footprint. Indigenous development — Sherlock, PocketHunter, Shadow, and Snyper are built in-house in India, not resold or white-labeled foreign tools. This matters directly for government/law-enforcement procurement, where data sovereignty and dependence on foreign vendors is a real concern. Integrated cybersecurity environment — all Blockstash applications and services are designed to be compatible with each other, giving users a unified ecosystem rather than disconnected point tools. Evidence, intelligence, and monitoring data flow across Sherlock, PocketHunter, Shadow, and Snyper instead of sitting in silos — a real workflow advantage over competitors offering standalone products that don't talk to one another. Research-backed core IP — the underlying tracing methodology grew out of M.Tech research at IIT Kanpur on tracing malicious actors on the blockchain, with IEEE publications behind it. Revenue Users, Revenue, Pilots Government Department, Law enforcement Agencies and Industries $18–20 billion by 2034 $1.4–2 billion by FY 2029–30 $15–40 million annually within 3–5 years Subscription based Chainalysis, TRM, Elliptic, Maltego Train officers first (SVPNPA, CBI Academy, NIA) — they become internal advocates, Direct outreach to department heads at target agencies, GeM/DPIIT eligibility for formal government procurement, Track record (100+ investigations) as the core sales asset Train → land → expand → scale via nodal agencies. Train officers first to build advocacy (SVPNPA, CBI Academy, NIA) Land via direct outreach to department heads, timed to procurement cycles Expand within accounts by cross-selling Sherlock → PocketHunter → Shadow → Snyper as one integrated environment Scale via nodal bodies to reach state governments efficiently Backed by ISO 27001/DPIIT eligibility (GeM) + channel partnerships Become the indigenous, integrated cybersecurity and crypto-forensics backbone for Indian law enforcement and regulated financial entities — one platform (Sherlock, PocketHunter, Shadow, Snyper) covering tracing, device forensics, OSINT, and threat/IP protection, so agencies never need to stitch together multiple foreign vendors. - Build a self-reinforcing pipeline: trained officers → institutional trust → deeper account penetration - Expand from state/central police to the full regulatory ecosystem (FIU-IND entities, tax enforcement, financial regulators) - Reduce India's dependence on foreign forensics/analytics vendors for sensitive crime and financial-intelligence data - Grow the product suite (Chanakya in development) so the platform, not any single tool, becomes the standard Active 22Lakh Yes Eligible as an IIT Kanpur alumnus — the connection is through IIT alumni status Bengaluru gives access to India's deepest startup/investor ecosystem — useful given ongoing investor discussions and the push into deeptech funding channels Incubator mentorship + IIT-alumni network credibility strengthens positioning for government procurement generally Access to peer IIT-alumni founders and potential technical/business co-founders or advisors Structured programme support to take Chanakya from development to deployable product We're eligible for IITACB as IIT Kanpur alumni, and Bengaluru gives us access to India's deepest startup and investor ecosystem — valuable given our ongoing investor discussions and push into deeptech funding channels. yes We'll pitch Snyper's IP-protection/threat-intelligence capability to Bommasandra's manufacturing and pharma companies as anti-counterfeiting and industrial-espionage protection, with IIT ACB providing the local corporate introductions and investor network to open that door. Yes We'll use dedicated desk/office space for focused product development, plus mentorship, investor connects, and IIT-alumni network access for fundraising and government-procurement support. Yes Core engine Blockstash uses a modern, AI-first, cloud-native architecture designed for high-volume intelligence processing and real-time analysis. AI/ML:We use a combination of proprietary ML models, LLMs, embeddings, entity-resolution models, anomaly detection, graph analytics, and RAG-based pipelines. We use leading foundation models where appropriate and build domain-specific models and intelligence pipelines on top of them. **Backend:** Python is our primary language for AI, data processing, and intelligence pipelines, with FastAPI for high-performance APIs. We also use Node.js/TypeScript where it makes sense for application and service development. **Data & Intelligence Layer:** Our architecture combines PostgreSQL for transactional data, Elasticsearch/OpenSearch for large-scale search and indexing, graph databases/graph processing for entity relationships, and object storage/data lakes for large-scale raw and enriched intelligence data. Redis is used for caching and high-speed data access. **AI Frameworks:** PyTorch, Hugging Face, LangChain/LlamaIndex where appropriate, along with custom ML and data-processing pipelines. **Infrastructure:** We use Docker and Kubernetes for containerization and orchestration, with AWS cloud infrastructure and services such as ECR, S3, and managed databases. Our services are designed as modular, independently scalable components. **APIs & Integrations:** The platform is API-first, with REST APIs and webhooks for integrating with enterprise and government security systems. We integrate with blockchain nodes/indexers, OSINT sources, threat-intelligence feeds, public data sources, and third-party security platforms. The overall stack is designed to support **real-time ingestion → enrichment → entity resolution → AI/graph analysis → threat detection → actionable intelligence**, while remaining scalable and deployable across cloud and enterprise environments. Our proprietary data advantage comes from the intelligence layer we build by continuously collecting, normalizing, enriching, and correlating data across cyber, blockchain, OSINT, and digital infrastructure sources. Rather than relying on a single dataset, Blockstash builds a continuously evolving intelligence graph that connects entities such as domains, IPs, wallets, organizations, identities, infrastructure, and threat indicators. Our systems learn from historical investigations, entity relationships, behavioral patterns, and detection signals to generate higher-quality context around individual indicators. Over time, this creates a compounding data advantage: every new source, investigation, relationship, and detection improves our ability to identify connections, reduce noise, and surface emerging risks. Our proprietary value is therefore not just the raw data, but the enrichment, entity resolution, relationships, historical context, and intelligence models built on top of it. Our defensibility comes from the combination of proprietary intelligence data, an evolving entity graph, AI-driven analysis, and deep domain expertise. Blockstash does not simply aggregate data or provide another cybersecurity dashboard. We continuously normalize, enrich, and correlate cyber, blockchain, OSINT, and threat intelligence to build a connected intelligence layer across digital entities and infrastructure. This creates a compounding advantage as more data, relationships, investigations, and detection signals are processed through the platform. Our product suite Sherlock, Pockethunter, Shadow, and Snyper is built on this shared intelligence infrastructure, allowing capabilities developed for one product to strengthen the others. The combination of proprietary data pipelines, entity resolution, graph-based intelligence, AI models, and accumulated investigation knowledge makes the platform increasingly difficult to replicate. Our deep understanding of real-world cybersecurity and intelligence workflows also allows us to continuously improve the product based on customer requirements and emerging threats. We evaluate Blockstash across **accuracy, speed, coverage, scalability, reliability, and data attribution**, benchmarking our technology against relevant cybersecurity, OSINT, blockchain intelligence, and threat intelligence platforms. Our key metrics include **detection precision/recall, false-positive rates, entity-resolution accuracy, search and investigation latency, time-to-first-result, data-source and entity coverage, ingestion throughput, API latency, uptime, error rates, and MTTR**. For our AI systems, we also measure the relevance and accuracy of generated intelligence, hallucination/error rates, confidence scores, and analyst acceptance. Data attribution is a core part of our architecture. Each intelligence signal maintains its source/provenance, timestamp, collection method, enrichment history, and relationships to other entities. This allows users to trace an insight back to its underlying evidence and understand why the system reached a particular conclusion. We also measure provenance completeness, data freshness, source reliability, attribution accuracy, and traceability of AI-generated insights. This is particularly important for government and enterprise use cases, where intelligence needs to be explainable, auditable, and verifiable. From a reliability standpoint, we use automated testing, monitoring, alerting, load testing, and continuous evaluation of our data and AI pipelines. Our objective is to outperform traditional tools not simply on individual features, but on speed of investigation, intelligence coverage, signal-to-noise ratio, explainability, and reliability at scale. We follow a security-by-design and privacy-by-design approach. Data is encrypted in transit and at rest, with strict RBAC, least-privilege access, secrets management, network isolation, audit logging, monitoring, and regular security testing. We maintain data provenance, access controls, retention policies, and tenant isolation to protect customer and intelligence data. We also design our platform to comply with applicable data-protection and cybersecurity regulations, with compliance and security controls continuously strengthened as we scale. Crypto Exchange compliance , DPDP Compliance and data protection act The key regulatory risks are changes in data privacy, AI governance, cybersecurity, and access to public/open-source data, especially across different jurisdictions. Because Blockstash operates across cyber, blockchain, OSINT, and AI, regulations around data collection, cross-border data transfers, AI usage, and digital assets could affect certain data sources or use cases. We mitigate this through data provenance, privacy-by-design, access controls, configurable data retention, and continuous monitoring of regulatory requirements. At 10x scale, the main challenges would be data ingestion volume, storage, search/query latency, and AI inference costs rather than a fundamental architectural limitation. Our architecture is designed to scale horizontally, so we would primarily need to increase compute, storage, indexing, and queue capacity. We would also optimize caching, database sharding, asynchronous processing, and AI inference pipelines to maintain performance. We continuously load-test these components and monitor throughput, latency, error rates, and infrastructure utilization to identify bottlenecks before they impact customers. yeah, my co-founders as explained earlier. We use a combination of publicly available datasets, licensed third-party data sources, open-source frameworks, and proprietary datasets and intelligence pipelines. Our technology stack uses open-source components such as Python, PyTorch, Hugging Face, FastAPI, PostgreSQL, OpenSearch/Elasticsearch, Redis, Docker, and Kubernetes, subject to their respective open-source licenses. We also use licensed APIs and data feeds where required. Our core differentiation including proprietary data pipelines, data enrichment, entity resolution, intelligence graphs, detection logic, AI/ML pipelines, and product code for Sherlock, Pockethunter, Shadow, and Snyper—is owned by Blockstash. Our proprietary IP is primarily software, data pipelines, models, detection methodologies, and the resulting intelligence datasets. We can provide detailed IP ownership and licensing references as part of technical or due-diligence documentation. We continuously improve performance through automated testing, production monitoring, customer feedback, and ongoing evaluation of our AI and data pipelines. We track key metrics such as accuracy, latency, coverage, false positives, uptime, and inference costs. We are building for both India and global markets. India is an important market for us, particularly across government, enterprises, and cybersecurity use cases, while our AI-first architecture and products are designed to address global cybersecurity and intelligence requirements. We see a significant opportunity globally as organizations increasingly need real-time cyber, blockchain, OSINT, threat, and digital risk intelligence. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/t3Vx6oavdXxO-Blockstash_PitchDeck-1.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/t3Vx6oavdXxO-Blockstash_PitchDeck-1.pdf http://NA Yes. Blockstash is mission-driven, with a focus on making the digital world safer and more trustworthy. We build AI-first cybersecurity and intelligence infrastructure that helps governments and enterprises detect threats, investigate digital crime, manage risk, and protect critical digital ecosystems. Our long-term mission is to make high-quality cyber and digital intelligence more accessible, actionable, and real-time, helping organizations move from reactive security to proactive threat prevention. NA NA checked
Aug 17, 2026 @ 11:59 PM Dhananjay Arya dhananjaysigning@gmail.com http://www.linkedin.com/in/hidhananjayhere +917838364011 Dhananjay is an IITD Alumnus, having worked in technical roles in Startups and Corporates. His skills are in Backend Engineering, Data Science, and Generative AI, and he serves as Technical Partner for this platform. Harish is a veteran Businessperson in Real Estate space, currently delving into Collar B workers mismatch problem at the Industry front, serves as Business partner for this platform. Connected through a common Founder's networking group. 2 The experience level of the founders in respective domains and their complementary skills provides a great founding team setting and solid product vision, plus the age group in team ranges from 18 to 40s that gives a good blend of speed and control. We are a tech savvy team, all willing to wear multiple hats as and when required. PlanCollarBlue New Delhi We provide an AI-based Evaluation platform for Collar Blue applicants to respective Jobs There are millions of blue collar workers in India alone. The hiring is mostly informal, referral-based, with almost no skill verification. So, hiring is slow, referral-dependent, and churn is brutal- often workers leaving within weeks. The solution is a structured, AI-run assessment in the worker's own language(default Hindi in India), that produces a comparable score across candidates for the same trade- based on competence, identity, and reliability-plus feedback from actual placements that keeps updating it. We turn an unverified blue-collar applicant into an objectively scored worker that any employer can trust. This is built on trade-specific assessments, multi-modal evidence, and continuous learning from hiring outcomes. The AI is replaceable. The defensible asset is the assessment framework, outcome data, and employer trust. That’s the differentiation: not another AI interviewer, but a trusted evaluation and verification layer for blue-collar hiring. Idea Large enterprises in Manufacturing, Construction, Logistics, Warehousing, and Caregivers. Separately, there are Large contractors, Gig platforms, and MSMEs in skill heavy trades and last but not the least, staffing agencies for Electricians, Technicians, Machine operators etc,. $1.5 Billion annually across India, Middle East, and SEA markets alone $303 Million annually across India, Middle East, and SEA markets $20.6 Million ARR 2-tiered structure: Gold Offering-> Success fee + modest premium for the platforms; Platinum Offering-> Enterprise licensing There are platforms such as-> Apna, WorkIndia, Vahan, Betterplace, and Mettle Etc. NA. But we propose to acquire the customers in large enterprises by contacting the HR and Ops leaders, and reach out to large contractors through their hiring teams Proposing to start with direct sales to a few large enterprises and large contractors, run pilots with clear ROI metrics, then land and expand. Our North Star is ubiquity. We aim to become the default trust layer for blue collar hiring. Assessment + Verification + Matching. Scalable across domains In Process NA Yes To access the Infrastructure, Mentoring from seasoned entrepreneurs, and Investors connect. Our Objective is to complete the product and transition into business. Initiating GTM processes and customer acquisitions, pilots and onboarding. Sure The hub fits perfectly into our target market with lots of Industry player potentially be using our platform in near future. IIT ACB can provide the required Infrastructure in Build and Test cycles for our product. Yes To access the Infrastructure for build and test cycles for the platform. Yes Core engine ASR, TTS, STT, LLM, GPU Compute, Caching and Storage Layer, State Management, RAG Pipelines, Scalable architecture, Python, FastAPI, JS, Multilingual models inferencing, Finetuning Etc., Already answered earlier. Finetuning on assessments with user consent. Both 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/r0NSzz3Rvv7Q-blue-collar-ai-hiring-deck.pptx, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/r0NSzz3Rvv7Q-blue-collar-ai-hiring-deck.pptx MD Ramaswami checked
Aug 17, 2026 @ 11:49 PM Rishabh Gupta rishabhiitbhu2011@gmail.com https://www.linkedin.com/in/rishabh-gupta1411/ http://NA +919956619654 Sparsh - CEO and having experience in community building and already created 2nd largest community of music jam in bangalore along with this having past experience in product management. ; Rishabh - CTO and worked in IT for 10 years; Saurabh - CPO worked in product design for last 11 years. Sparsh and I(Rishabh) have known each other since 2010, when we were classmates and close friends preparing for engineering entrance exams (IIT-JEE). Since then, whenever either of us wanted to build something of our own, we’ve usually been among the first people to reach out to each other. Sparsh and Saurabh have known each other since 2011, from the first day of college. They were in the same class and hostel, and over the years they have worked on multiple projects together, both during and after college. Through Sparsh, all three of us got to know each other well over time. All three of us have been based in Bangalore for the last 3.5 years, and for the last 6 months we’ve been working very closely together on this project while meeting regularly in person. 2 Our biggest strength is our ability to combine strong product and technology expertise with a deep understanding of what users actually need. We move quickly from an idea to a working product, constantly test it with real users, and iterate based on what we learn. As a team, we complement each other well, bringing together product thinking, engineering, and a strong bias toward execution. This allows us to stay close to our users while building and improving Stance rapidly. Stance https://mystance.space/ Bengaluru Stance is a social debate platform where people share opinions, take sides on topics, and engage with perspectives beyond their own. Social media is creating echo chambers where people mostly see and interact with opinions they already agree with, limiting exposure to diverse perspectives and healthy disagreement. Stance turns social media into a space for healthy debate. Users take a stance on questions and topics, see perspectives from people who disagree with them, and participate in structured conversations. By making opposing viewpoints engaging and accessible, Stance helps people break out of echo chambers and understand perspectives beyond their own. Unlike traditional social platforms that optimize for engagement within existing interests, Stance is built around perspective diversity. Our debate-first format, stance-based interactions, and growing network of opinions create a unique social graph centered on how people think not just who they follow. Over time, this opinion graph and user behavior data become a strong product and network-effect moat. Users Users, Pilots, Signups Our initial target is Gen Z and young millennials who are active on social media, enjoy sharing opinions, and are interested in debates, current affairs, pop culture, and diverse perspectives. We are building for people who want more meaningful interaction than passive scrolling and are curious to understand how others think. ~5.8B global social media users, the broader market for social platforms. ~500M social media users in India, our initial target market. ~5M users in India over the next 3–5 years, representing ~1% of the Indian social-media market. Stance will primarily monetize through native advertising and sponsored debates, allowing brands to engage users around relevant topics without disrupting the experience. As the platform grows, we plan to introduce premium features and subscription-based offerings for power users, communities and debates. Our main competitors are Reddit, X, Instagram, and YouTube, which already facilitate opinion sharing and discussions. Debate-focused platforms do not exist. However, Stance differentiates itself by making structured debate and exposure to opposing perspectives the core social experience, rather than an incidental feature. We will acquire users primarily through organic, community-driven growth leveraging short-form content, viral debates, campus communities, and creator partnerships. We will also use referral loops and shareable debates to turn users into our distribution channel, with paid acquisition becoming more relevant as we identify scalable channels. We started with young, socially active users in India, using debate-driven content to build our initial community. Our GTM combines campus and community-led growth, creator partnerships, short-form social content, and referral loops. We have also launched offline debate events to build communities and create shareable conversations. We are now expanding geographically as engagement and network effects grow. Our vision is to build the global social platform for perspectives where people come not just to consume content, but to understand how others think. We want Stance to become the place where healthy disagreement, debate, and diverse perspectives are a natural and engaging part of everyday social interaction. Stance is currently not incorporated. We are operating as an early-stage startup and plan to incorporate in India as we progress toward our next stage of growth and fundraising. NA Yes We are applying to IITACB to gain access to strong mentorship, a relevant founder network, and an ecosystem that can help us scale Stance. In particular, we see the incubator as an opportunity to sharpen our product and GTM strategy, validate our business model, and connect with mentors, partners, and potential investors who can help us build Stance into a global platform for perspectives. During the programme, we want to validate product-market fit, grow our early user community, and strengthen our GTM and monetization strategy. We also want to leverage IITACB’s mentorship and network to refine Stance’s product, build a scalable growth engine, and prepare for our next stage of fundraising. Yes IIT ACB can help us accelerate this through industry connections, mentorship, market access, and introductions to relevant corporates, institutions, and investors. This would help us validate use cases, build strategic partnerships. Yes We would use IITACB’s workspace as a base for our team to build, test, and grow Stance. Beyond office infrastructure, we would leverage the incubator’s meeting spaces and ecosystem to conduct user interviews, product discussions, community sessions, and meetings with mentors, partners, and potential investors. Being part of the IITACB environment would also give us a collaborative setting to iterate faster and build meaningful connections. Yes Supporting feature Stance runs on a single Flutter codebase for iOS and Android, backed by a Spring Boot (Java) REST API with PostgreSQL. Auth is JWT-based with Apple/Google sign-in. AI is core, not a bolt-on: we use Anthropic Claude to generate debate questions, and AWS Rekognition for image moderation so every debate has substance from day one. Infrastructure is on AWS, with Firebase for push, config, and auth, and Mixpanel for analytics. Every debate captures what most platforms don't: which side a person took, the argument they gave. That builds a first-party dataset of opinions and persuasion on polarizing topics, tagged by side and demographic and our Live Events before/after vote gives rare signal on what actually changes minds. This feature we are planning to add in our app too. Two things compound over time: 1. A data moat competitors can't copy - our debate loop captures opinions, counter-arguments, and mind-changes on polarizing topics; the more debates happen, the better our content and ranking get. 2. Network effects - debates are only good with two active sides, so value grows with the community and makes it costly to leave or replicate. We track a focused set of metrics rather than vanity numbers: 1. Availability / uptime - self-healing infra (auto-restart + OOM guards) keeps the API resilient; target [99.x]%. 2. API latency - p50/p95 response times, with a lightweight cached vote-count endpoint for real-time polling under bursty load. 3. Crash-free sessions & error rate - monitored via Firebase Crashlytics. 4. Load capacity - we run k6 load tests simulating realistic concurrent users and polling behavior before scaling events. 5. Engagement/funnel health - tracked in Mixpanel. Since competitors don't publish internal metrics, we benchmark against our own SLO targets and load-test thresholds, and against the qualitative bar of feeling instant to the user. 1. Secure by default - all traffic over TLS (HTTPS); JWT-based auth; social sign-in via Apple/Google, including support for Apple's Hide My Email (private relay). 2. Data minimization - we collect only what the product needs; no selling of user data. 3. User controls - in-app account deletion, block, and report; users own and can remove their content. 4. Content safety - automated image moderation (AWS Rekognition) plus user reporting to keep debates safe. 5. Compliance posture - aligned with Apple App Store / Google Play data policies and India's DPDP Act; privacy policy and consent flows in place. NA NA 1. Single app instance → the API becomes the ceiling. Fix: horizontal auto-scaling behind a load balancer (already the natural next step on our AWS setup). 2. Polling-based live counts → vote/comment polling multiplies DB reads under load. Fix: extend caching (already started) and move hot counters to Redis / push updates instead of polling. 3. Single PostgreSQL → read load and connection limits bite first. Fix: read replicas + connection pooling. No NA 1. Measure everything —> latency, crash-free rate, and funnel health (Crashlytics + Mixpanel) so decisions are data-driven, not guesswork. 2. Load-test before we grow —> k6 tests ahead of events and launches, so we fix bottlenecks before users feel them. 3. Ship the known scaling steps proactively —> caching, read replicas, auto-scaling, CI/CD on a roadmap, not as firefighting. 4. Tighten the AI loop —> keep improving prompt quality, model tiering, and batching to raise quality while cutting cost/latency. India-first, built to scale globally. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/1ilkcxYxh3kb-Stance-Pitch-Deck.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/1ilkcxYxh3kb-Stance-Pitch-Deck.pdf Yes, Stance exists to fix something broken in how we disagree online. Most social platforms reward outrage and lock people in echo chambers. Stance rewards the opposite: hearing the other side, arguing well, and being willing to change your mind. Our whole loop: take a side, debate it, then vote again is built to make open-mindedness feel good, not weak. The impact we're after is a generation, starting with young Indians and students, that can disagree productively and think critically turning polarization into conversation. That's the mission, and it's also why the product design and the business align: healthier debate is both the good we want and the moat we build. NA NA checked
Aug 17, 2026 @ 11:20 PM Akshatha K akshatha.kesagodu@gmail.com http://LinkedIn/chinmayaka http://NA +91 9410904993 Mrs. Akshatha K (Founder and CEO) Operational Manager Ex. Western Digital Full time for Pragna Energies // Dr Chinmaya K. A (Founder and CTO) Assistant Professor Department of Electrical Engineering, IIT BHU Varanasi // Prof. Sandip Ghosh (Founder and Mentor) Assistant Professor Department of Electrical Engineering IIT BHU Varanasi // Ms. Devananda Thamby (Founder and CMO) B.Tech Student Department of Electrical Engineering, IIT BHU Varanasi // Ms. Niranjana R (Founder and COO) B.Tech Student, Department of Electrical Engineering, IIT BHU Varanasi 1 Our biggest strength is the mix of deep technical expertise and hands-on execution. The team combines strong research and engineering capability with someone fully dedicated to building and running the company day to day - giving us both the technical depth to build genuinely defensible technology and the operational focus to bring it to market. Pragna Energies NA Varanasi We are building an intelligent energy management and peer-to-peer trading platform for rooftop solar households in India. By combining a second-life EV battery storage system with an AI-driven Demand Management and Analysis (DMA) device, we help households store and use solar power more efficiently, sell surplus energy at fairer prices, and reduce their dependence on costly grid electricity while easing the strain distributed solar puts on the grid. Shifting of focus toward bidirectional smart meters has made grid interfaced rooftop solar increasingly common. But this shift has created a lose-lose situation for both the consumers and grid operators. Since the price paid for electricity exported to the grid is far lower than the price paid for electricity imported from it, households investing in solar see minimal financial benefit despite generating their own power. For grid operators, on the other hand, large volumes of unmanaged, intermittent solar being pushed directly into the grid causes voltage regulation issues and reduces grid inertia, threatening stability. There is no intelligent, low-cost local storage or demand-matching layer between the household and the grid. We work out a solution through two integrated components. Second life EV battery storage and a demand management and analysis device. We source used EV batteries(with SoH above 50%), select high-quality cells, and pair them with a proprietary Battery Management System (BMS) purpose-built for the different degradation and cycling behavior of second-life cells. This significantly lowers the cost of storage compared to new batteries. Installed as an add-on to the smart meter, the AI-based Demand and Analysis (DMA) device is set up which continuously learns a household's consumption patterns and charges the battery only to the extent needed to cover that demand. Any additional solar generation is exported to the grid resulting in a smarter, more controlled way rather than an unmanaged real-time dump. On top of the hardware, our core IP is a peer-to-peer DC microgrid energy trading system that lets neighboring households (DCMGs) trade surplus power directly with each other rather than solely with the grid. This uses an asynchronous ADMM (Alternating Direction Method of Multipliers) optimization approach, where each household's system independently computes optimal power exchange and pricing decisions without needing constant synchronized communication with others. The result is a decentralized, privacy-preserving, scalable trading network where consumers can earn better rates for their surplus energy through direct P2P trades, while also reducing strain on the upstream grid. Most residential/ commercial Solar PV are directly grid connected. If there is storage, it uses new battery packs, increasing the overall cost. Our BMS is specifically engineered to manage the irregular degradation, capacity fade, and limited cycling of second-life EV cells which is a technically harder problem, and a real barrier to entry for competitors using off-the-shelf BMS designs. Moreover, the DMA device's charge/discharge decisions are driven by energy management algorithms developed in-house, tuned to real household usage data rather than generic scheduling rules improves both battery lifespan and consumer savings. Moreover, unlike conventional two-stage trading systems, which separate power allocation and pricing into sequential steps, our system jointly optimizes power exchange and pricing in a single phase. This is a patented, technically differentiated approach. Because each DCMG performs local updates independently via asynchronous ADMM, the system doesn't require synchronous communication or a central coordinator making it more scalable, fault-tolerant, and privacy-preserving than centralized or synchronous P2P trading architectures. This is a meaningful technical moat, since most existing P2P energy trading research and products rely on synchronous or centrally-cleared designs. Thus, we simultaneously address the consumer's economic problem and the grid operator's technical problem making the solution attractive to both sides of the market, including potential utility or DISCOM partnerships. MVP Pilots Our target customers are residential and commercial building owners in India who want to become prosumers. Residential households with rooftop solar installations or interested in installing them, who are already using, or are eligible for, bidirectional smart meters under India's ongoing smart metering rollout. Commercial building owners (offices, retail spaces, small industrial units, housing societies or RWAs) with significant rooftop area and daytime electricity demand that aligns well with solar generation making them strong candidates for storage and P2P trading. Every residential and commercial building in India with (or eligible for) rooftop solar + bidirectional smart metering for a full national prosumer opportunity. Near-term base: ~48 lakh (4.8M) households already solar-equipped, plus an estimated 2–3 lakh commercial/industrial rooftop sites. Forward-looking: with rooftop capacity tracking toward 48.55 GW by 2031 and the smart meter base scaling toward 20+ crore connections by 2028, the prosumer-eligible base could realistically reach 1.5–2 crore (15–20M) buildings nationally by 2030. Urban/semi-urban households and commercial buildings in states with (a) active RDSS smart meter rollout, (b) net-metering policy support, and (c) high rooftop solar density. Top states — Gujarat, Maharashtra, Uttar Pradesh, Rajasthan — already account for the majority of cumulative rooftop solar installations, led by Gujarat (24%), Maharashtra (16%), and Uttar Pradesh (9%). Initially if we focus initial go-to-market on 4–6 leading states, SAM could reasonably be 50–65% of national TAM — i.e., roughly 8–13 lakh prosumer households/buildings in the near term (2026–27), scaling with the underlying rooftop solar growth curve. We expect a seed stage SOM of 0.1%–1% of SAM(8 to 13 lakh) within 3 years NA The competitive landscape falls into two categories, each solving only part of the problem. Battery storage providers repurpose retired EV batteries into residential, commercial, and industrial storage products, but stop at hardware — offering no trading network or intelligent demand management. P2P energy trading platforms, mostly blockchain-based, let prosumers trade surplus solar directly with each other and have run promising regulatory pilots in India, but they don't manufacture or manage storage hardware, and rely on synchronous consensus mechanisms rather than a faster, more scalable coordination approach. Our acquisition strategy blends direct outreach with the trust-based channels Indian solar consumers already rely on. Rooftop solar installers (especially those working under PM Surya Ghar) already have direct access to our target customers. We can partner with regional EPC firms to offer our battery and DMA device as a valueadded bundle at point of sale. Since bidirectional smart meter rollout is DISCOM-led, we aim to position ourselves as an approved or recommended vendor in states with active RDSS rollouts, riding the same infrastructure wave. We match our value proposition to PM Surya Ghar messaging, using state-backed subsidies and earnings to ride the wave of public awareness. We go to market through the channels our target customers already trust — partnering with rooftop solar EPC installers to bundle our battery and DMA device at the point of sale, and positioning ourselves as an approved vendor alongside DISCOM-led smart meter rollouts. We focus on tight geographic clusters rather than scattered installations, so early customers can actually trade power with real neighbors and experience the full value of the P2P network from day one. As adoption grows within a cluster, referrals and network effects (better trading rates as more neighbors join) drive further acquisition naturally. To become the operating layer for India's distributed energy economy, turning every rooftop solar owner into an active participant in a local, intelligent, self-balancing energy market, rather than a passive exporter at grid-dictated prices. As a near term goal, we want prosumer households and commercial buildings using second-life battery storage and AI-driven demand management to lower costs and unlock trading income. Further through the journey, dense, interconnected DC microgrid communities across multiple Indian states, can be set up, where our asynchronous P2P trading platform becomes the default infrastructure for local energy exchange. No Invested 5 lakhs and funding required is 50 lakhs. Yes We believe that applying to IITACB Venture will help us in transitioning our project to scalable venture. We believe that the structured mentoring sessions, guidance from the experienced and support can help us achieve our goals. Being part of the incubator will provide the accountability, guidance, and ecosystem needed to build a market-ready solution efficiently. During the programme, we aim to move from a technically validated concept toward a market-ready prototype and pilot deployment.IITACB’s mentorship and industry ecosystem will help us strengthen our business model, regulatory roadmap, IP strategy and fundraising readiness, enabling us to transition efficiently from prototype to scalable venture. Yes The Bommasandra industrial ecosystem can provide us with access to EV, automotive, power-electronics, manufacturing and component companies that are directly relevant to our second-life battery and energy-management solution. We aim to leverage Bengaluru as a testbed for partnerships with EV OEMs, fleet operators, rooftop-solar EPCs, technology providers and potential pilot customers. The broader Bengaluru market can also help us validate our solution with urban prosumers and commercial buildings before expanding to other Indian markets. IITACB can accelerate this process by connecting us with IIT alumni, industry leaders, corporates, researchers, mentors and potential investors. Its industry-academia network can help us identify pilot partners, validate our technology and navigate commercialization, regulatory and fundraising challenges. Yes We intend to use IITACB as our Bengaluru base for product development, industry engagement and pilot preparation. The workspace and maker facilities can support our hardware prototyping, system integration and iterative development of the DMA device and battery-management system. Conference and meeting facilities will help us conduct technical reviews, partner discussions and customer discovery sessions. More importantly, we want to actively leverage IITACB’s network of IIT alumni, faculty, industry experts and mentors for technical validation, business strategy, regulatory guidance and fundraising. We also aim to participate in workshops and networking events to build partnerships across the EV, solar, power-electronics and energy sectors. Our goal is to use the physical infrastructure together with the ecosystem to shorten the path from prototype validation to commercial deployment. Yes Supporting feature The project integrates a two-layer AI optimization architecture, an unsupervised load-prediction model for local demand management, feeding into the ADMM-based decentralized optimization system for P2P trading. The data acquisition layer is the foundation for the model. A solar MPPT charger and data-logger continuously records real-time solar PV generation, battery state, and residential load consumption. This creates a time-series dataset per household (power drawn from battery vs. grid, at what time of day, under what solar generation conditions) which becomes the training input for the learning model. Since there are no labeled "correct" consumption targets (no ground truth for "ideal" household usage), the algorithm is unsupervised, learning consumption patterns directly from the household's own historical load data rather than pre-labeled examples. Architecturally, this can be best described as a time-series pattern recognition or load-profiling model — using techniques to group recurring usage patterns, combined with a forecasting component that continuously updates its prediction of near-term household demand as new data arrives. Using the model's predicted near-term load, the system makes a local dispatch decision of how much power to draw from the battery vs. how much surplus to export to the grid, prioritizing battery use first. Once multiple households are networked, the same demand predictions feed into our asynchronous ADMM optimization system, which decides not just "battery vs. grid" but "battery vs. grid vs. neighbor" — extending the single-household AI prediction into a multi-agent, decentralized optimization problem. We don't have any proprietary data presently. The competitive landscape falls into two categories, each solving only part of the problem. Battery storage providers repurpose retired EV batteries into residential, commercial, and industrial storage products, but stop at hardware — offering no trading network or intelligent demand management. P2P energy trading platforms, mostly blockchain-based, let prosumers trade surplus solar directly with each other and have run promising regulatory pilots in India, but they don't manufacture or manage storage hardware, and rely on synchronous consensus mechanisms rather than a faster, more scalable coordination approach. What makes our solution defensible is that no current player combines all three layers we do, in one integrated system: 1. Second-life battery storage, built on a BMS specifically engineered for the unique degradation and cycling behavior of repurposed EV cells 2. AI-driven demand prediction, continuously learning household consumption patterns to optimize when to store, use, or export power 3. A patented, asynchronous peer-to-peer trading algorithm that lets households trade energy directly and independently, without requiring synchronous coordination or a central clearing mechanism Where existing players specialize in just one of these layers, we've built a vertically integrated stack — meaning a competitor would need to partner across at least two separate companies just to approximate what we offer as a single, cohesive system. This positions us as the only full-stack solution turning a household from a passive solar exporter into a genuinely optimized, trading-ready energy prosumer. Performance: Our asynchronous ADMM trading system lets each household compute decisions independently, avoiding the latency of blockchain consensus used by competing platforms. Jointly optimizing power allocation and pricing in a single phase (vs. competitors' sequential two-stage approach) reduces convergence time. Scalability: Since each node updates locally without synchronized coordination, adding new households doesn't create proportional overhead — unlike blockchain networks, where every new node adds to network-wide verification load. This makes our system better suited to grow into dense, multi-neighborhood trading clusters. Demand-side accuracy: Our AI-based demand management algorithm continuously relearns household consumption patterns rather than relying on static rules, so prediction accuracy should improve over time as usage data accumulates — validated at a component level through our lab-tested MPPT charger and data-logger, which already benchmarks converter and MPPT algorithm efficiency under varying solar conditions. Reliability: With no central coordinator or blockchain ledger, there's no single point of failure — one node's delay doesn't stall the network. Our BMS is purpose-built for second-life EV cell degradation, addressing a reliability gap generic BMS systems (designed for new cells) can miss. Privacy-preserving by design: Local optimization means households never expose raw consumption or trading data to a central party or shared ledger, reducing both privacy risk and attack surface versus blockchain systems where transaction data is more widely visible. Our core trading algorithm (asynchronous ADMM) is inherently privacy-preserving by design: each household's DMA device performs local optimization and only shares the minimum information needed (power availability, price signals) with the network — never raw consumption data, usage patterns, or household-level details with a central party or other participants This is a structural advantage over blockchain-based trading platforms, where transaction data is often more widely visible across the ledger. Data protection law: Household energy consumption data qualifies as personal data under India's Digital Personal Data Protection (DPDP) Act, 2023. We'd need consent-based data collection, purpose limitation (using data only for demand prediction and trading, not resale), and secure storage/deletion policies aligned with DPDP requirements. Electricity sector regulation: P2P trading and grid interfacing require coordination with DISCOMs and state electricity regulatory commissions (SERCs) DISCOMs typically require trading data to integrate with their existing billing/ERP systems, and regulators may mandate specific reporting or audit access. Metering standards: Since we operate alongside bidirectional smart meters, we need to align with CEA (Central Electricity Authority) metering and safety standards, and any BIS certification requirements for our BMS and power electronics hardware. Device-level security: DMA devices and DC-DC converters connect to home networks and grid infrastructure, so they need secure firmware, encrypted communication protocols, and protection against unauthorized access — critical since compromised IoT energy devices can be a grid-stability and safety risk, not just a data risk. Battery safety: Our BMS includes protective monitoring against thermal runaway and overcharging, particularly important given second- life cells' less predictable degradation profiles. Network resilience: Because trading decisions are computed locally rather than through a central server, there's no single point of failure a security breach could exploit to compromise the entire network at once. Net metering / virtual net metering policy reform: Many states still have restrictive net-metering caps or unfavorable buy/sell tariff structures — the exact problem our startup addresses. Advocating for fairer export tariffs or virtual net metering (allowing trading credits across a local network rather than only with the DISCOM) would directly strengthen our value proposition. Second-life battery certification standards: There's currently no standardized certification for second-life EV battery safety/performance in India. A clear BIS or CEA certification pathway specific to second-life storage would reduce the compliance uncertainty and build consumer trust faster. PLI (Production Linked Incentive) extension to storage/BMS manufacturing: Battery storage and ACC (Advanced Chemistry Cell) manufacturing already have PLI support; extending incentives to BMS and second-life battery refurbishment specifically would lower our hardware costs. Green/climate finance access: Priority-sector lending status or green bonds for decentralized clean energy storage startups would ease capital costs for scaling hardware deployment. Extended Producer Responsibility (EPR) alignment for EV batteries: As India's Battery Waste Management Rules mature, favorable EPR credit mechanisms for reuse before recycling (rather than only recycling) would formalize and incentivize the second-life sourcing model our business depends on. Formal recognition of non-blockchain P2P trading mechanisms in SERC regulations: Existing P2P trading sandbox approvals in India are framed around blockchain platforms. We'd advocate for technology-neutral SERC guidelines — evaluating trading systems by outcomes (transparency, auditability, fair settlement) rather than mandating blockchain — enabling our patented optimizationbased trading system to qualify for the same regulatory pathway. 1. P2P trading framework P2P trading currently operates through state-level pilots (UP, Delhi), not yet nationwide law — but both states have already extended and formalized their initial pilots based on positive results, and other states are actively evaluating similar frameworks. Current guidelines are written around blockchain mechanisms; we see this as an opportunity to engage regulators early and advocate for technologyneutral criteria, rather than a blocker. 2. DISCOM alignment DISCOMs control grid interconnection and billing integration, and P2P trading does shift some revenue dynamics for them. That said, DISCOMs also stand to benefit — reduced grid-stability costs, and precedent (like BRPL in Delhi) shows DISCOMs earning revenue through transaction fees rather than losing out. Building this as a partnership, not just a compliance requirement, is central to our DISCOM engagement strategy. 3. Second-life battery certification There's no dedicated BIS/CEA certification standard for second-life EV storage yet — this is a genuine gap, but also a chance to help shape the standard as an early, safety-conscious mover, rather than retrofitting to rules built without our input. 4. Net metering and tariffs State tariff policies evolve periodically. Even in scenarios where export tariffs improve for consumers, our value proposition extends beyond arbitrage — the AI-driven demand optimization and P2P trading income remain relevant regardless of how the base tariff moves. 5. Data protection (DPDP Act) The DPDP Act is still in early implementation, which means compliance requirements are becoming clearer over time rather than shifting unpredictably. Building consent-based, privacy-preserving data handling into our architecture from day one — rather than retrofitting it — positions us ahead of the compliance curve as enforcement matures. 6. Battery Waste Management Rules (EPR) As EPR rules for EV batteries evolve, there's a clear policy trend globally and in India toward favoring reuse before recycling, which aligns directly with our second-life battery model rather than working against it. 1. ADMM trading algorithm — convergence speed Iteration count and coordination overhead grow with network density. Fix: hierarchical clustering (neighborhood-level sub-networks) instead of one flat trading network. 2. Second-life battery supply chain The hardest bottleneck — sourcing, grading, and assembling battery packs at 10x volume doesn't scale like software. Fix: long-term offtake agreements with EV OEMs/fleets, plus in-house refurbishment capacity. 3. Manufacturing and installation capacity Field installation and after-sales service are labor-intensive and quality control gets harder at volume. Fix: standardized installation kits and certified third-party installer partnerships. 4. DISCOM and regulatory bandwidth Current DISCOM integrations are pilot-scale; 10x transaction volume could expose capacity gaps in billing/settlement systems. Fix: early scaling conversations with DISCOMs, phased regulatory milestones. 5. Trust and safety at volume Rare battery safety incidents become statistically more likely at scale, with reputational risk extending beyond one company to the second-life battery category. Fix: rigorous safety/certification protocols scaled ahead of customer growth, not behind it. Yes. We are working on it. No. 202511132501 for EMS used in DMA. No. 202511066685 for converter integrating grid and residential/ commercial load No. 202511058220 for BMS Algorithm refinement: Continuously log real-world consumption, battery, and trading data from deployed systems to retrain the AI demand-prediction model and tune ADMM convergence as network density grows. Hardware iteration: Track second-life battery degradation data to continuously calibrate the BMS, since second-life cells behave less predictably than new ones — this tuning never fully stops. Research partnerships: Maintain ties with the research team behind the patented ADMM system to incorporate ongoing algorithmic improvements (e.g., hierarchical/federated extensions) as the network scales. Review cadence: A recurring (e.g., quarterly) review of prediction accuracy, convergence time, battery health, and safety metrics. Regulatory and DISCOM feedback integration: As pilot programs expand, incorporate DISCOM feedback on billing integration, settlement accuracy, and grid-stability impact into system design — since compliance requirements and real grid behavior will surface issues lab testing can't fully predict. Indian Market 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/VprrQcYcMzHK-Pitch_Deck_Final.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/VprrQcYcMzHK-Pitch_Deck_Final.pdf https://canva.link/n0g3iihyn8wl6b0 Both. Mission (environmental): At the core is a genuine environmental mission, extending the usable life of second-life EV batteries, reducing electronic and chemical waste, and lowering demand for new battery manufacturing (and the mining it requires). This directly supports India's circular economy goals as EV adoption scales. Impact (economic and social): Built on top of that mission is a measurable economic impact, helping households and building owners become genuine prosumers who actually benefit financially from their solar generation. Today's gap between grid electricity cost and solar export earnings leaves most rooftop solar owners without meaningful returns. This product closes that gap, lowering electricity costs and unlocking secondary income through peer-to-peer trading. Yes Centre for Innovation, Incubation and Entrepreneurship (CIIE), IIT(BHU), Varanasi. It is the Institute's dedicated platform for fostering innovation, entrepreneurship, technology, transition, and startup development. NA checked
Aug 17, 2026 @ 10:21 PM priyanshu jayswal priyanshuabc987@gmail.com https://www.linkedin.com/in/priyanshu-jayswal%20 https://preplinc.com/ 917307134641 Priyanshu Jayswal - Founder & CEO I lead PrepLinc full-time and have been working extensively on building and validating the venture. I have developed the product, conducted user and market validation, built the initial community and partnerships, and worked on defining the business model and technology roadmap. Alongside this, I am supported by a group of collaborators who contribute on a part-time and need basis, particularly in live sessions, mentorship, technical inputs, product, and business development. This includes Pranav Kumar Pandey, an AI Research Engineer at Amazon and an alumnus of IIT Dharwad, who contributes technical guidance and advanced AI-related inputs; Vedant Ghodke, an alumnus of IIT Dharwad with experience in resume-building startups, who contributes product and growth insights; and Pulkit Upadhyay, an alumnus of IIT Patna currently working in the RM BBG team at ICICI Bank, who contributes business and industry perspectives. They are not full-time members of the venture but contribute whenever their expertise is required. I remain the primary full-time founder responsible for the day-to-day execution, product development, partnerships, business strategy, and overall growth of PrepLinc. 1 Our biggest strength is the combination of strong founder ownership with access to a diverse network of domain expertise. I work full-time on PrepLinc and drive product development, execution, business strategy, and growth, while our collaborators bring expertise across AI, technology, product, growth, mentorship, and industry. This allows us to stay lean and move quickly while bringing in the right expertise whenever required. More importantly, our proximity to IIT alumni, experienced professionals, mentors, and students gives us a strong feedback loop between student needs, industry expectations, and hiring requirements. This combination of full-time execution and an expert network allows PrepLinc to continuously validate, build, and improve its AI-driven career ecosystem based on real-world data and experiences. PrepLinc https://preplinc.com/ Dharwad PrepLinc is building an AI-powered career and talent ecosystem that learns from the real interview experiences, career journeys, projects, resumes, and outcomes of seniors who have successfully entered top companies. PrepLinc uses this structured knowledge to help students understand the requirements of their target roles, personalize their preparation, and build stronger, opportunity-ready profiles rather than resume. The same talent intelligence is then used to identify high-potential students based on their skills, projects, experiences, and career readiness, enabling connections with relevant senior referrals, startups, and companies with seasonal or emerging hiring requirements. The career preparation ecosystem is highly fragmented and largely generic. Students often rely on scattered resources, generic courses, and informal advice, while the most valuable information—how specific students actually prepared, which projects helped them, what questions they faced, how they approached interviews, and what their successful profiles looked like—is rarely structured and made actionable. At the same time, companies, startups, and working professionals with referral or hiring requirements face the opposite problem: discovering genuinely capable students from a large and noisy talent pool is difficult. Resumes alone often do not capture a student's actual skills, projects, preparation, or potential. This creates a gap between two sides: valuable knowledge exists within successful professionals and alumni, while capable students and emerging hiring opportunities remain difficult to discover and connect efficiently. PrepLinc is building a data-driven AI career ecosystem around real career outcomes. We first structure knowledge from successful seniors—including interview experiences, resumes, projects, career paths, preparation strategies, and role-specific insights. Our AI layer uses this information to help students understand the pathways and requirements associated with their target roles and generate more personalized preparation and profile-building recommendations. As students interact with the platform, PrepLinc builds a richer understanding of their skills, projects, experiences, interests, and career readiness. This enables us to identify high-potential students beyond traditional college-brand or resume-based filtering. The resulting talent intelligence can then be used to connect relevant students with senior referral opportunities, startup hiring requirements, and seasonal or emerging company requirements. Our long-term vision is to create a continuous ecosystem where successful career journeys improve preparation for the next generation, while the resulting talent intelligence improves how companies discover emerging talent. Our potential defensibility comes from the combination of proprietary career-outcome data, structured talent intelligence, and a growing network of students, seniors, mentors, and employers. Unlike conventional career platforms that primarily aggregate courses, job listings, or generic preparation content, PrepLinc is building a structured knowledge layer from real outcomes—interview experiences, selected resumes, projects, career paths, preparation patterns, and role-specific experiences of successful candidates. As more seniors contribute their experiences and more students use the platform, PrepLinc can continuously improve its understanding of what successful career pathways look like and how student profiles evolve toward those outcomes. This creates a data and network flywheel that can improve both personalized career guidance and talent discovery. Over time, the combination of structured career data, student profiles, senior networks, employer relationships, and outcome feedback can become increasingly difficult to replicate. Users Users, Pilots, Signups PrepLinc serves two primary customer groups: **1. Students and early-career talent:** Engineering and university students seeking internships, placements, career guidance, and opportunities. We initially focus on students targeting SDE, AI/ML, core engineering, and other competitive roles. **2. Employers and talent seekers:** Startups, SMEs, growing companies, and hiring teams looking for relevant, pre-screened student talent for internships, entry-level roles, seasonal hiring, and project-based requirements. We also target working professionals and alumni who want to identify suitable candidates from their institutions or professional networks for referrals. Our long-term ecosystem connects these two sides through AI-driven career intelligence and talent discovery. **TAM: ~₹2,000–3,000+ crore annually** We view the long-term market as a combination of the student career-development market and the technology-enabled early-career hiring/talent acquisition market in India. Our broader opportunity includes millions of engineering and university students seeking career preparation and opportunities, together with startups, SMEs, and companies hiring interns and early-career talent. With a combination of student subscriptions/services and employer-side hiring or success-based fees, we estimate a multi-thousand-crore annual addressable opportunity in India. **SAM: ~₹500–800 crore annually** Our initial serviceable market focuses on engineering and technology-oriented students in India seeking internships and placements, along with startups, SMEs, and technology companies hiring entry-level talent. We will initially focus on high-intent segments such as students preparing for SDE, AI/ML, data, core engineering, and related competitive roles, where structured preparation and talent discovery have clear value. **SOM: ~₹25–50 crore annual revenue opportunity over the initial 3–5 year scale-up period** Our initial objective is to establish PrepLinc across selected engineering colleges and technology-focused student communities, build a strong network of successful seniors and mentors, and develop recurring relationships with startups and companies hiring early-career talent. We expect to initially capture a focused portion of the serviceable market through student subscriptions, employer hiring partnerships, and performance-based talent placement fees, before expanding across India. In terms of the business model, PrepLinc is evolving into a multi-layer ecosystem connecting students, senior talent, and companies. We plan to conduct structured short courses and cohort-based programs for students, led by top senior students and alumni from premier institutions. These programs will be priced in the range of ₹10,000–₹20,000 per student, focusing on practical career preparation, interview readiness, and role-specific skill building. On the company side, we will offer a subscription-based access model for startups and hiring companies to discover and evaluate high-signal talent data from the platform. In addition, for companies that directly hire candidates sourced through PrepLinc, we will charge a success-based fee in the range of 8–10% of the candidate’s CTC, particularly for startup and second-stage hiring companies. For candidates, PrepLinc also enables direct referrals through the senior network. In such cases, when a candidate is successfully placed via a senior-led referral through the platform, a platform facilitation fee of 8–10% of the candidate’s first-year salary will be applicable. This structure ensures alignment across all stakeholders—students gain access to high-quality mentorship and opportunities, seniors are incentivized to contribute, and companies gain access to high-intent, pre-validated talent efficiently. PrepLinc operates at the intersection of career preparation, professional networking, and talent discovery. **Direct/adjacent competitors include:** * **Naukri / Foundit / LinkedIn** — strong job and professional networking platforms, but primarily focused on job discovery and recruitment rather than learning from structured career journeys. * **LeetCode / GeeksforGeeks / InterviewBit** — strong technical preparation platforms, but primarily focused on practice and educational content rather than connecting preparation intelligence with talent discovery. * **Scaler / Interview-focused EdTech platforms** — provide structured career preparation, but generally follow a course/coaching-led model. * **Unstop / Internshala** — strong internship, competition, and early-career opportunity platforms, but primarily operate around opportunity discovery rather than building a deep career-outcome intelligence layer from successful candidates. PrepLinc's differentiation is in combining **real senior career data + AI-powered personalized preparation + student talent intelligence + opportunity matching** within one ecosystem. PrepLinc uses a community-led and campus-driven acquisition strategy. **Student acquisition:** * Founding Campus Leaders across engineering colleges * Partnerships with student communities, technical clubs, placement cells, and college organizations * Direct outreach through student and professional communities * Senior-led webinars, live sessions, and career events * Referral and peer-to-peer growth * Organic content built around real interview experiences, resumes, projects, and career journeys **Senior acquisition:** We onboard successful professionals and alumni by enabling them to share their interview experiences, career journeys, projects, and insights, creating value for both the contributor and the next generation of students. **Employer acquisition:** We plan to acquire startups and companies through direct B2B outreach, alumni networks, founder networks, startup communities, hiring partnerships, and referrals from the senior ecosystem. Our go-to-market strategy is designed to build the ecosystem from the supply of high-quality career knowledge before scaling employer monetization. **Phase 1 — Build the knowledge network:** Onboard successful seniors and alumni and structure their interview experiences, resumes, projects, and career journeys into a searchable and AI-ready knowledge base. This foundation is now nearly complete and will serve as the core engine for all downstream activities. **Phase 2 — Campus-led training and talent seeding:** Conduct structured training sessions in tier 2 and tier 3 colleges by bringing in high-performing seniors and alumni as mentors. These sessions will not only build awareness but also identify and nurture top talent early. High-potential students will be given referrals and internal recommendations from employees and mentors, creating a trusted talent pipeline. **Phase 3 — Expand college and community reach:** Gradually increase the number of partner colleges and student communities. Strengthen on-ground presence through student ambassadors, workshops, and senior-led cohorts to ensure consistent engagement and deeper penetration across campuses. **Phase 4 — Extend to startups and companies:** Reach out to startups, SMEs, and larger companies to showcase the platform as a talent discovery and training ecosystem. Offer them access to pre-trained, high-signal candidates and structured talent insights derived from the knowledge network. **Phase 5 — Build a closed-loop ecosystem:** As placements and internships increase, successful candidates become new seniors in the system, contributing back their experiences. This continuously enriches the knowledge network, improves training quality, and strengthens employer trust, creating a compounding growth loop. Our long-term vision is to build the intelligence layer connecting education, talent, and employment. We envision PrepLinc becoming a career ecosystem where every student's journey can be understood through skills, projects, experiences, interests, preparation, and demonstrated capabilities—not simply college name or a conventional resume. We aim to build a continuously improving career intelligence system powered by real-world outcomes: successful professionals contribute their career journeys, the system learns from those outcomes, students receive more personalized guidance, and employers gain access to better-understood emerging talent. Over time, PrepLinc can evolve from a career preparation platform into a talent intelligence and opportunity marketplace connecting students, alumni, mentors, startups, and companies across India. Our ultimate goal is to make high-quality career guidance and opportunity discovery less dependent on a student's college brand, network, or geography. NA 0 Yes We are applying to IITACB because PrepLinc is at a stage where access to the right mentors, alumni network, industry connections, and startup ecosystem can significantly accelerate our transition from an early product to a scalable career and talent ecosystem. IITACB's strong connection with IIT alumni, faculty, corporates, entrepreneurs, and the Bangalore startup ecosystem is particularly relevant to our model. Our platform is built around learning from successful professionals and alumni, so access to this network can directly strengthen our senior knowledge base, mentorship ecosystem, and industry relationships. We also want to leverage IITACB to validate our B2B talent-discovery model, develop partnerships with startups and companies, strengthen our technology and AI roadmap, and prepare PrepLinc for larger-scale growth and fundraising. During the programme, we aim to achieve five key outcomes: 1. **Strengthen our AI and technology layer** to convert our growing database of interview experiences, resumes, projects, and career journeys into actionable career and talent intelligence. 2. **Validate and scale our campus model** by expanding structured training and mentorship programmes across engineering colleges, particularly in the Tier 2 and Tier 3 ecosystem. 3. **Build employer partnerships** with startups, SMEs, and companies to validate our talent-discovery and hiring model and generate our first repeatable B2B hiring pipeline. 4. **Strengthen our senior and alumni network** by connecting with IIT alumni, experienced professionals, mentors, and industry leaders who can contribute knowledge, referrals, and hiring opportunities. 5. **Build a scalable business and fundraising strategy** with the guidance of IITACB mentors and the wider startup ecosystem, positioning PrepLinc for expansion across India. YES Bangalore provides an ideal market for PrepLinc because it brings together a dense ecosystem of technology companies, startups, engineering talent, investors, IIT alumni, and experienced professionals. We want to use this ecosystem as an early market for the employer side of PrepLinc. Our objective is to build relationships with startups, SMEs, technology companies, and growing businesses that regularly require interns, fresh graduates, and skilled early-career talent. IITACB can help us accelerate this by providing access to IIT alumni, industry leaders, corporates, founders, mentors, and potential hiring partners. We can leverage these relationships to strengthen our senior knowledge network, validate our AI-driven talent intelligence, develop employer partnerships, and create referral and hiring opportunities for students. The Bommasandra ecosystem can also serve as a real-world testing ground for our B2B model: understanding hiring requirements from companies, identifying relevant candidates from our student network, and measuring outcomes from training to hiring. Our goal is to use Bangalore not only as a physical base, but as an industry ecosystem through which PrepLinc can validate, refine, and scale its career-to-employment model before expanding it to other technology and startup hubs across India. Yes We would primarily use the IITACB infrastructure as a base for product development, industry engagement, mentor interactions, and ecosystem building. We would leverage the workspace for: * **Product and AI development:** Building and testing PrepLinc's AI-driven career and talent intelligence layer. * **Mentor interactions:** Regular discussions with IIT faculty, alumni, industry professionals, and startup mentors. * **Industry meetings:** Conducting meetings and demonstrations with startups, companies, and potential hiring partners. * **Senior-led sessions:** Organising focused career and mentorship sessions with IIT alumni and experienced professionals. * **Talent and employer pilots:** Running small-scale hiring and talent-discovery pilots with companies in the Bangalore ecosystem. * **Investor and stakeholder meetings:** Using the professional incubation environment for investor discussions, partnerships, and fundraising preparation. * **Team collaboration:** Using conference and collaborative spaces for product, strategy, and business-development activities. We see IITACB not simply as an office location, but as a physical gateway to the IIT alumni, industry, startup, and investor ecosystem that can help PrepLinc scale. Yes Supporting feature PrepLinc is being designed as a layered career and talent intelligence platform. **1. Data Layer:** We collect and structure interview experiences, resumes, projects, career journeys, role information, skills, student profiles, and hiring requirements. **2. Knowledge Structuring Layer:** The collected information is converted into structured entities such as companies, roles, skills, interview rounds, questions, projects, technologies, experiences, and career outcomes. **3. Intelligence Layer — Current:** At the current stage, we use rule-based algorithms, scoring systems, filtering, and matching logic to connect student profiles with relevant career paths, preparation resources, senior experiences, and opportunities. **4. Intelligence Layer — Future:** As our dataset grows, we plan to introduce machine-learning and deep-learning models to identify more complex patterns across successful career journeys, improve recommendations, predict candidate-role fit, and personalize preparation. **5. Application Layer:** Students receive personalized preparation and opportunity recommendations, while employers and senior professionals can discover relevant high-potential candidates. The architecture is therefore designed to evolve from deterministic algorithms to data-driven machine intelligence as the underlying dataset reaches sufficient scale. Our long-term data advantage is the structured career-outcome dataset we are building around successful candidates. Instead of collecting only conventional resumes or job listings, PrepLinc is structuring multiple dimensions of a candidate's journey: interview experiences, questions faced, preparation approaches, projects, skills, resumes, target roles, companies, career transitions, and eventually outcomes. The key advantage is the relationship between these data points. Over time, this can allow us to understand patterns such as what types of projects, skills, preparation paths, and experiences are associated with success for particular roles and companies. The dataset is currently at an early stage, so we are focusing on building data quality, structure, and relevance before introducing more sophisticated machine-learning models. Our defensibility is expected to come from the combination of structured career-outcome data, algorithms, network effects, and employer relationships. The underlying information is not simply generic educational content. We are building structured connections between successful candidates, their resumes, projects, interview experiences, preparation journeys, roles, companies, and eventual outcomes. As more students, seniors, mentors, and employers participate, the ecosystem can generate increasingly valuable data and feedback. Successful students can eventually become contributors themselves, creating a continuous feedback loop. Over time, this combination of proprietary structured data, accumulated outcomes, student and senior networks, and employer relationships can create a stronger competitive advantage than simply offering another AI-powered preparation interface. At the current stage, we evaluate the system primarily through the quality and relevance of its algorithmic recommendations and matching results. Our current evaluation areas include: * Relevance of recommended preparation resources and senior experiences * Accuracy of role/company/skill-based filtering * Quality of student-to-opportunity matching * User engagement with recommendations * Feedback from students and mentors * Conversion from preparation to applications, referrals, interviews, and opportunities * Quality of candidates shortlisted for employer requirements As the dataset grows and machine-learning models are introduced, we plan to additionally evaluate precision, recall, ranking quality, recommendation relevance, calibration, and outcome-based metrics such as interview and placement conversion. We intend to continuously compare technology-driven recommendations against baseline rule-based approaches and real-world outcomes. PrepLinc treats student and professional data as sensitive career information and follows a consent-driven approach to data collection and usage. We aim to collect only information required for the relevant product functionality, clearly communicate how data is used, and obtain appropriate consent before using personal information for recommendations, referrals, or hiring-related activities. Our planned approach includes role-based access controls, secure authentication, encrypted data transmission, controlled database access, and separation of personally identifiable information from analytical datasets wherever practical. For employer-side talent discovery, we intend to share candidate information only through appropriate consent-based workflows. We will also build processes for data deletion, correction, and user control as the platform scales. As PrepLinc expands, we will align our privacy, security, and data-handling practices with applicable Indian data-protection and technology regulations. Government and institutional initiatives supporting digital education, employability, skill development, entrepreneurship, startup incubation, and technology adoption can positively support PrepLinc's ecosystem. However, the business is not dependent on a specific policy intervention. Our primary growth drivers are student demand, senior/alumni participation, employer hiring requirements, and the increasing need for efficient talent discovery. The primary regulatory considerations relate to data privacy, consent, cybersecurity, and the responsible use of student and professional information. As PrepLinc expands its AI capabilities, we will also need to ensure that automated recommendations and candidate matching are transparent, appropriately monitored, and do not create unfair or discriminatory outcomes. We currently view these as manageable compliance and product-design considerations rather than fundamental barriers to the business. We plan to strengthen our privacy, security, consent, and responsible-AI processes as the platform and dataset scale. At 10x scale, the primary challenges would be data processing, search and recommendation performance, database growth, concurrent traffic, and maintaining recommendation quality as the number of students, seniors, opportunities, and career experiences increases. The architecture is being designed with these scaling requirements in mind through structured data models, modular services, indexed search, caching, and scalable cloud infrastructure. The larger challenge will not only be infrastructure capacity but also maintaining data quality and relevance. As the dataset grows, we will need stronger automated data validation, deduplication, ranking systems, monitoring, and eventually machine-learning models to handle the increasing complexity of relationships within the data. We currently do not have a dedicated full-time deep-tech team. The core product and technology development is led by the founder, supported by part-time technical collaborators. This includes Pranav Kumar Pandey, an AI Research Engineer at Amazon and an alumnus of IIT Dharwad, who provides technical guidance and contributes to discussions around AI and advanced machine-learning approaches. As the dataset and product scale, we plan to build a dedicated AI/ML capability focused on recommendation systems, talent matching, career intelligence, and eventually deep-learning models. Our current system primarily uses internally collected and structured data, including interview experiences, resumes, projects, career information, student profiles, and opportunity information. The current recommendation and matching layer is primarily based on our own database structures, business logic, scoring systems, filtering, and algorithms rather than a proprietary deep-learning model. We also use standard open-source software libraries and frameworks for application development and data management under their respective licenses. We do not currently claim ownership of third-party datasets or open-source components. As we introduce machine-learning and deep-learning components, we will maintain clear records of model sources, datasets, licenses, dependencies, and internally developed components to ensure appropriate IP and licensing compliance. Our technology roadmap follows a progressive data-driven approach. **Current stage:** We are focusing on collecting high-quality structured data and using deterministic algorithms, scoring, filtering, and matching systems. This allows us to validate the product and understand which signals actually matter before introducing complex models. **Next stage:** As the dataset grows, we will introduce machine-learning models for recommendation, ranking, candidate-role matching, and personalization. These models will be trained and evaluated against real-world outcomes and user feedback. **Later stage:** With sufficient volume and diversity of high-quality data, we plan to explore deeper neural and other advanced AI models capable of learning complex relationships across career journeys, skills, projects, interview experiences, and hiring outcomes. At every stage, we will compare the newer approach against the existing baseline using measurable outcome metrics rather than adopting more complex AI simply for its own sake. **India initially, with a long-term global vision.** India is our initial market because of its large engineering student population, rapidly growing startup ecosystem, strong IIT and university networks, and significant gap between student talent and access to high-quality career opportunities. We plan to first build and validate the model across Indian colleges, startups, and companies. Once the career-intelligence and talent-matching infrastructure is validated, the underlying model can be extended to other emerging talent markets and eventually global early-career ecosystems. The long-term opportunity is to build a technology platform that can understand career pathways and talent beyond geographical or institutional boundaries. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/HUtIVVOakMw1-PrepLinc_clean.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/HUtIVVOakMw1-PrepLinc_clean.pdf Yes. PrepLinc is built around the mission of reducing the dependence of career opportunities on college brand, geography, and existing personal networks. A large amount of valuable career knowledge already exists among students and professionals who have successfully entered top companies, but this knowledge is fragmented and often inaccessible to students from Tier 2, Tier 3, and other underserved colleges. PrepLinc aims to structure this knowledge and make it actionable through technology—helping students understand successful career pathways, prepare more effectively, and become visible based on their actual skills, projects, and potential rather than only their college name. On the other side, we aim to help startups and companies discover capable students who may otherwise remain hidden in a large and fragmented talent pool. Our long-term goal is to create a more merit- and capability-driven career ecosystem where opportunity is determined more by what a student can demonstrate than by where they studied or whom they already know. NA Rakshit Kalyani , IIT Dharwad NA checked
Aug 17, 2026 @ 10:05 PM Rohit Kumar rohit.kumar.che23@itbhu.ac.in https://www.linkedin.com/in/rohit-kumar2005/ https://tripflow.live +919350126101 Tarun Singh — Co-founder (AI & Backend Architecture), Rohit Kumar — Co-founder (Product Engineering & Full-Stack) We met during an on-campus college event at IIT (BHU) and have been working closely together for about 2.5 years. Over this period, we have collaborated across multiple technical projects and venture initiatives, developing a strong working chemistry and a proven track record of shipping end-to-end products together. 2 100% In-House Technical Execution and Rapid Iteration. We cover the entire product lifecycle internally—from AI workflow orchestration and backend pipelines to frontend design and deployment—without relying on external developers. Having built and shipped projects together for 2.5 years, our complementary skill sets and shared context allow us to unblock technical bottlenecks quickly, validate user feedback, and move from concept to working code with high velocity. TripFlow https://tripflow.live Agra, India TripFlow is an AI travel agent that plans and books personalized, end-to-end trips in real time—integrating transport, stays, and activities into a single seamless flow. Travel planning is highly fragmented, requiring users to juggle multiple platforms for flights, stays, itineraries, and weather. This manual coordination leads to severe decision fatigue and abandoned plans. TripFlow provides an agentic AI travel platform that understands natural-language travel intent and automatically constructs complete, personalized journeys. It fetches real-time transport (flights, trains, buses) and hotel availability, generates day-wise itineraries with curated attractions, offers weather-aware packing recommendations, and facilitates direct booking execution within a unified interface. Unlike traditional OTAs that only handle disconnected, individual transactions, TripFlow orchestrates the full journey through end-to-end AI reasoning and real-time API integrations, converting conversational planning directly into real-time bookings. Users Signups Digitally native leisure travelers, including young professionals, couples, and group travelers who actively research vacations online and value personalized, time-efficient travel planning. $1.1T (Global Online Travel & Tourism Market) $28B (Indian Online Travel & Digital Itinerary/Booking Market) $35M (Targeting 1.5M digitally active Indian leisure travelers over 3 years) Hybrid model: Micro-transactions (₹49 per complete AI-generated itinerary unlock) combined with affiliate commissions and booking fees from transport and accommodation partners. Traditional OTAs (MakeMyTrip, Booking.com, EaseMyTrip), itinerary builders (Wanderlog, TripIt), and generic conversational AI tools. Organic travel-tech content marketing on Instagram/YouTube, community-led college and young professional outreach, SEO-driven destination guides, and referral incentives. Launch focused campaigns targeting weekend getaways and popular holiday routes for college students and young professionals, scale through viral social media itineraries, and integrate directly with travel suppliers for seamless checkout. To become the default autonomous travel companion globally, managing the entire lifecycle of a trip—from intent discovery and instant booking to real-time, on-trip itinerary adjustments. Incorporated in Jan 2026 500000 Yes To leverage IITACB’s strategic network, industry mentorship, and startup ecosystem in Bangalore to transition TripFlow from a validated MVP (TRL 5) to a fully commercialized, revenue-generating platform (TRL 7). Establish key travel supplier/API partnerships, achieve product-market fit with 10,000+ active users, optimize unit economics, and prepare the company for institutional seed funding. Yes, we are fully open to a hybrid/virtual engagement mode while traveling to Bangalore for critical milestones, mentor reviews, and investor showcases. Bangalore is India’s primary tech and consumer innovation testbed with a dense demographic of tech-savvy, frequent weekend travelers. IITACB can facilitate direct access to corporate travel partnerships, local angel/VC networks, and mentorship to refine our distribution strategy. Yes We plan to use the incubator space as our strategic base in Bangalore for product sprints, in-person mentor meetings, strategic partner onboarding, and direct investor presentations. Yes Core engine • Frontend: React / Next.js, TypeScript, Tailwind CSS. • Backend & Orchestration: Node.js / Hono / Python, agentic workflow orchestration pipelines. • AI & LLMs: Large Language Models (e.g., Gemini API) with structured schema validation and prompt pipelines for intent parsing. • Data & Real-Time APIs: Live travel APIs (flights, trains, buses, hotels), weather endpoints, places data, and a scalable database (PostgreSQL / Supabase / MongoDB). A compounding feedback loop of intent-to-itinerary mappings, user travel preference graphs, and aggregated route optimization data generated from real user trip-planning interactions. End-to-end orchestration and seamless booking flow. Unlike standalone LLM wrappers that only generate text, TripFlow binds dynamic user constraints to real-time inventory and execution, building strong personalization moats and high switching costs over time. Itinerary Generation Latency: Time-to-first-plan delivery. • API Success & Freshness Rate: Accuracy and live availability of inventory results. • Constraint Adherence Rate: Percentage of generated trips meeting exact user budget, timing, and route constraints. • Plan-to-Booking Conversion Rate: User transition from AI itinerary generation to payment/checkout. End-to-end TLS encryption in transit, secure database storage with strict access controls, zero sensitive payment storage (delegated entirely to PCI-DSS compliant payment gateways), and strict adherence to data privacy standards (DPDP Act compliance). Government initiatives promoting domestic tourism (Dekho Apna Desh), the rapid digitalization of Indian transit infrastructure (IRCTC/NDHM/ONDC travel initiatives), and DPDP compliance frameworks supporting transparent data-driven digital platforms. Changes in travel aggregator licensing, strict API throttling/terms from global travel inventory providers, and evolving data residency/privacy compliance requirements. External API rate limits/latency bottlenecks and concurrent LLM reasoning costs. We mitigate this using intelligent caching layers, decoupled asynchronous task queues, and optimized multi-tier model routing. Yes. Both co-founders are hands-on engineers with expertise in full-stack web architecture, agentic AI orchestration, API integration, and automated data processing pipelines. • Open-Source Stack: React, Next.js, Node.js/Python frameworks (all MIT/Apache 2.0 licensed). • External APIs: Commercial REST APIs for live travel data, maps, and weather. • Proprietary IP: In-house agentic prompt workflows, parsing algorithms, and end-to-end travel orchestration codebase owned entirely by TripFlow Technologies Private Limited. Fine-tuning lightweight open/custom models on curated travel preferences, implementing proactive edge caching for top travel corridors, and optimizing agent reasoning latency based on user telemetry. Both. Launching initially in the Indian market to capture the domestic travel and tech-savvy leisure demographic, with an architecture designed to expand into Southeast Asian and global leisure corridors. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/GyjeRi90UrfZ-Trip-Flow-Pitch-deck_compressed.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/GyjeRi90UrfZ-Trip-Flow-Pitch-deck_compressed.pdf Yes. TripFlow makes travel accessible, stress-free, and personalized for everyday travelers while promoting local tourism. By intelligently distributing footfall to offbeat destinations, local homestays, and regional experiences rather than just overcrowded commercial hotspots, TripFlow empowers local tourism economies and sustainable travel practices. NA IIT (BHU) Incubation Centre / Student Entrepreneurship Network, JIC IIT BHU We are a dedicated student-founder team from IIT (BHU) with a working, validated MVP (TRL 5). We are prepared to commit fully to scaling TripFlow with the support, mentorship, and industry connections provided by the IITACB incubator. checked
Aug 17, 2026 @ 9:50 PM Prabhjit Gill prabhjeetgill17@gmail.com https://www.linkedin.com/company/10495000/admin/dashboard/ http://www.chaintracelabs.com +91-9814666141 Co-Founder & Chief Legal Officer, Chain Trace Labs We've known each other for the past 10 years. 2 Our biggest strength is the complementary expertise of our founding team. I bring legal, regulatory, business development and institutional partnership experience, while my technical co-founder brings strong expertise in blockchain technology and product development. Together, we combine the ability to understand complex crypto investigations from both the legal and technological perspectives and turn that into a practical, scalable product. Chain Trace Labs www.chaintracelabs.com Chandigarh, India. Chain Trace Labs is a blockchain forensics and crypto-investigation platform that enables law enforcement agencies, financial institutions, exchanges, and legal professionals to trace and analyse cryptocurrency transactions across multiple blockchains. It provides KYT, wallet and transaction analysis and legal-ready forensic reports, helping organisations investigate crypto fraud and illicit fund flows. Chain Trace Labs addresses the growing challenge of investigating cryptocurrency fraud and illicit transactions. Blockchain data is public, but tracing complex fund flows across multiple wallets, chains, bridges and services requires expensive tools and specialised expertise. We simplify this process by providing investigators, law enforcement, financial institutions and legal professionals with faster, affordable and legally useful blockchain tracing and forensic analysis. Chain Trace Labs is a blockchain forensics platform that enables users to trace cryptocurrency transactions across multiple blockchains, identify wallet relationships and fund flows, detect high-risk activity, and generate investigation-ready reports. Our platform combines automated blockchain analytics with AI-assisted investigation narratives, making complex crypto investigations faster, more affordable, and easier to understand for law enforcement, financial institutions, investigators, and legal professionals. Our key differentiator is the combination of multi-chain blockchain tracing, AI-assisted analysis, and legal-ready forensic reporting in a single platform. Unlike expensive enterprise tools that primarily provide blockchain intelligence, Chain Trace Labs is designed to bridge the gap between technical transaction tracing and actionable legal/investigative outcomes. Our focus on affordability, ease of use, and investigation-ready outputs makes the platform accessible to law firms, financial institutions, and law-enforcement agencies that may not have access to expensive specialist tools. MVP Pilots Our primary target customers are law-enforcement and cybercrime agencies, financial institutions, cryptocurrency exchanges and VASPs, law firms, crypto-investigation firms, compliance teams, and corporate fraud/investigation teams. We focus particularly on organisations that need to trace illicit crypto flows, investigate fraud and money laundering, conduct AML/KYT analysis, and generate legally usable forensic reports. Our global TAM is approximately US$3.5 billion in 2026, covering the crypto compliance, blockchain analytics and blockchain forensics market. Our Serviceable Addressable Market is approximately US$1–1.5 billion globally. Our Serviceable Obtainable Market (SOM) is approximately US$10–15 million over the next 3–5 years, representing an achievable share of our initial target segments across law enforcement, financial institutions, crypto businesses, investigators and legal professionals. Our revenue model is primarily B2B SaaS, supported by investigation and enterprise services. We generate revenue through monthly/annual subscriptions for access to blockchain tracing, KYT, risk analysis and monitoring tools, along with pay-per-investigation and forensic reporting fees. For larger institutions, law-enforcement agencies and enterprise clients, we offer customised enterprise licences, API access, training and implementation services. Our main competitors are TRM Labs, Elliptic, Crystal Intelligence, Merkle Science and AnChain.AI. We use a focused B2B, founder-led sales strategy to acquire customers. Our initial approach is direct outreach to law-enforcement agencies, law firms, financial institutions, crypto businesses and professional investigators, supported by product demonstrations and pilot investigations. Our go-to-market strategy is a B2B, institution-led approach focused initially on India and then expanding internationally. We will target law-enforcement and cybercrime agencies, law firms, financial institutions, crypto businesses and investigation firms through direct founder-led outreach, demonstrations and pilot projects. Our long-term vision is to build Chain Trace Labs into a global digital-asset intelligence and blockchain forensics platform that becomes a trusted layer for investigating and preventing crypto-related financial crime. Partnership NA Yes We are applying to IITACB because Chain Trace Labs sits at the intersection of blockchain, cybersecurity, financial crime investigation and legal technology. IITACB’s strong network of IIT alumni, industry leaders, mentors, investors and government stakeholders can help us strengthen our technology, validate institutional use cases and accelerate market adoption. We believe the IITACB ecosystem can help us scale Chain Trace Labs from an emerging product into a globally recognised blockchain forensics platform. During the programme, we aim to strengthen and validate our product, secure pilot projects with institutional customers, develop strategic partnerships, and accelerate customer acquisition. We also want to leverage IITACB’s mentorship, industry and investor network to refine our technology and go-to-market strategy, prepare for fundraising, and establish Chain Trace Labs as a scalable global blockchain forensics platform. Yes Bengaluru offers access to a strong ecosystem of technology, fintech, cybersecurity, financial and corporate customers. We can leverage this market for enterprise pilots, partnerships and customer acquisition. IITACB can support us through its IIT network, industry and government connections, mentorship and investor ecosystem, helping us validate and scale Chain Trace Labs in India and internationally. Yes We would use IITACB’s infrastructure as a professional base for team collaboration and institutional networking. The meeting and conference facilities would help us engage prospective partners, while the wider IITACB ecosystem would support collaboration with mentors, industry and the IIT community. Yes Supporting feature Chain Trace Labs uses a modular, cloud-based architecture with blockchain data ingestion and risk-detection engines. The platform aggregates on-chain data, maps wallets and transaction flows, identifies risk indicators, and converts findings into investigation-ready reports through a secure web-based interface. Our primary data advantage is not proprietary blockchain data, since the underlying blockchain data is public. Our advantage lies in how we structure and analyse that data. We are building proprietary case intelligence and cross-case intelligence derived from investigations conducted on the platform. Over time, this growing intelligence layer will improve our ability to identify recurring wallets, entities, fraud patterns and fund-flow behaviours Our defensibility comes from combining multi-chain tracing with a complete investigation workflow rather than offering blockchain analytics alone. We are building proprietary case intelligence investigation patterns. This creates a growing intelligence layer and workflow ecosystem that becomes more valuable as investigation volume increases. Our focus on law firms, investigators and law enforcement also creates domain-specific workflows and institutional relationships that are difficult to replicate quickly We evaluate performance and reliability using measurable benchmarks including transaction-tracing accuracy, API response time and investigation processing time. We also benchmark tracing depth and cross-chain performance against established blockchain analytics platforms. As we scale, we plan to conduct structured pilot tests using real investigation datasets, detection time and analyst productivity. We follow a security-by-design approach, with strict access controls, encryption of sensitive data and controlled access to investigation data. Customer and case information is segregated and accessed only by authorised personnel. Yes. India’s evolving regulatory framework for Virtual Digital Assets, including FIU-IND registration and AML/CFT requirements for VDA service providers, creates strong demand for blockchain analytics, transaction monitoring and forensic investigation tools. The strengthening of India’s digital data-protection and cybersecurity framework also supports the need for secure, compliant technology solutions. Yes. Key risks include changes in VDA/AML regulations, cross-border data rules and evolving regulatory treatment of blockchain analytics services. We mitigate these risks through a compliance-first approach, ongoing regulatory monitoring and designing our platform to support applicable AML/KYC, privacy and security requirements. India’s evolving VDA framework also creates significant demand for our solution. At 10x scale, the main pressure points would be blockchain data ingestion/indexing, database query performance, and AI/report-processing workloads. Our architecture is designed to address these through horizontal scaling. We would monitor throughput, uptime, queue depth and infrastructure cost per investigation, allowing us to identify and scale bottlenecks before they impact customers. Yes. Our technical co-founder leads the in-house deep-tech development, with expertise in blockchain architecture, multi-chain data processing, transaction analytics, backend engineering and AI-assisted investigation workflows. The team is focused on building scalable blockchain forensics infrastructure, automated tracing and intelligence capabilities. We primarily use publicly available blockchain datasets and licensed third-party APIs/data sources for on-chain analysis. We also use open-source libraries and standard software components under their respective licences. Our proprietary IP lies in the data-processing architecture, tracing and analytics workflows, risk-scoring methodologies, case-intelligence layer, investigation workflows and reporting system that we build on top of these data sources. Any third-party datasets or components are used in accordance with their applicable licences and commercial terms. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/KlPjISTjJ078-ChainTrace-Labs-Investor-Deck-August-2026.pptx, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/KlPjISTjJ078-ChainTrace-Labs-Investor-Deck-August-2026.pptx Yes. Chain Trace Labs is focused on making digital-asset investigations more accessible, affordable and effective. By helping law-enforcement agencies, financial institutions, investigators and legal professionals trace illicit crypto flows, we aim to combat fraud, money laundering and financial crime while improving trust and accountability in the digital-asset ecosystem. NA NA checked
Aug 17, 2026 @ 9:41 PM Vaibhav Pratap Singh vaibhavpratapsingh07@gmail.com https://www.linkedin.com/company/quntrolsphere/ 917829635748 Vaibhav leads the technology development, Amruta leads the business and growth vertical and Ashutosh leads the scientific R&D. Vaibhav and Amruta are IIT Madras alumni from the 2014–2015 batch and have maintained a long-standing friendship since. Additionally, Vaibhav and Ashutosh have collaborated since 2022 on the MeitY-funded project "Metro Area Quantum Access Network" as part of their Ph.D. research at IIT Madras. The outcomes of this research have laid the groundwork for Quntrolsphere. 1 The QuntrolSphere team combines multidisciplinary expertise across RF engineering, FPGA-based high-speed digital logic, and precision quantum control. We possess a unique ‘hardware-first’ advantage, having successfully engineered sub-nanosecond synchronisation matrices and control electronics for quantum communication and currently working on universal control architectures essential for scaling quantum nodes. Our strength lies in our ability to translate complex quantum physical requirements into deployable, interoperable hardware systems. This end-to-end competency allows us to overcome the critical latency and coherence bottlenecks that currently prevent the effective scaling of distributed quantum computing. QuntrolSphere Pvt. Ltd. https://www.quntrolsphere.com/ Chennai QuntrolSphere is architecting the full-stack quantum infrastructure of the future. Our portfolio spans universal control electronics, distributed quantum computing hardware, and secure quantum communication protocols—engineered to make quantum systems scalable, interconnected, and commercially viable. Incubated within the deep-tech ecosystem of IIT Madras and the IITM-CDOT Samgnya Technologies Foundation, we build high-precision, mission-critical hardware for advanced quantum applications. Distributed Quantum Computing QuntrolSphere solves the scaling limits of monolithic quantum processors by delivering a modular hardware architecture for Distributed Quantum Computing (DQC). We interconnect multiple quantum processing units (QPUs) into a single, cohesive computational network to bypass the thermal, spatial, and wiring bottlenecks of isolated systems. Synchronized Control Infrastructure: Ultra-low-latency, phase-stable electronic platforms enable deterministic real-time pulse generation and readout across physically separated QPUs. Photonic Interconnects: Specialized hardware interfaces convert stationary qubits to flying photonic qubits, driving high-fidelity optical links and remote entanglement generation. Distributed Gate Execution: Hardware-level routing protocols and integrated FPGA co-processors manage real-time classical feed-forward, state teleportation, and non-local multi-qubit gates. This approach enables linear, modular scaling—allowing to expand computational capacity incrementally without redesigning core processor chips. Our defensibility lies in our unified hardware stack, proprietary IP, and deep-tech domain expertise. Unlike modular patchwork systems, QuntrolSphere integrates synchronized control electronics, photonic interconnects, and real-time FPGA feed-forward into a single low-latency architecture. Built on multi-year research and supported by IIT Madras and the IITM-CDOT Samgnya Technologies Foundation, our solution has a steep technical moat across quantum optics, high-speed RF, deterministic multi-node synchronization and quantum networks. Idea Pilots, Signups Our target customers are quantum computing OEMs and research labs requiring modular FPGA/RF control stacks and distributed computing hardware. Additionally, we serve defense, government, and telecom operators towards quantum communication systems and solutions. 5.9 billion USD 61 million USD 29 million USD Our model follows a phased, value-first approach focused initially on ecosystem adoption, IP creation, and technical validation rather than immediate aggressive monetization. Early-stage revenue will be driven by non-dilutive research grants, joint development partnerships, and paid hardware pilots with academic and national research labs. As the market reaches commercial maturity, we will transition to high-value hardware sales of our modular control and interconnect platforms, and recurring software licensing for our proprietary routing firmware across enterprise quantum computing centers world over. Qblox, Quantum Machines, Zurich Instruments, Qphox We acquire customers through a direct B2B deep-tech sales strategy driven by joint research partnerships and paid hardware pilots with academic institutions and national labs. We also aim to target public procurement tenders and defense mandates, while scaling enterprise adoption via direct technical sales and strategic integrations with quantum hardware OEMs and system integrators. Our go-to-market strategy begins by establishing initial traction through joint research partnerships, paid pilot deployments, with national labs, academic institutions, and defense agencies. As our platform validates at scale, we transition to direct enterprise sales targeting quantum hardware OEMs and strategic integration partnerships with quantum cloud and HPC providers. QuntrolSphere envisions a future where quantum computing transcends the physical constraints of individual processors through seamlessly interconnected, modular hardware. By building the universal control electronics, photonic interconnects, and synchronisation and routing protocols that unify distributed quantum nodes, we aim to become the critical infrastructure layer powering the world’s first fault-tolerant, networked quantum supercomputers and sovereign quantum-secure communications. Incorporated at ROC Chennai on 9th June 2025 1 cr INR from IITM CDOT Samgnya Technologies Foundation Yes We are applying to IITACB to establish a strong operational presence within Bengaluru’s vibrant innovation hub. As an IIT alumni-founded venture, we recognize the immense value of leveraging the collective strength, mentorship, and industry access of the alumni network. Engaging with the IITACB ecosystem gives us direct access to experienced deep-tech operators, corporate tie-ups, and active angel and VC networks, providing the strategic support needed to transition our technology from validation to scalable commercial deployment. Through the IITACB programme, our primary objective is to rigorously validate our investor readiness, refine our commercial narrative, and establish direct connections with deep-tech investors and alumni angels. Yes We are applying to IITACB to expand our operations into Bengaluru’s startup ecosystem by renting dedicated seats at the incubator. As IIT alumni, we deeply value the trust, and collaborative power of the alumni ecosystem. Being physically based at IITACB will provide our team with essential infrastructure, proximity to advanced hardware/tech clusters, and high-trust access to mentors, industry tie-ups, and early-stage deep-tech investors as we scale. Our collaborators ae based in proximity to the Bommasandra industrial hub and gives us strategic advantage going forward. Yes We plan to use IITACB’s incubator and facility infrastructure as a dedicated hardware development base to advance our core quantum systems. We will execute the design, development, and testing of our universal control electronics, leveraging Bengaluru’s concentration of leading quantum computing labs for rapid validation cycles. Additionally, we will use the facilities for the integration and characterization of our QKD chassis systems under the National Quantum Mission's Quantum Internet with Local Access (QuILA) project Yes Supporting feature Our technical architecture is a modular hardware-software stack engineered for distributed quantum computing and quantum networking. The physical layer integrates high-speed FPGA and RF/microwave control electronics with sub-nanosecond master clock synchronization matrices and low-loss QKD/entanglement interconnects. Above the hardware, an orchestration software pipeline compiles quantum circuits into pulse-level execution, utilizing embedded machine learning models at the DSP stage strictly to optimize readout state classification and accelerate quantum error correction (QEC) syndrome decoding. Our data advantage lies in proprietary, hardware-in-the-loop operational datasets generated from our control electronics and testbed deployments. Because these datasets reflect physical hardware imperfections and environmental noise, they provide a closed-loop training asset that purely software-based competitors cannot replicate without custom hardware testbeds. Our defensibility stems from our full-stack integration across high-speed RF/FPGA control electronics, picosecond-level master synchronization, and low-latency quantum networking hardware. By solving physical interconnect and latency bottlenecks directly at the hardware layer, we create a high technical barrier to entry. We benchmark performance using timing jitter and synchronization precision, qubit readout fidelity and latency, and control signal purity (SFDR across RF channels etc.). For reliability, we measure continuous drift stability during 24/7 testbed runs, quantum bit error rate (QBER) and secure key rate (SKR) over extended fiber links etc. We will implement security-by-design at the hardware layer, ensuring all quantum control and telemetry data will remain encrypted on-premise without external cloud dependencies. Our quantum communication hardware will comply with standard communication security protocols, while strict FPGA firmware integrity checks, signed bitstreams, and role-based access control will prevent tampering across all deployment environments. National Quantum Mission (NQM) and RDI funds have been vital initiative which shall assist in making India a deep tech power house in the coming years. We shall maintain regular compliance to RF/baseband electronics standards and quantum communication standards under TEC, DoT. Any restriction on export control of developed solution shall be pose a risk. Scaling 10x stresses inter-chassis clock synchronization (maintaining sub-nanosecond phase alignment across multiple racks), thermal dissipation in dense multi-channel RF pipelines, and real-time backplane bandwidth for distributed QEC syndrome decoding. We mitigate these through modular chassis designs, automated optical clock distribution, and high-speed inter-FPGA optical transceivers. We have expertise to get started in the proposed technology stack. We shall scale further as per requirements and cash flow. Vaibhav and team comes with experience in control electronics development, and Ashutosh comes in with a research focus towards distributed computing. Vaibhav and Ashutosh both have worked extensively on quantum networks. We leverage standard open-source tools (Qiskit, OpenQASM) and the CERN open-source White Rabbit protocol for sub-nanosecond optical timing distribution. However, all core FPGA RTL, RF pulse synthesis pipelines, embedded ML readout models, and hardware calibration datasets shall be proprietary and owned in-house. Our IP is secured via trade secrets, closed-source HDL repositories, with patent filings planned at critical junctures. We aim to continuously improve performance by feeding empirical telemetry from active quantum computing facilities back into our ML models to optimize qubit readout fidelity. Simultaneously, we refine our FPGA RTL pipelines to push for better performance alongside evolving support for multiple qubit modalities. We have started with Indian market; however, we do plan to expand to global markets in near future. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/pW2L8Qzw8WMS-Pitch_Deck_QS_brief.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/pW2L8Qzw8WMS-Pitch_Deck_QS_brief.pdf Yes, we are deeply mission-driven. We are building the foundational hardware layer required to enable distributed quantum computing and quantum-secure communications. In alignment with India’s National Quantum Mission, our mission is to establish indigenous deep-tech capability, securing national critical infrastructure with indigenous QKD hardware while eliminating dependence on foreign dual-use control electronics. By solving the challenges with distributed computing and control bottlenecks, our solutions will empower researchers and enterprises to scale quantum computing facilities and realize the true potential of quantum technologies. Prof. Anil Prabhakar checked
Aug 17, 2026 @ 9:11 PM Dipen Mangal dipen.mangal@gmail.com http://www.linkedin.com/in/ca-dipen-mangal-021119147 https://kredemy.com/ +919157969219 Dipen is responsible for the designing product, managing operations, strategy and financial management of the company. Kredemy was founded by Dipen Mangal, who began the venture with a clear vision to transform education finance through technology. As the idea evolved, Dipen brought together a highly committed and complementary team around the mission. Rather than being a team formed solely for the venture, the core members have developed strong professional trust and alignment through sustained collaboration, shared responsibilities and a common belief in Kredemy’s vision. 1 We are fostering a culture of ownership, loyalty and long-term commitment in the company. The team has worked together across product development, technology, operations and business strategy, thereby creating strong working chemistry and a shared understanding of the company’s goals. Kredemy Technologies Private Limited https://kredemy.com/ Surat Kredemy is solving education financing problems for both parents and educational institutions. Our entire current ecosystem is designed to power our signature product i.e., INDIA’S FIRST EVER EDUCATION CO-BRANDED CREDIT CARD. We aspire to solve the following problems: 1) Finding schools based on references substantially limits the options to 3-4 schools only to select from. 2) Limited education financing option at K12 education level. 3) Most already has a policy to give discounts from 4%-15% on upfront fees payment. But most parents aren't able to claim those discounts due to shortage of liquidity for upfront fees payment. 4) Colleges and universities usually require parents to make upfront fees payment semester wise or annually. While professional courses like doctorate, engineering, MBA from top colleges are financed by bank, such financing option aren’t available for all graduate and post graduate courses. 1) Creating a network of educational institutions such that parents can seamlessly find the best schools for their children. 2) Each school already has a policy to give discounts from 4%-15% on upfront fees payment. But most parents aren't able to claim those discounts due to shortage of liquidity for upfront fees payment. 3) Launching our own co-branded credit cards allowing parents to make upfront fees payment. We will pass up to 80% discount received from schools to the parents. This will allow parents to claim discounts on fees payment while also deferring payments up to 6 months on no-cost basis. 4) Allow parents to defer fees across our network colleges and universities level up to 6 months. Colleges and universities usually require parents to make upfront fees payment semester wise or annually. Our goal is to launch India's first ever co-branded credit cards in the education space. There are numerous credit cards in the market offering dicounts and offers across travel, dining, shopping etc. But none exists that can provide discounts on education related spending that is one of the highest spends for most households. The existing players provide financing in the form of loans without any discount benefit. Further, it increases costs for parents due to interests on such loans. Our tech infrastructure and payment gateway integration will equip educational institutions to accept payments through cards following which we will proceed to launch our cards in the market. MVP Pilots Our target customers are educational institutes and parents. 19 lakh crore 68709 crore 1275 crore Our company has 3 major revenue streams: (1) Subscription fees for our SAAS platform (2) Comission payout from partner payment gateway (3) Credit card interchange fee from the credit card network issuer Our main competitors include Grayquest, Leo1 and Ezyschooling Dipen being a Chartered Accountant and auditor of certain educational institutes, he is responsible for customer acquistion through direct contacts, references and marketing Launching of SAAS platform to create a network of educational institutes Our long-term vision is to build Kredemy into a large, technology-driven financial services company and eventually evolve it into an NBFC with a diversified lending and financial services portfolio. We intend to begin by establishing a strong presence in education payments and financing, then gradually expanding into broader consumer, business and institutional financial products. The objective is to leverage the technology, data infrastructure, distribution network and customer relationships built through Kredemy to create scalable, responsible and innovative new age financial solutions across multiple segments. Private Limited Company incorporated NAA Yes We are applying to IITACB Incubator to leverage its strong ecosystem, institutional credibility, mentorship and access to industry and technology networks to accelerate Kredemy’s growth. As we build Kredemy into a technology-driven financial services company with a long-term vision of becoming an NBFC, we believe the right incubation ecosystem [especially related to education] can significantly strengthen our business model, technology, regulatory understanding and execution capabilities. During the programme, we wish to create a network, learn and refine our product and offerings and get investor, network and funding connect. Yes Kredemy can leverage the Bommasandra industry hub and the broader Bangalore market to expand its education payments and financing ecosystem. The large employee and business base provides a strong potential customer segment, particularly salaried parents and families seeking convenient and flexible ways to manage school and higher-education expenses. We can also build relationships with schools, colleges, employers and local institutions to expand Kredemy’s fee-payment, credit-card, EMI and education-financing solutions. Bengaluru’s strong technology and fintech ecosystem can further help us access relevant technology, talent, financial partners and institutional relationships. No If given an option, virtual incubation will be our first choice. Yes Supporting feature For frontend, we are using Next.JS while our backend is built on Java. Our database is supported by PostgreSQL Kredemy’s data advantage is built through its integrated education-finance ecosystem. As users and institutions interact with Kredemy for fee payments, EMI options, credit-card-based fee payments and education financing, the platform can build a structured understanding of education-related payment behaviour, including fee cycles, payment patterns, institution profiles and financing requirements. Kredemy’s defensibility comes from building an integrated ecosystem rather than offering a standalone fee-payment or financing product. By bringing together educational institutions, parents, students, fee payments, credit-card payments, EMI solutions and education financing on one platform, we create multiple points of engagement and a strong network effect. Our objective is to build Kredemy on a high-availability, API-driven and scalable architecture capable of supporting large volumes of fee financing and financial transactions. As we scale, we will continuously benchmark these metrics against industry standards and leading fintech platforms to identify and address performance gaps. Kredemy treats data privacy, regulatory compliance and security as core components of the product architecture rather than as post-launch requirements. Since the platform handles education and financial information, we follow a privacy-by-design and security-by-design approach, with appropriate access controls, encryption, secure API integrations, audit trails, data minimisation and controlled access to sensitive information. Regular testing and vulnerability assessment will help us ensure that we do not compromise on platform security. NA Kredemy operates in the education payments and financing ecosystem, where regulatory requirements are an important consideration. Potential changes in RBI guidelines, payment regulations, data protection, KYC/AML or digital lending frameworks may require adjustments to our products or processes. At 10x scale, the primary areas requiring strengthening would be infrastructure capacity, database performance, monitoring and customer support operations rather than the core product itself. While the architecture is build using scalability infrastructure and technology, we may face challenges where human intervention is required. As of now, we don't require a in-house deep-tech team. NA We plan to continuously improve Kredemy’s technology through data-driven monitoring, user feedback, regular testing and continuous optimisation. Key performance metrics such as uptime, response time, transaction success rates, error rates and system capacity will be monitored regularly to identify bottlenecks and improvement areas. We are building for India and have vision to expand to global markets 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/IJ3Y9tf6sWcb-Kredemy.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/IJ3Y9tf6sWcb-Kredemy.pdf Kredemy is an impact-focused fintech addressing a fundamental gap in India’s education ecosystem: education finance is highly fragmented and significantly underserved. At the school level, organised financing options are negligible, while at the higher-education level, financing is largely concentrated around prestigious institutions and select professional courses and degrees. This leaves a large segment of families without convenient and flexible ways to manage one of their most significant household expenditures. There is also a clear gap in everyday credit. Consumers have dedicated credit-card solutions for shopping, dining, fuel, entertainment and travel, yet there is no comparable mainstream credit card ecosystem built around education, despite education being a recurring and substantial expense for most households. Kredemy aims to bridge this gap by bringing fee payments, credit-card-based payments, EMI options and education financing onto a single platform. Our mission is to make education expenses more manageable and financing more accessible, while helping educational institutions receive payments in a timely and predictable manner. In the long term, we want to build an inclusive education-finance ecosystem where access to financial flexibility is not determined by the institution a student attends or the course they pursue, but is available to a much broader section of Indian families. NA NA checked
Aug 17, 2026 @ 8:20 PM Deepika Deepika deepika@livegracious.co.in https://www.linkedin.com/in/deepikabsingh/ https://livegracious.in/ +919910100537 Deepika - CEO, IIT Roorkee engineer, IIM Kozhikode MBA, ex-Tata & Aequitas Investments; Rashi Atry: COO of Live Gracious, leading operations and GTM. Product leader with 13+ years across Dream11 (130M+ users), Naukri and interface.ai. At TatvaCare she launched MyTatva, a chronic-disease patient app, bringing direct healthtech and AI product experience to women's preventive care. We met through work colleague references and bounced off ideas each other for the initial 3 months and then made a decision to work together fully and have been doing so for last 7 months. All Our biggest strength is how cleanly our minds divide the work. I bring clarity: the vision, the direction, and a deep, lived understanding of the woman we build for. Rashi turns that clarity into action. She has spent 13 years shipping products at scale, and she converts direction into roadmaps, execution and momentum. The underlying feeling is trust. I can hand her a direction and know it will become something real, and she can push back on my thinking without ego. That is why we move fast and rarely stall. LVGR Wellness Pvt Ltd/ Live Gracious https://livegracious.in/ Bengaluru Live Gracious is a women’s health platform for women navigating chronic hormonal and metabolic conditions such as PCOS, thyroid disorders and insulin resistance. It brings together a woman’s symptoms, health history, lab reports, treatments, doctors and everyday life into one continuous health journey—helping her understand what is happening in her body, make better decisions between appointments, and have more informed conversations with her doctors. Women with chronic hormonal and metabolic conditions are forced to manage a complex, interconnected health journey through fragmented symptoms, reports, doctors, treatments and daily-life experiences—without a single place that connects them. Live Gracious is a two-sided platform built around continuity of care. For doctors, it is a clinical continuity platform that captures the full patient journey, including what happens between consultations. For women, an AI companion turns everyday health experiences into personalised guidance and structured context for their doctors. Together, they create one longitudinal record connecting the woman, her everyday health and her care team. 1. Built for the full care journey, not the consultation Captures what happens between appointments—the missing layer in traditional clinical records. 2. A true two-sided care loop The woman's everyday health data feeds the doctor; the doctor's care plan feeds back into the woman's daily journey. 3. Fertility as a high-intent GTM wedge Fertility naturally brings together hormonal, metabolic and reproductive health, giving us a high-need entry point into a much larger women's-health platform. 4. Longitudinal data moat Over time, we build a structured record of symptoms, interventions, clinical data and outcomes—not just static medical history. 5. Doctor-led distribution Embedding into clinical workflows creates a B2B2C acquisition channel and strengthens retention on both sides. 6. Context-powered AI Our AI isn't another generic health chatbot. It operates on a woman's longitudinal clinical + lived-experience context and translates it into actionable guidance and doctor-ready information. 7. Expandable women's-health infrastructure The same continuity layer can support multiple chronic hormonal, metabolic and reproductive journeys without rebuilding the platform for each condition. Users Users, Signups Indian women of reproductive age who are actively thinking about pregnancy within the next 1–2 years and are engaging with their reproductive, hormonal or metabolic health. This includes two important groups: A. Diagnosed PCOS thyroid disorders insulin resistance/metabolic issues endometriosis and related reproductive conditions, potentially later fertility/subfertility diagnosis B. Undiagnosed / seeking answers irregular periods unexplained symptoms difficulty conceiving weight/metabolic changes abnormal labs recurring symptoms questions about whether something may affect future fertility Indian women of reproductive age ~386M Women in 1–2 year fertility-planning journey + digitally reachable ~18M SOM Realistically acquirable women in initial 3–5 year horizon ~300K–500K Realistically acquirable women in initial 6-12 months horizon ~300K–500K Our primary revenue comes from premium subscriptions paid by women for continuous, personalised health support. Doctors can subscribe to the clinical continuity platform, creating a secondary B2B revenue stream and strengthening the two-sided product. Over time, employers and insurers can sponsor access for their women members or employees. Live Gracious competes across women’s health, fertility and digital healthcare. Consumer platforms such as Flo, Clue and Premom help women track cycles, symptoms and fertility, while healthcare platforms such as Practo and MediBuddy facilitate access to doctors and digital care. However, these solutions largely address individual parts of the journey. Live Gracious differentiates by connecting a woman’s everyday health experience, longitudinal health data and doctors into one continuous care journey—bridging the gap between what happens at the consultation and what happens between consultations. We acquire women through a digital-first, fertility-led GTM, using high-intent content and search around fertility, PCOS, thyroid and preconception health, supported by social and community-led education. We use OB/GYNs and fertility specialists as a trusted distribution channel, with doctors introducing Live Gracious to women as part of their ongoing care. Over time, employer and insurer partnerships can provide additional B2B2C distribution. The initial wedge is women actively planning pregnancy within the next 1–2 years, giving us a high-intent audience that is already seeking information, tracking their health and engaging with doctors. Our GTM strategy is fertility-led and consumer-first. We start with women who are planning pregnancy within the next 1–2 years, particularly those navigating PCOS, thyroid, insulin resistance or unexplained symptoms, because they have a high-intent need for continuous health support. We acquire them through high-intent digital content, search, social and communities, while using OB/GYNs and fertility specialists as trusted distribution channels. Once we establish engagement in the fertility journey, we expand the relationship into broader hormonal and metabolic health, making Live Gracious a long-term health companion rather than a single-purpose fertility product. To become the continuous health layer for women—starting with fertility and hormonal/metabolic health, and eventually supporting women across life stages from preconception and pregnancy through postpartum and later-life health. Live Gracious will connect a woman's everyday health, longitudinal data and care team, shifting women's healthcare from fragmented, episode-based care to continuous, personalised care. Pvt Ltd and DPIIT registered 8 lakhs Yes We are applying to IITACB at a stage where Live Gracious is moving from defining the problem and product to building and validating a technology-led solution at scale. Our biggest needs are strong AI and product expertise, clinical and healthcare validation, and access to the right mentors, industry partners and investors. IITACB's unique combination of the IIT ecosystem, experienced alumni and industry mentors, research and industry collaborations, and investor access makes it particularly relevant to us. We want to use the programme to build a technically robust and clinically credible product, validate our model with women and healthcare professionals, and develop the partnerships and capabilities needed to take Live Gracious from an India-first women's health solution to a scalable healthcare platform. During the programme, our primary goals are to secure the funding and ecosystem support needed to build and validate Live Gracious. We want to use the programme to develop our AI and longitudinal health platform, launch pilots with women and doctors, validate the woman–doctor continuity model, and establish strong clinical and technology foundations. We also want to leverage IITACB’s mentorship, industry and healthcare networks to strengthen our product and business model, while using the programme and investor ecosystem to prepare for and raise our next round of funding. Ultimately, we want to leave the programme with a validated product, early user and clinical traction, a stronger technology foundation, and the capital and partnerships required to scale across India. Yes Bengaluru gives Live Gracious access to one of India's strongest technology, healthcare and startup ecosystems, while the Bommasandra industrial and business hub provides proximity to corporates and potential institutional partners. We see an opportunity to leverage Bengaluru for customer and partner discovery, technology talent, healthcare partnerships and early B2B2C opportunities with employers and insurers. IITACB can be a critical bridge into this ecosystem through its IIT alumni, industry, academic and investor networks. We particularly want to leverage IITACB for AI and technology mentorship, healthcare and industry partnerships, product and clinical validation, and investor access to help us raise the capital required to build and scale Live Gracious across India. IITACB's existing focus on tech-driven startups, industry-academia collaboration and healthcare/MedTech makes it particularly relevant to our stage and ambition. Yes We would use IITACB’s infrastructure as our base for building and validating Live Gracious, particularly as we develop our technology and begin working with healthcare and industry partners in Bengaluru. The workspace would give our team a professional environment to collaborate, conduct product and user-validation sessions, and engage with mentors, researchers and other startups in the ecosystem. We would also like to leverage relevant meeting, event and collaboration facilities for investor discussions, partner meetings and workshops. Beyond the physical infrastructure, the proximity to the IITACB ecosystem would be valuable for accessing technical expertise, healthcare and industry networks, and potential talent as we build Live Gracious. Yes Supporting feature Grace, our AI Clinical Assistant, runs on OpenAI's API [confirm current model — GPT-4o/4.1/5, etc.] and is positioned as a pre-appointment prep tool evolving into a personalized health companion. It sits alongside our core B2B SaaS platform — EHR, IVF cycle/follicular tracking, and voice prescription capture — built for fertility and OB-GYN clinics. Primary database: MongoDB through Mongoose. Vector database: MongoDB, normally MongoDB Atlas Vector Search. Evaluation database: Neon Postgres. Backend hosting: AWS ECS on Fargate. Frontend hosting: Vercel. Object storage: AWS S3. CMS: Sanity. API edge/DNS: Cloudflare and an AWS Application Load Balancer. Primary Al provider: OpenAl. Secondary Al provider: Anthropic. Clinical transcription: EKA Care EkaScribe. Longitudinal patient records across cycles/consults that most point-solution competitors don't capture; structured clinical + community/context data (symptom tracking, treatment adherence) linked to outcomes. The IVF, follicular data details that are added by the doctor based on the patients cycle history, family health history, etc are the data points that are captured 1. dual-sided platform — B2B clinic workflow + B2C patient engagement — creates network effects most single-sided competitors lack; 2. clinical sign-off/compliance rigor (Dr. Shreshtha's review process, DPDP pseudonymisation standard) as trust moat; We are solving behavioural and infrastructure problem, tech is a way to fill the gap than to innovate. DPDP Act compliance with pseudonymisation standard applied to patient data; clinical content and AI outputs are gated — Grace carries an explicit disclaimer that it doesn't diagnose or replace a doctor. ABDM (Ayushman Bharat Digital Mission) as an enabling government digital health infrastructure; possibly relevant government health screening initiatives, ART Act Drugs and Magic Remedies Act exposure for medication-specific content; NMC Code of Ethics conflict risk around fee-splitting/referral commissions in partner integrations — under active resolution; ABDM/ABHA certification dependency for the Pinnacle Biomed government contract (M1 required within 90 days of execution); general DPDP Act compliance risk for patient data handling. Traffic does not. That is the honest and slightly boring part of the answer. The backend is stateless containers on AWS Fargate with auto-scaling behind a load balancer, so capacity follows demand without anyone touching a server. The data layer is fully managed and scales independently, with our operational database and vector store separately addressable. All six frontends sit on a global CDN, which means the patient-side traffic that grows fastest never touches our compute at all. There is no single machine to fall over, no queue to saturate, no disk to fill. Ten times the concurrent users is a capacity event, not an engineering project. Unit economics scale linearly too. We deliberately architected Grace around small, fast models for routing and generation — reserving the expensive frontier model for the safety check where it actually matters — so cost per conversation stays flat as volume grows rather than becoming the constraint that quietly kills consumer health AI products. What genuinely gets harder at 10x is the intelligence, not the infrastructure. Grace's quality today is tuned against real patient conversations we have observed. That has been exactly the right way to build — improve against real usage rather than imagined usage. But it means that at ten times the volume, the tail of what women ask widens faster than the volume itself grows. Perimenopause and menopause. Adolescent health. Post-partum. Male-factor and secondary infertility. Pregnancy loss. Regional languages and code-mixed Hinglish. Questions carrying risk in shapes we have not yet seen. The failure mode is not downtime. It is Grace giving a merely generic answer to a woman who needed a specific one, at 2am — and never earning her trust back. That failure is silent. It does not page an engineer. And it is the only one that actually costs us the business. This is a solved problem in principle and an instrumented one in practice. We already have the full loop in production: De-identified conversation export from live traffic — built, shipped, fails closed. Analysis of the real query distribution to find where our coverage thins. Rubric expansion in our clinical evaluation console, authored by our clinician. Graded regression testing against a committed baseline before any behaviour change ships. Scaling that loop to 10x is a matter of cadence and clinical review capacity: automating the clustering step, growing our graded case library from tens into hundreds with deep per-persona coverage, sampling production traffic for continuous online evaluation, and systematically triaging the patient feedback we already collect on every response. It is resourcing and clinical throughput — a second clinical reviewer is worth more to us at that stage than a second infrastructure engineer. Why we consider this a strength rather than a risk. Most teams asked this question answer with servers, because servers are the only part of the system they have instrumented. We can answer it about the intelligence, with numbers, because we built the measurement apparatus before we needed it. Knowing precisely where your AI thins out — and having the pipeline to close that gap systematically rather than anecdotally — is the difference between a health AI product that survives scale and one that quietly degrades until patients stop trusting it. Yes, we have an in-house deep-tech team with expertise across: * AI agent development (conversational architecture, context and memory management, workflow and tool integration, guardrails, evaluation pipelines, and continuous performance improvement) * SLM fine-tuning and optimization (dataset preparation, domain adaptation, benchmarking, and inference optimization) * Data engineering (building internal datasets, data pipelines, quality validation, and processing systems) * Infrastructure engineering (scalable deployment, monitoring, reliability, and observability) * Frontend and backend engineering (web and mobile interfaces, APIs, system integrations, and application architecture) We have also built our own observability platform for the conversational-agent layer, enabling us to evaluate interactions, identify failure patterns, and continuously improve agent performance. We are not currently using any external datasets. Our data has been developed internally through usage of our B2C application. We have also built a proprietary observability platform for our conversational agent layer, which enables us to monitor performance and continuously improve the system. For the frontend and backend, we use standard open-source technologies and libraries, including React and Express.js, under their respective open-source licences. All proprietary product logic, internally generated data, and custom infrastructure are owned by us. For our B2C product, we are developing a health-focused AI conversational agent. We are building an internal dataset based on interactions with our existing users, which is reviewed and evaluated in collaboration with doctors. These evaluations help us continuously improve the agent’s accuracy, relevance, and usefulness to users. For our B2B product, we work closely with doctors to understand their workflows, challenges, and evolving needs. Their ongoing feedback directly informs our product development and helps us continuously improve the technology and deliver greater value. Currently we are building for India but can be easily scalable globally. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/2A95pjd1uzTc-IITBCold-send-pitch-deck-Presentation.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/2A95pjd1uzTc-IITBCold-send-pitch-deck-Presentation.pdf https://drive.google.com/drive/folders/1fR_7cWrNGa78KwkbMS-O52v7JUaX9hJO Yes. Live Gracious is fundamentally mission-driven because we are building to address a structural gap in women's healthcare: women living with chronic hormonal, metabolic and reproductive health challenges often have to navigate fragmented information, disconnected consultations and manage their health largely on their own between appointments. Our mission is to make women's healthcare more continuous, personalised and informed. By connecting a woman's everyday health experience, longitudinal health data and doctors, Live Gracious aims to help women understand and actively manage their health while enabling doctors to make better-informed decisions with greater context. We are starting with women planning pregnancy within the next 1–2 years, particularly those navigating conditions such as PCOS, thyroid disorders and insulin resistance, and aim to expand across women's health and life stages over time. The impact we seek is not just better access to information, but a shift from fragmented, episodic care to continuous care—helping women make better decisions earlier and enabling more informed healthcare interactions throughout their lives. Yes. Live Gracious is a women-led startup founded by women, building specifically for women's health. Women remain underrepresented among technology founders and in the broader startup ecosystem, particularly in building technology-led companies in healthcare. Our lived understanding of the gaps women face in navigating hormonal, reproductive and metabolic healthcare also directly informs the problem we are solving. NA checked
Aug 17, 2026 @ 7:15 PM Bharat Vohra bharat@linobud.com https://www.linkedin.com/in/bharat-vohra-63443b1b1?utm_source=share&utm_campaign=share_via&utm_content=profile&utm_medium=ios_app +919779933422 Lino team is led by the Founder and CEO, who drives the overall vision, product strategy, and business growth. Supporting this vision is a passionate and skilled team across key domains. The product and technology team, headed by a CTO, focuses on hardware development, AI integration, and the app ecosystem. A creative content and learning team develops child-friendly educational content, storytelling experiences, and interactive modules. The design team ensures that every Lino bot is visually appealing, toy-like, and child-safe. A marketing and brand team manages promotions, community building, and customer engagement, while a sales and partnerships team handles distribution, retail partnerships, and collaborations with educational brands. Operations, finance, and customer support teams ensure smooth execution, budgeting, manufacturing, logistics, and happy parent–child experiences. Together, this team is building the future of playful, smart learning toys with the Lino family. My co-founder and I have known each other for several years and have been working together on Lino since its inception. We started collaborating when we identified the need for a more personalized and emotionally engaging AI companion for children. Since then, we have worked closely across product development, design, customer validation, and business strategy, combining our complementary skills to build and launch Lino. All Teamworka dn discussions on every topic Lino Bud https://www.linobud.com Amritsar Lino is a smart, interactive toy designed to be a child’s best buddy for learning, fun, and emotional growth. Blending playful design with AI technology, Lino features an on-screen animated mascot that talks, listens, tells stories, plays games, and helps children learn in a natural, engaging way. It comes with a dedicated app for parents to manage content, track usage, and ensure age-appropriate learning. With built-in voice recognition and offline capabilities, Lino works safely and intuitively, even without constant internet access. Today’s children are growing up surrounded by screens — from smartphones to tablets — often spending hours passively watching content. This not only affects their attention span and creativity but also limits real interaction and emotional development. For mothers, especially in Indian households, this creates a daily struggle. While they want their children to learn and be entertained, they also seek safe, healthy alternatives to screen time. Many mothers end up sacrificing their own time to keep their children engaged, often feeling guilty or overwhelmed. Meanwhile, the toy market is flooded with outdated, non-interactive options that haven’t evolved in decades. There’s a clear gap for something modern, affordable, and meaningful. Lino is designed to replace passive screen time with meaningful, interactive play — giving children a fun, educational companion and mothers the peace of mind they’ve been waiting for. Lino features an AI-powered on-screen mascot that talks, listens, plays, teaches, and grows with the child. It engages kids in storytelling, games, songs, and learning activities — all without needing a phone or tablet. This keeps children mentally stimulated and emotionally engaged, while also reducing screen dependency. For mothers, Lino becomes a helping hand — keeping kids occupied in a safe, healthy way, allowing them more personal time and reducing daily stress. The dedicated app lets parents control content, track usage, and ensure the experience is age-appropriate Lino combines AI-powered emotional companionship, personalized learning, and multilingual interaction in a single device designed specifically for children aged 2–6. Unlike traditional educational toys or generic AI assistants, Lino adapts to each child's interests, learning pace, and emotional needs through ongoing interactions. Our focus on 16+ Indian languages, culturally relevant content, parent controls, and emotional development makes the product uniquely suited for Indian families. The defensibility comes from our proprietary child-focused AI experience, growing dataset of child interactions, content ecosystem, hardware-software integration, and deep understanding of the Indian parenting market, creating a personalized experience that becomes more valuable over time. Users Users Lino is designed for parents of children aged 2–6 years, particularly working parents seeking a safe, engaging, and educational AI companion for their child. Our primary target customers are families in urban and Tier 2 cities who value early childhood development, personalized learning, emotional well-being, and technology-enabled parenting. Secondary customers include preschools, daycare centers, and early learning institutions looking to enhance children's learning and engagement experiences through AI-powered interactive tools. 2.3B$ 1.2B$ 500M$ Lino operates on a hybrid revenue model consisting of device sales, recurring subscriptions, and digital content services. Customers purchase the Lino device as a one-time hardware purchase, followed by a monthly or annual subscription that unlocks AI conversations, personalized learning experiences, stories, games, and continuous content updates. Additional revenue opportunities include premium content packs, educational modules, brand partnerships, and future add-on accessories. This model enables both upfront revenue from hardware sales and recurring revenue through subscriptions, creating long-term customer value and retention. Miko , Wippi, SNorble , We acquire customers through a combination of digital marketing, parent communities, influencer partnerships, e-commerce platforms, and strategic partnerships. Our primary channels include Meta and Google advertising, parenting groups, mom communities, content marketing, and collaborations with child psychologists, educators, and parenting influencers. We also leverage marketplaces such as Amazon and quick-commerce platforms, along with referral programs and word-of-mouth from early adopters. As we scale, we plan to expand through preschools, daycare centers, and offline retail partnerships. Our go-to-market strategy focuses on digital-first customer acquisition through parenting communities, social media, influencer partnerships, and performance marketing. We are initially targeting working parents of children aged 2–6 through Meta ads, mom communities, parenting influencers, and content-led campaigns. Sales will be driven through our website, Amazon, and quick-commerce platforms, supported by referrals and word-of-mouth from early adopters. As we scale, we plan to expand through preschool partnerships, daycare centers, offline retail channels, and strategic collaborations with educators and child development experts. Our vision is to build the world's most trusted AI companion ecosystem for children, helping millions of families support their child's learning, emotional development, creativity, and well-being. We aim to create a personalized AI platform that grows with every child, combining hardware, software, and content to deliver meaningful, safe, and engaging experiences across languages and cultures. In the long term, we envision Lino becoming a global category-defining brand in AI-powered childhood development and family technology. Yes 0 Yes We are applying to IITACB Incubator to accelerate the growth of Lino through access to a strong innovation ecosystem, mentorship, industry connections, and investor networks. As we prepare to scale manufacturing, strengthen our AI capabilities, and expand market reach, we believe IITACB's support can help us validate our product faster, refine our go-to-market strategy, and connect with strategic partners. The incubator's focus on technology-driven startups and its ecosystem of mentors, researchers, and investors aligns well with our vision of building a globally impactful AI companion platform for children. Funding Yes i am Lino can significantly benefit from the Bommasandra industrial ecosystem and the Bangalore market. Bommasandra's strong presence in electronics manufacturing, hardware supply chains, product engineering, and industrial partnerships can help us optimize production, reduce costs, improve quality control, and accelerate product iterations. Bangalore also provides access to a large base of technology talent, AI expertise, early adopters, parenting communities, schools, and strategic partners that can support both product development and market expansion. IIT ACB can play a critical role by providing mentorship, industry connections, technical expertise, pilot opportunities, and access to investors. The incubator's network can help us establish manufacturing partnerships, strengthen our AI and product roadmap, validate our solution with educational institutions, and accelerate fundraising efforts as we scale Lino into a leading AI companion platform for children. Yes We intend to leverage IITACB's infrastructure, mentorship, and innovation ecosystem to accelerate the development and commercialization of Lino. Access to co-working space, meeting facilities, technical resources, industry experts, and startup support services will help us collaborate more effectively, engage with potential partners and customers, and strengthen our product roadmap. We also look forward to leveraging IITACB's network for manufacturing partnerships, talent acquisition, investor introductions, pilot opportunities, and strategic guidance as we scale Lino across India and expand into global markets. Yes Core engine Lino is built on a hardware-software-AI architecture comprising an embedded device with a display, microphone, speaker, and connectivity modules. The device uses speech recognition, conversational AI, and personalized content delivery to interact with children. A cloud backend manages user profiles, content, subscriptions, analytics, and OTA updates, while a dedicated parent app provides monitoring, controls, and personalized insights Through continuous interactions on Lino, we are building a proprietary dataset of child engagement patterns, learning preferences, conversation flows, and content interactions across multiple Indian languages. This data enables us to personalize experiences, improve recommendations, optimize content delivery, and enhance AI interactions for children. Over time, this creates a unique data advantage that is difficult to replicate and strengthens our ability to deliver highly personalized and culturally relevant experiences for young children. Lino's defensibility lies in its unique combination of AI-powered emotional companionship, personalized learning, regional language support, and a tightly integrated hardware-software ecosystem built specifically for children aged 2–6 years. Unlike generic AI assistants or educational toys, Lino continuously adapts to each child's interests, engagement patterns, learning pace, and developmental needs. Our growing library of child-focused content, multilingual capabilities, proprietary interaction data, and parent-centric controls create a personalized experience that becomes more valuable over time. This combination of technology, content, data, and hardware integration creates strong barriers to entry and is difficult for competitors to replicate. We evaluate Lino using a combination of engagement, AI performance, reliability, and customer satisfaction metrics. Key metrics include average daily engagement time, conversation completion rates, speech recognition accuracy, AI response latency, content consumption, repeat usage, and subscription retention. From a reliability perspective, we monitor system uptime, crash rates, OTA update success rates, battery performance, and hardware failure rates. During pilot testing, children demonstrated over 1 hour of average daily engagement, with strong repeat interactions and high parent satisfaction. We continuously benchmark these metrics against leading AI companion and educational toy platforms to ensure a safe, engaging, and reliable experience for children. Lino is designed with privacy, safety, and compliance as core principles. We follow a privacy-by-design approach, collecting only the data necessary to deliver personalized experiences and improve product functionality. All user data is stored securely using industry-standard encryption and access controls. For child users, parental consent is obtained before account creation and data collection, and parents are provided with controls to access, manage, or delete their child's data. We maintain secure cloud infrastructure, regularly monitor system security, and work with trusted technology providers for AI and cloud services. Our policies and practices are designed to align with applicable data protection regulations, including child data protection requirements, while ensuring a safe and transparent experience for families. As an AI-powered product designed for children, Lino operates in a regulated environment that includes data privacy, child safety, consumer protection, and product compliance requirements. We have proactively incorporated compliance considerations into our product design and operations, including parental consent mechanisms, secure data handling practices, child-safe content policies, and applicable hardware certifications. We continuously monitor evolving regulations and work to ensure alignment with relevant standards and legal requirements. At present, we do not foresee any material regulatory risks that would significantly impact our ability to develop, market, or scale the product. At 10x scale, the primary challenges would be cloud infrastructure costs, AI processing capacity, content delivery, customer support operations, and supply chain management. Increased user interactions would require scaling our AI infrastructure, data storage, and personalization systems to maintain low response times and a seamless user experience. On the hardware side, manufacturing, inventory planning, quality control, and after-sales support would need to scale significantly. We are designing our architecture with cloud scalability, OTA updates, modular content delivery, and automated support processes to ensure that growth can be managed efficiently without impacting product performance or customer experience. Yes. We have an in-house team focused on AI, embedded systems, product development, and cloud infrastructure. The team has expertise in conversational AI, speech recognition, natural language processing, mobile and embedded application development, cloud services, and hardware-software integration. Our capabilities include developing AI-powered child interactions, personalization systems, content delivery platforms, parent applications, and connected device experiences. The team is supported by advisors with experience in technology, AI, cloud transformation, consumer products, and business scaling. Lino utilizes a combination of proprietary content, licensed third-party AI services, and open-source software components. Our technology stack incorporates open-source frameworks and libraries for application development, embedded systems, and AI integration, used in accordance with their respective licenses. We also leverage licensed cloud, speech, and AI services from established providers to power conversational experiences and personalization features. Our proprietary assets include the Lino product concept, child-focused interaction design, content library, personalization logic, user experience workflows, and platform architecture. We are continuously developing and expanding our own content, datasets, and engagement models derived from product usage and user interactions. Any intellectual property, trademarks, copyrights, and future patentable innovations related to the Lino platform are owned or intended to be owned by the company. Formal IP protection activities are ongoing as the product and technology mature. We continuously improve Lino through a combination of user feedback, AI model optimization, content expansion, analytics-driven insights, and regular software updates. Product performance is monitored using engagement metrics, speech recognition accuracy, response latency, retention rates, and customer feedback. We leverage real-world usage data to refine personalization, improve conversational quality, and enhance learning experiences. Our cloud-based architecture enables regular OTA (Over-the-Air) updates, allowing us to introduce new features, content, and performance improvements without requiring hardware changes. As our user base grows, our proprietary interaction data and content ecosystem will further strengthen the intelligence and effectiveness of the platform. Both 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/s9Q8xJvOumpD-Lino-Deck.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/s9Q8xJvOumpD-Lino-Deck.pdf https://drive.google.com/file/d/1Tob1w9tukFa95guMSEl8rEvge4--GiO3/view?usp=drive_link Yes, Lino is a mission-driven startup focused on helping children build healthier relationships with technology through meaningful, interactive play. We believe that while AI is becoming a part of everyday life, children should experience it in a way that encourages curiosity, creativity, learning, and emotional development rather than passive screen consumption. Our mission is to bring children back to engaging with toys by combining the benefits of physical play with the intelligence of AI. Through personalized conversations, stories, games, and learning experiences, Lino aims to support childhood development while creating a safe, educational, and engaging companion that grows with every child. Yes IIT Ropar checked
Aug 17, 2026 @ 7:11 PM Deepanshu Sahu deepanshusahu621@gmail.com https://www.linkedin.com/in/deepanshusahu22/ +917415702217 Deepanshu Sahu – Co-founder & CEO: B.Tech in Mechanical Engineering, leading business strategy, fundraising, partnerships, grant applications, marketing, customer discovery and go-to-market execution. Nitin Hingwe – Co-founder & CTO: B.Tech in Chemical Engineering, leading the complete technology development of Dronosaur, including drone electronics, avionics, PCB design, embedded systems, AI models, autonomous flight features, prototyping and product testing. We met during our B.Tech First Year in a random group chat, and then we started participating and collaborating on technical projects while in college. Our shared interest in drones, electronics and building real-world products eventually led us to start Dronosaur together. We have worked closely as a team from initial research and concept validation to prototype development, incubation and fundraising. Over this period, we have learned to divide responsibilities clearly, resolve technical and business challenges together, and continue executing through repeated iterations and setbacks. 2 Our biggest strength is the combination of strong technical execution and business capability within the founding team. Nitin leads the complete technology stack, from drone hardware, electronics and embedded systems to AI and autonomy, while Deepanshu leads business strategy, fundraising, partnerships, customer discovery and go-to-market execution. This allows us to develop the product and validate its commercial potential simultaneously. We also complement each other in decision-making and have remained resilient through technical failures, multiple prototype iterations and startup rejections. We do not just have an idea; we have the complementary skills and persistence required to convert it into a market-ready product. Dronosaur Private Limited https://dronosaur.in/ Ropar Dronosaur is building an intelligent autonomous videography drone that enables creators, solo travellers, fitness professionals and businesses to capture professionally framed aerial content without requiring a drone pilot or camera crew. The drone can autonomously follow, track and film the user while maintaining cinematic framing. Capturing professional video currently requires a camera operator, drone pilot or repeated manual setup, making content production expensive, complicated and inaccessible. Existing consumer drones still demand constant piloting, shot composition and safety monitoring, preventing users from freely performing, travelling or presenting while filming themselves. Solo creators and small teams therefore struggle to capture dynamic, professionally framed footage independently. Dronosaur is developing a compact intelligent drone that acts as a personal aerial videographer. A user can select or lock onto themselves, and the drone autonomously follows their movement while maintaining suitable distance, orientation and cinematic framing. The system combines person and face tracking, AI-based composition, gesture commands, autonomous navigation and obstacle avoidance. Instead of continuously controlling the drone, the user can focus on the activity while the drone handles flight and filming. The product is being designed for creators, travellers, fitness professionals, events and small businesses that need high-quality content without hiring a dedicated operator. Unlike conventional drones that primarily provide flying hardware, Dronosaur is being purpose-built as an autonomous videography system. Its differentiation comes from the integrated development of drone electronics, embedded systems, edge-AI tracking, autonomous flight and intelligent camera framing. Our defensibility will be built through proprietary real-world flight and tracking data, continuously improved autonomy and framing models, custom hardware-software integration, and application-specific workflows for hands-free filming. This integrated technology stack is difficult to replicate through an off-the-shelf drone or a standalone tracking application. MVP Pilots Our primary customers are content creators, vloggers, solo travellers, fitness professionals and other individuals who need professionally framed videos without depending on a camera operator or drone pilot. Secondary customers include event teams, tourism businesses, real-estate professionals, production agencies and small businesses that regularly create visual content. ₹51 billion, representing approximately 3,40,000 potential customers at an estimated average selling price of ₹1.5 lakh per unit. ₹9.6975 billion, representing approximately 64,650 early-adopter customers in India across the creator, travel, fitness, event and professional-content segments. Year 1: ₹96.98 million from approximately 647 units, equal to 1% of SAM. Year 3: ₹290.93 million from approximately 1,940 units, equal to 3% of SAM. Year 5: ₹678.83 million from approximately 4,526 units, equal to 7% of SAM. Our primary revenue will come from direct sales of Dronosaur drones at an estimated price of ₹1.5 lakh per unit. Additional revenue streams will include batteries, accessories, spare parts, after-sales service and annual maintenance plans. In the future, we may introduce optional subscriptions for advanced AI videography, cloud storage and automated content-processing features. Our direct competitors include DJI’s compact camera drones and HOVERAir’s X1-series autonomous flying cameras. Indirect competitors include conventional consumer drones, smartphone gimbals, action cameras, professional drone pilots and camera operators. Dronosaur differentiates itself through hands-free operation, gesture-based control, intelligent subject tracking and autonomous cinematic framing. We will acquire customers through creator demonstrations, influencer seeding, user-generated content, product reviews, organic social media, performance marketing and founder-led content. Additional channels will include startup and creator events, referral programmes, partnerships with travel and fitness communities, and demonstrations through experience centres and selected retail partners. We will begin with controlled pilot testing and demonstrations among creators, travellers and fitness professionals to validate product performance and collect real-world feedback. We will then seed the product with more than 100 relevant creators to generate demonstrations, reviews and over 1,000 pieces of user-generated content. The initial commercial launch will follow a D2C model through our website, supported by pre-orders, digital marketing and EMI options. Physical experience and demonstration stores will first be established in Delhi, followed by expansion into other major Indian cities. After validating demand, we will scale through retail partnerships, creator communities and B2B sales to events, tourism, real estate and media-production teams. Our long-term vision is to make autonomous aerial videography accessible to anyone, regardless of their piloting or filmmaking experience. We aim to build Dronosaur into an intelligent personal videographer that understands the user, follows their movement and independently captures professionally framed content through gesture, voice and autonomous controls. Over time, we plan to develop a family of intelligent camera drones and an integrated AI content ecosystem serving creators, travellers, professionals and businesses. Our goal is to establish Dronosaur as a globally recognised Indian consumer-drone brand built around autonomous filming rather than manual piloting. Dronosaur is incorporated as a Private Limited Company in Madhya Pradesh. CIN: U62011MP2025PTC076871. We have raised ₹25 lakh in total external funding: ₹20 lakh through angel investment for 7.5% equity, ₹3 lakh grant from IIT Ropar–TBIF. Yes Dronosaur is transitioning from functional prototypes to a reliable, market-ready autonomous videography drone. We are applying to IITACB for technical and business mentorship, DFM and manufacturing guidance, testing support, access to Bangalore’s hardware ecosystem, industry partnerships and investor connections. The incubator can help us reduce development risks and accelerate our journey from prototype to pilot production and commercial launch. During the programme, we aim to finalise our market-ready MVP, validate autonomous tracking, gesture control, intelligent framing and obstacle avoidance through real-world testing, and optimise the product’s BOM and design for manufacturing. We also want to establish a reliable supplier and manufacturing network, prepare a pilot production batch, conduct customer pilots, develop our regulatory roadmap and become ready for seed investment and commercial launch. Yes. We are open to virtual participation and can travel to Bangalore for technical reviews, laboratory work, supplier meetings, product demonstrations, pilot programmes and investor sessions whenever physical participation is required. Bommasandra and Bangalore provide access to PCB manufacturers, electronics suppliers, precision-fabrication vendors, injection-moulding companies, battery partners, testing facilities and contract manufacturers required to develop and scale our drone. Bangalore’s creator, technology, tourism and startup ecosystem can also support customer discovery, product pilots and early adoption. IITACB can help through industry introductions, technical mentorship, laboratory and testing access, DFM and BOM optimisation, talent connections, pilot customers, manufacturing partnerships and investor access. Yes We will use IITACB as our Bangalore execution base for product development, mentor reviews, supplier coordination, customer meetings and investor interactions. We aim to leverage its workspace, laboratories, prototyping and testing facilities, industry network, meeting rooms and talent ecosystem to improve our drone’s reliability, optimise it for manufacturing, conduct demonstrations and coordinate pilot production with Bangalore-based partners. Yes Core engine The current prototype uses an onboard camera connected to a Raspberry Pi 5 with an AI accelerator for edge-based person, face and gesture detection, subject tracking and framing analysis. Python/C++, OpenCV and lightweight edge-inference models process the video locally. The AI layer converts the subject’s position and movement into tracking and framing errors. These are communicated through MAVLink to an ArduPilot-based flight controller, which controls the motors using flight-sensor feedback. The production architecture will move towards a Compute Module 5/custom carrier, custom power and flight electronics, additional obstacle sensors, autonomous failsafes and a mobile interface for target selection, filming modes and flight management. Our data advantage is early but structurally valuable. During prototype tests and pilots, we generate synchronised onboard video, subject movement, environmental conditions, flight telemetry, control response, framing error and failure-event data. Unlike public image datasets, this data connects what the camera sees with how the drone responds physically. It will help us improve target reacquisition, cinematic framing, motion prediction, obstacle handling and flight stability across different lighting, backgrounds, movements and Indian outdoor conditions. With consent, this data will be labelled and converted into a continuously improving proprietary dataset owned by Dronosaur. Our defensibility does not depend on a single AI model. It comes from the integrated development of drone electronics, embedded systems, edge-AI perception, autonomous navigation and intelligent videography. The moat will deepen through proprietary flight-and-video data, closed-loop tracking and framing algorithms, hardware-specific model optimisation, custom electronics, safety logic and real-world system tuning. Every deployed unit can generate additional performance data and edge cases, enabling continuous improvement. This combined hardware, software, data and manufacturing knowledge is substantially harder to replicate than an off-the-shelf drone with a standalone tracking application. We evaluate the system using repeatable indoor and outdoor test scenarios and metrics including person-detection precision and recall, tracking success rate, identity switches, target-reacquisition time, inference FPS, end-to-end response latency, subject-framing error, following-distance error, hover drift, command-response time, obstacle-detection rate, flight completion rate, battery endurance and thermal performance. We also test performance across different lighting, backgrounds, speeds, wind conditions and temporary subject occlusions. Results will be benchmarked against manual operation and comparable compact autonomous camera drones under identical test routes. Acceptance thresholds will be frozen before pilot production. Dronosaur is being designed using a privacy-by-design approach. AI inference will primarily occur on-device, reducing the need to upload raw video or facial data. Cloud backup or analytics will be optional and based on clear user consent. We will minimise data collection, provide user-controlled storage and deletion, encrypt transferred and stored data, restrict internal access and use secure authentication, signed firmware and controlled OTA updates. Target-identification data will be session-specific wherever possible rather than becoming a permanent facial database. Product policies will address recording consent, bystander privacy and compliance with India’s DPDP framework and GDPR when entering applicable global markets. India’s Drone Rules and Digital Sky framework provide a structured path for drone classification, certification and operation. The Production Linked Incentive scheme for drones and drone components, Make in India, Startup India and government-backed deep-tech grants can support domestic design, manufacturing and commercialisation. We will assess eligibility for individual schemes instead of assuming automatic benefits. Yes. Regulatory risks include changes in DGCA drone regulations, airspace restrictions, product classification, type-certification and registration requirements, radio-frequency approvals, battery and charger safety, data-protection obligations and restrictions on where autonomous filming can be conducted. If the final drone remains approximately 500 grams, the relevant small-category requirements must be addressed. We will mitigate these risks through early regulatory consultation, certified components, documented flight testing, geofencing, return-to-home and emergency-landing failsafes, product traceability and a compliance roadmap before commercial launch. At 10× scale, the first constraints will likely be manufacturing consistency, component availability, calibration, flight-testing capacity, battery quality, repair turnaround and customer support—not the AI inference itself. We will address these through design-for-manufacturing, multiple approved suppliers, incoming-component inspection, standardised assembly procedures, automated end-of-line testing, calibration rigs, serial-level traceability and a spare-parts and service network. On the software side, we will require automated data ingestion, model-version control, staged OTA deployment, fleet monitoring and rollback mechanisms to prevent a defective update from affecting all units. Yes. Nitin Hingwe, Co-founder and CTO, leads drone electronics, avionics, PCB development, embedded systems, flight-control integration, AI deployment, autonomy and product testing. Also, Nitin works on AI and computer vision development. Renuka Parmar and Mantasha Khan contribute to battery, power-management and BMS development. Together, the team covers electronics, embedded systems, computer vision, autonomous flight, power systems, prototyping and integration. We will supplement the team with specialists in aerodynamics, industrial design, safety certification and production engineering as we move towards pilot manufacturing. The prototype uses internally captured and consented video, flight telemetry and system-response data, along with permitted public human-detection, tracking and pose datasets for initial model development. Open-source components include OpenCV, the Linux/Python/C++ ecosystem and ArduPilot with MAVLink-based communication. Edge-inference tools are selected according to the onboard accelerator used in each prototype. All dependencies will be documented in a software bill of materials and used according to their respective licences, including any copyleft obligations. Dronosaur owns its original recordings, annotations, model fine-tuning, tracking and framing logic, integration code and custom hardware designs. No patent has been filed yet; patentable elements are being evaluated. We will continuously collect consented real-world edge cases from testing and pilots, including fast motion, occlusion, low light, complex backgrounds, wind and subject loss. These cases will feed an active-learning pipeline for labelling, retraining and regression testing. Simulation, software-in-the-loop, hardware-in-the-loop and controlled flight tests will be used before real-world deployment. Each model and firmware update will be benchmarked against a fixed test suite covering accuracy, latency, stability, safety and energy consumption. Updates will be released gradually through version-controlled OTA deployment, with monitoring and rollback support. We are building for both India and global markets. India will be our initial launch and validation market because of its growing creator economy, cost-efficient manufacturing ecosystem and increasing acceptance of drones. After validating product reliability and commercial demand in India, we plan to expand into Southeast Asia, the Middle East, Europe and North America. The hardware and software architecture will be designed for localisation, while certification, radio, privacy and aviation compliance will be addressed separately for each target geography. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/IBWBhJsBPaqy-Dronosaur-Creators-Pitch-Deck_compressed.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/IBWBhJsBPaqy-Dronosaur-Creators-Pitch-Deck_compressed.pdf https://drive.google.com/file/d/1aZZ_v4P7XdjNOblsEXicRv_qNoo-ZbxB/view?usp=sharing Yes. Dronosaur is building an intelligent autonomous videography drone designed to make professional-quality filming more accessible to solo creators, travellers, fitness professionals, small businesses and content teams. Our mission is to remove the dependency on dedicated camera operators by combining autonomous flight, AI-based subject tracking and intelligent camera framing into a hands-free filming system. In the long term, we aim to contribute to India’s indigenous deep-tech and drone ecosystem by developing core capabilities across drone electronics, embedded systems, edge AI, autonomous navigation and hardware-software integration. NA TBIF, IIT Ropar Dronosaur is currently incubated at TBIF, IIT Ropar, and is developing an autonomous videography drone for hands-free professional filming. Our prototype development covers drone electronics, embedded systems, edge-AI tracking, autonomous flight and intelligent camera framing. We have received grant support for product development and are progressing toward an integrated MVP, real-world pilot testing and subsequent commercialization. checked
Aug 17, 2026 @ 6:43 PM Manas Kumar manas@fintolit.com http://www.linkedin.com/in/manas-kumar-marketing http://NA +919870404663 Manas Kumar (Co-Founder, Growth, Marketing & CX): background in brand and performance marketing at HUL, Revolt Motors, and Okaya EV. IIT Mandi and IIM Indore graduate. Abhishek (Co-Founder, Operations & Legal Network): built and manages the verified lawyer network and day-to-day operations. We met at Kyno Health, where I led growth and marketing and Abhishek ran revenue. We've worked together for the last 2.5 years, and co-founded Fintolit after seeing firsthand how fragmented and opaque legal services were for everyday consumers. All Our biggest strength is ownership: I drive growth, marketing, and customer experience, while Abhishek owns the lawyer network and operations. We've worked together for 2.5 years, so decisions move fast with no coordination lag, and we both have direct operator experience (not just strategy) from our time at Kyno Health. Fintolit www.fintolit.com Gurugram Fintolit is a managed legal services marketplace connecting everyday consumers with verified specialist lawyers for fixed-price consultations, live in Delhi NCR. Legal help in India is fragmented, unpriced, and trust-deficient - people don't know which lawyer to pick, what a fair price looks like, or whether they'll get quality advice. We built a platform of verified, specialist lawyers across various practice areas like workplace, family, divorce, real estate, cyber fraud - with fixed, upfront pricing for lawyer consultation(₹1,599 online, ₹3,499 at-home). Clients get matched to a vetted specialist instead of searching blind, and know the exact cost before they commit. This removes the two biggest friction points in legal services: who to trust and what it will cost. Right after the consultation, the client receives a legal roadmap with a full timeline to closure - and if they want to proceed with the case, the same lawyer continues with them, so there's no handoff or loss of context. This removes the biggest friction points in legal services: who to trust, what it will cost, and what happens next. Fixed-price, specialist-matched consultations plus a verified lawyer network - most Indian competitors are either content-led lead-gen (weak on trust) or unbundled directories (no pricing clarity). Our closest global comparable, Lawhive in the UK, has raised $110M+ validating the managed case management model outside India. Revenue Revenue Urban Indian consumers and small businesses facing a legal issue - workplace disputes, divorce/family matters, real estate transactions, or cyber fraud - who need a trustworthy, fairly-priced lawyer but don't have one in their network. 25-60 years age group, digitally active, currently based in Delhi NCR. Household income of >50k per month. 200000 cr 22000 cr 3500 cr Fixed consultation fees (₹1,599 online / ₹3,499 at-home) as the entry point, followed by case engagement fees when the client proceeds with the same lawyer post-consultation. LegalKart, LawRato, VakeelSaab, and Vakilsearch/Zolvit in India Performance marketing across Google Ads and Meta (Facebook/Instagram Reels), driving traffic to WhatsApp and our booking landing page, backed by SEO content. Paid digital acquisition (Search + Social) into a WhatsApp-first funnel, converting through a sales team that counsels leads to a paid consultation, then retains them into case engagement with the same lawyer. We want to make quality legal advice as accessible and predictable as any other essential service: fixed pricing, verified experts, and a clear path from problem to resolution. Incorporated - June 2025 Bootstrapped Yes To access structured mentorship, investor connects, and a founder ecosystem that can help us scale Fintolit's legal marketplace model beyond Delhi NCR, while tapping into IIT's technical and startup network to sharpen our product and operations. Validate and refine our path to ₹2 Cr revenue run-rate, & get investor-ready with structured mentorship. Yes Bangalore's dense tech and enterprise ecosystem is a strong expansion market for Fintolit's B2B legal offerings (workplace, MSME, staffing) beyond our current B2C base. IIT ACB's industry connect within the Bommasandra hub can help us pilot enterprise legal partnerships and access corporate HR/compliance teams directly. Yes We'd use the seats as a working base for our founding team to be closer to the mentor network, investor-connect sessions, and enterprise/B2B partnership meetings in the Bommasandra hub. Yes Supporting feature Odoo CRM as the core lead and case pipeline, WhatsApp AI chatbot for lead conversation and booking, Razorpay for payments, Google Workspace Studio with Gemini for automation, and Google Ads/GA4 for acquisition and conversion tracking. Case outcome data, consultation-to-engagement conversion patterns, lawyer performance by case type, demand predictability by category and city. A verified lawyer network with fixed pricing and same-lawyer case continuity - most Indian competitors are either unbundled directories (no pricing clarity, no accountability) or content-led lead-gen (weak on trust and follow-through). That combination is hard to replicate. We follow DPDP Act 2023 consent requirements for all marketing communications, and Bar Council of India Rule 36 compliance guardrails in how we present lawyers (no direct solicitation, no outcome promises, no superlative claims). DPIIT Startup India recognition; we are also evaluating applicable central and state (Haryana) government grants DPDP Act 2023 compliance on client data handling is an ongoing operational requirement as we scale. Lawyer supply - we'd need a much larger and elite lawyer network to maintain quality at 10x volume. The case allocation engine also needs to become far more robust to a system that can route cases to the right specialist lawyer instantly and accurately as volume scales. No dedicated deep-tech/engineering team in-house currently. We are looking for a tech lead. By tightening the automation layer already in progress - such as auto-generating case summaries from consultation transcripts - and reducing manual steps in the booking-to-payment and case-allocation flow. We track and act on funnel drop-off data (for example, booking page bounce rate) to keep improving conversion and reliability over time. India-first. Our current focus is deepening penetration in Delhi NCR and expanding to other major Indian cities, given the specific regulatory (Bar Council of India), language, and trust dynamics of the Indian legal market. We also plan to promote our platform with government entities, to create a legal pathway to rural India later. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/yIH7c4jHFSky-Fintolit-·-Performance-Report-·-July-2026.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/yIH7c4jHFSky-Fintolit-·-Performance-Report-·-July-2026.pdf Yes. Access to fair, trustworthy legal help is a genuine problem for most Indian consumers - people either overpay, get exploited by unverified intermediaries, or avoid seeking legal help altogether due to cost and trust concerns. Fintolit exists to make legal help predictable, fairly priced, and accountable. No NA checked
Aug 17, 2026 @ 5:54 PM Lt Col Omprakash Mayur@mapservices.in https://www.linkedin.com/in/mayur-mutgi?utm_source=share_via&utm_content=profile&utm_medium=member_android http://www.mapservices.in 919686690801 Founder & CEO - Lt Col Omprakash (Retd) : IIMK Alumni with 14 years experience in Indian Army,CBO - Mayur Mutgi : ISB ABA Alumni with 16 years of Sales, Marketing & Operations experience Director of Operations - Akash Ingole : 15 years of experience in Business & Ground operations Childhood friends All Our biggest strength is combining operational expertise, technology and a strong student-first approach to deliver measurable results. OMAP Management Services Pvt Ltd www.mapservices.in Pune Team MAP is a tech-enabled hostel management company transforming student living through integrated operations, technology, compliance and student engagement. Our MAP/Pulse ecosystem combines hostel management with student experience, wellness, engagement and sustainability intelligence, helping institutions build safer, smarter and more sustainable campuses. Hostel management is often fragmented, manual and inefficient, leading to poor transparency, inconsistent student experiences and avoidable costs. Team MAP brings operations, technology, compliance, student experience and sustainability into one integrated ecosystem. We combine deep hostel operations expertise with MAP/Pulse technology, integrating operations, compliance, student experience and sustainability in one ecosystem. Revenue Revenue Institutions ₹6,800+ Cr ~₹1,500 - 2,000 Cr annually — focused on institutional hostels in India ₹150–200 Cr annually We operate a B2B recurring revenue model, charging institutions per student/bed per month for end-to-end hostel management. Additional revenue comes from MAP/Pulse technology, student engagement and sustainability services. Good Host Spaces, Campus Living Villages, and Yugo Direct B2B sales to educational institutions through targeted outreach, referrals, partnerships and pilot deployments, converting successful pilots into long-term contracts. Institution-led B2B GTM: Target educational institutions directly through decision-maker outreach, referrals and strategic partnerships, use pilot hostel deployments to demonstrate impact, and convert successful pilots into long-term management contracts and MAP/Pulse subscriptions. To build a holistic, paperless and sustainable hostel ecosystem where student engagement, operations and technology are seamlessly integrated and scalable across institutions. Pvt ltd NA Yes We are applying to IITACB to gain access to mentorship, industry networks, technology expertise and institutional partnerships that can help us scale MAP/Pulse. We believe IIT’s ecosystem can help us strengthen our technology, validate our model and accelerate our growth across institutions. To validate and strengthen our business model, accelerate MAP/Pulse product development, build strategic institutional partnerships, and develop a scalable roadmap for expanding PULSE across India. Yes Leverage Bommasandra’s industrial ecosystem and Bengaluru’s education and technology market to expand hostel management and MAP/Pulse deployments. IIT ACB can support us with industry connections, mentorship, technology expertise and strategic partnerships to accelerate growth. No NA Yes Supporting feature 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/2uwTA370rHeR-Investor-Pitch-deck.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/2uwTA370rHeR-Investor-Pitch-deck.pdf Yes. MAP is mission-driven, focused on improving student life through better hostel operations, holistic engagement and sustainability. We aim to make hostels safer, more transparent, paperless, sustainable and technology-enabled, creating measurable positive impact for students and institutions. Ni TBIF checked
Aug 17, 2026 @ 4:59 PM Kumar Kislay kislay.work@gmail.com https://www.linkedin.com/in/kislay42/ https://kislay.co/ 09920947261 Founder & CEO. B.Tech + M.Tech, IIT Bombay (2013). Nine years as a product manager at Swiggy (built the Dineout vertical and Gift Cards 0→1), CarDekho, MakeMyTrip, Adda247, and DesignCafe as AVP Product. Before that, marketing head at bootstrapped Holidify (0 → ~500K monthly organic visitors in under a year). Solo founder. Currently building alongside independent product consulting; full-time from the moment the company is funded or incubated --- consulting winds down with zero obligations. I am deliberately not blocked on a co-founder: AI coding agents removed the "need hands to build" dependency, and I have shipped four V1 product stages myself. 1 Founder–product fit plus a build method that compounds. I am the target user with nine years of PM scar tissue at India’s top consumer companies. I build software the exact way the product says humans should work with AI: - I write locked behavioral specs and own every architecture decision; - AI agents implement; - I review adversarially against the spec. One person, four months, part-time: a working product with a typed five-layer state architecture and 90+ logged design decisions. PM Answers (working title) https://pm-answers-landing.vercel.app/ Bengaluru PM Answers is an AI-native thinking system for product managers. The AI owns scaffolding, context and critique. It interrogates before drafting, red-teams every document before it can close, and carries full context across the product lifecycle. The PM owns judgment and every decision, with block-level provenance of who (human or AI) wrote and decided what. It is deliberately not a document generator: deliverables like PRDs are projections of pressure-tested thinking, not one-shot outputs. AI tools now produce PRDs, roadmaps and strategy documents faster than anyone can think about them - polished output, unexamined thinking. Meanwhile PMs assemble their most consequential documents from scattered templates and tribal knowledge, and thinking quality depends on whichever senior PM happens to review them. The result is a universal, expensive failure mode: well-written but poorly-thought-out specs leading to misaligned builds and costly rework. As AI absorbs the writing and the coding, judgment is what remains of the PM job - and there is no tool for it. A guided workflow across the product lifecycle (Idea Capture → Vision Doc → PRFAQ → PRD in V1), where every stage runs a three-part ceremony: Enter (AI clarifying questions), Work (AI-scaffolded drafting with real-time critique), Exit (confidence scoring across four dimensions, gap detection, and a mandatory Red Team pass that must be resolved before the stage closes). Underneath sits a five-layer Context Spine - a typed state architecture where every fact and decision carries provenance (working → candidate → validated → locked), so the AI knows what to challenge and what to treat as settled, and nothing is silently dropped or contradicted between stages. The plan is to include adjacent functions like marketing and design, culminating in a multi-player orchestration platform with a common reasoning layer. Idea to final product with AI as a companion. TG: professionals in product orgs or startups Three things: (1) Structural opinionation: rigor is enforced by the system, not requested by the prompt - a stage cannot close until adversarial critique is addressed or dismissed with a recorded reason. The median PM will never prompt a chatbot to argue with them. (2) The provenance data model: block-level authorship and per-field decision provenance are first-class from the rendering layer up - impossible to retrofit onto a generic editor with an AI sidebar. (3) Compounding switching costs: every decision logged makes the accumulated spine more valuable; at team level it becomes the organization’s system of record for product decisions. MVP Signups Individual mid-level PMs at mature product companies (India + US), who already pay for personal AI tools. Expansion: product teams and CPO organizations, where the shared Context Spine becomes organizational decision memory. Buyer evolves from the PM personally (~$25/month prosumer) to the VP Product/CPO (team plans). The initial set of Target customers are mid-senior level PMs at product orgs and start-ups with plans to accommodate other levels as well as verticals. LinkedIn lists 1M+ product-management professionals globally; with product-adjacent roles that touch product decisions (design, marketing, business, eng leads, founders), the reachable seat pool is a multiple of that. TAM: ~5M seats × ~$300/year ≈ $1.5B for the individual wedge alone; team plans (more seats per account at higher ARPU) expand this 3–5x. SAM: English-first, AI-forward software companies in India + North America ≈ 1M seats ≈ $300M. SOM (3 years): 15–20K paid seats ≈ $5–6M ARR via product-led growth in PM communities. Per-seat SaaS. Individual PMs at ~$25/month; team plans at a multiple, where PMs, designers and engineers jointly work against a shared, provenance-tracked Context Spine. Expansion revenue comes from seats around the PM, not just more PMs - every function that consumes product decisions benefits from the decision memory. Document generators (ChatPRD, Notion AI, Coda AI) compete on writing speed; PM workflow suites bolting on AI (Productboard, ProdPad) own feedback and roadmap plumbing; and the real competitor is raw ChatGPT/Claude - what most PMs use today. All optimize output speed. None enforces thinking rigor, carries provenance-tagged context across the lifecycle, or refuses to let weak reasoning ship. That structural difference is the category. Three channels, in order of current weight. 1. Direct network: nine years of ex-colleagues across Swiggy, CarDekho, MakeMyTrip and DesignCafe, plus Bangalore's PM community (densest in the world) - my first 20-30 trial partners are recruited personally, one demo at a time. 2. Content and community: PMs congregate in a small number of trusted watering holes - newsletters, communities, podcasts, LinkedIn. I teach the method publicly (how to red-team your own PRD, why decision provenance matters), so the content demonstrates the product rather than advertising it. 3. Product-generated distribution: every document a PM shares out of PM Answers is provenance-tagged and visibly more rigorous than what their peers produce - the artifact itself is the demo. No paid acquisition until organic channels are measured; no sales team at this stage. A sequenced bottom-up approach. Phase 1 (September): 20-30 hand-picked design partners from my network prove the core loop and sharpen the product against real work. Phase 2 (post-beta): self-serve individual subscriptions (~$25/month) launched through PM communities - the PM buys with a personal card, no procurement, same motion that ChatPRD and personal AI tools have validated. Phase 3: bottom-up team expansion - when an individual PM's locked PRD circulates, their team inherits context from a spine they can't see into, and upgrading to a shared team plan is the natural fix; the individual seat is the trojan horse for the organization. Geographically: India first for product and design partners and community density, US first for revenue. Sales stays founder-led until team plans show a repeatable expansion pattern - then the GTM hire builds the playbook. A judgment operating system for anyone whose work is deciding. PMs are the wedge because the role is being reshaped by AI fastest, but the architecture - provenance-tagged context, enforced critique, decisions as durable organizational memory - generalizes to founders, strategy, policy and investment work. The end state: an organization’s accumulated, pressure-tested decisions become its most durable asset, and PM Answers is where they live. The plan is to include adjacent functions like marketing and design, culminating in a multi-player orchestration platform with a common reasoning layer. Idea to final product with AI as a companion. NA NA Yes Three reasons. The mentor pool: IIT alumni who have operated companies through 0→1 in India are exactly whose pattern-matching I want on my wedge-vs-expansion decisions. The investor connect: I will raise a round after my beta launch proves retention, and warm alumni introductions beat cold decks. And the community: I am an IIT Bombay alum building in Bengaluru. This is my natural home turf, and I would rather build dense local roots than only chase remote programs. Three outcomes in six months: 1. V1 complete and a design-partner beta live with 100+ weekly-active PMs; 2. retention proof on the core loop - does a PM who finishes one document start another; 3. a seed round anchored by conviction from (1) and (2), with IITACB alumni-network introductions. Plus one mentor-shaped ask: pressure-testing from operators who have sold SaaS into Indian and US product organizations. I am Bengaluru-based, so primarily in-person, with virtual as needed. (If I am concurrently accepted into an out-of-town program, I would switch to virtual for that period and return.) Honestly: my first hundred customers are software PMs in Bangalore’s tech corridors, not Bommasandra’s factories. But there is a real second-order play: the industrial and manufacturing companies around Bommasandra are building digital product teams (IoT, D2C channels, software-defined products) staffed by first-time product managers with no senior PM review culture - precisely the users whose thinking quality my product raises most. IITACB’s corporate connects could make manufacturing-sector product teams an unexpected early B2B segment, and I would happily run a pilot with one such team during the program. Yes A dedicated build base near the mentor pool, conference rooms for design-partner sessions and user research with Bangalore PMs, and event space for the PM community meetups that double as my go-to-market. I would also run my monthly design-partner demo days from the incubator. Yes Core engine React + TypeScript + Tailwind front end. A centralized typed state store (Zustand) implements the five-layer Context Spine - PM profile, project spine, document layer, conversational context, meta layer - as the single source of truth; every field carries a provenance tag. The document surface is custom-built (no off-the-shelf rich-text editor) so block-level authorship, inline decision markers and stage-gated rendering are first-class. All AI calls route through a typed facade - runAiCall (stage, phase, input). It is currently fixture-driven for deterministic development; swapping to the live Anthropic API is a one-file change. V1 persistence is local-first; the design-partner beta adds a hosted backend with per-org isolation. The advantage will come with usage. Structurally, the product is positioned to accumulate the rarest dataset in the space: how experienced PMs actually make, revise and reverse product decisions, with full provenance (what the AI proposed, what the human overrode, and why). Opt-in and privacy-bounded, that corpus becomes an eval and tuning asset no writing-speed competitor collects, because their products do not capture deliberation - only output. Same three moats as stated earlier (structural opinionation, provenance-native data model, compounding decision memory), plus one against the "ChatGPT adds this" scenario specifically: a general assistant optimizes for being agreeable and stateless across every use case; we optimize for being demanding and cumulative in one. Those are opposite product objectives - matching us would make a general chatbot worse at being a general chatbot. Three measurement layers, honestly staged: (1) Today - deterministic fixture-driven development, so every ceremony is testable end-to-end without model variance; dogfooding on the product’s own strategy as a continuous qualitative eval. (2) At live-AI wiring (next) - an eval harness for critique quality: Red Team catch-rate against documents with planted flaws, false-positive rate on sound reasoning, and confidence-score calibration against expert PM ratings. (3) At beta - the product metric that subsumes the rest: second-document retention, plus per-ceremony completion and challenge-acceptance rates. This is a first-class concern - the product holds unreleased product strategy, which is among a company’s most sensitive material. V1 is local-first: data never leaves the user’s device. The hosted beta adds encryption in transit and at rest, per-organization isolation, no training on customer content (opt-in only for the anonymized deliberation corpus), and API-provider agreements that exclude training on our traffic. Compliance roadmap tracks India’s DPDP Act and GDPR; SOC 2 begins when the first team-plan customer requires it - which for this buyer will be early, and is planned for, not bolted on. Startup India / Karnataka startup-policy benefits post-incorporation; DPDP’s clarity actually helps sell to Indian enterprises (a defined bar to clear beats ambiguity). There are some low and generic risks. Data-protection compliance as a SaaS handling confidential business documents, and evolving AI-disclosure norms in enterprise procurement. No sector-specific regulatory exposure: we process business strategy, not personal or regulated data categories. At 10× individual users: AI inference cost and latency discipline - long-context ceremony calls are expensive, so the spine needs selective-context retrieval instead of full-context stuffing (designed for, not yet built). At 10× from there (team scale): three things break honestly :- 1. the Context Spine per-org grows past comfortable single-store size and needs summarization + retrieval layers; 2. multiplayer editing needs real-time state sync (CRDT-class) that local-first V1 deliberately avoided; 3. critique-quality evals must become continuous regression infrastructure, because a silent model update that makes the Red Team 10% more agreeable is an invisible product failure. All three are why the founding hires are a systems engineer and an applied-AI/evals engineer. I am working Solo currently. I design the architecture and specs; AI coding agents implement; I review adversarially. First two technical hires are scoped: a founding systems engineer (harden the agent-built codebase, own the hosted backend) and an applied-AI engineer (own the eval harness and critique quality). Open source (permissive licenses): React, TypeScript, Tailwind, Zustand - all MIT/Apache. Commercial API: Anthropic Claude (licensed usage; no training on our data). No third-party datasets: the product ships no trained model of ours. Design research used only publicly available PM templates and frameworks plus my own past work. All specs, schemas, ceremony logic and code are owned outright. An eval-first loop: the critique-quality harness (planted-flaw catch rates, calibration) runs as regression infrastructure against every model or prompt change. The product also accumulates its own improvement signal by design - every reject-with-reason on a critique, every overridden AI proposal, every Avoid-Check dismissal is logged with provenance, which becomes the tuning corpus for making the challenger sharper without making it noisier (acting on this signal is the v2 roadmap, and it is already being collected in v1). Both, from day one - the product is English-language SaaS for a global profession. India (Bangalore) is the design-partner and community base; the US is the largest revenue market. Nothing in the product localizes; the go-to-market sequences India-first for partners, US-first for dollars. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/4GEGJDWT8gdC-PM_Answers_Kislay.pptx, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/4GEGJDWT8gdC-PM_Answers_Kislay.pptx https://www.youtube.com/watch?v=QlALdWDCLCY This product is Mission-driven. It raises the quality of decisions, not just the speed of output. In markets like India where most first-time PMs have no senior review culture, it functions as a rigor mentor that scales. NA Dileep Venkataramanan Currently also in application processes with international programs (YC F26, SPC); IITACB is attractive precisely because it is compatible with those - Bengaluru-based, and focused on mentorship and investor readiness. checked
Aug 17, 2026 @ 4:01 PM Janeya Mehta janeya.mehta88@gmail.com https://www.linkedin.com/company/hollybelly-food-boutique/posts/?feedView=all +91 98110 88127 Janeya Khanna (Founder & Culinary Director): Le Cordon Bleu (Paris) trained chef. Oversees end-to-end B2B product formulations, bespoke menu architecture, culinary R&D, operations, and quality benchmarking across enterprise accounts. Having completed classical culinary training at Le Cordon Bleu Paris, I founded Holybelly Food Boutique in 2015 to deliver elevated culinary concepts. Over the past decade, I have led and scaled our team to serve high-end corporate clients, luxury brands, and institutional B2B accounts. 1 Our strength lies in combining Michelin-standard culinary innovation with structured B2B execution. By maintaining strict standard operating procedures, customized high-margin product formulations, and rigorous quality control, we deliver consistent, reliable bulk fulfillment and fast turnaround times for enterprise and luxury brand clients. Hollybelly Food Boutique New Delhi A chef-led gourmet food boutique delivering specialized B2B culinary solutions, artisanal food products, and curated corporate dining experiences. The B2B gourmet food and corporate hospitality sector is dominated by commoditized, inconsistent caterers and generic mass producers who lack culinary refinement, custom formulation capabilities, and strict standard operating procedures for premium enterprise accounts. We provide end-to-end gourmet B2B solutions, including custom culinary product formulation, high-end corporate dining experiences, and institutional supply. By applying classical Le Cordon Bleu culinary standards, clean-label seasonal ingredients, and scalable production workflows, we offer enterprise clients and luxury brands consistent, high-margin, bespoke food offerings. Led by Le Cordon Bleu (Paris) trained expertise with over a decade of operational excellence in New Delhi, proprietary recipe formulations, deep supplier networks, and established long-term relationships with top-tier corporate and luxury brand accounts. Revenue Revenue Enterprise corporations, luxury lifestyle and fashion brands, creative agencies, high-end experiential event planners, boutique hospitality venues, and specialty retail distributors seeking premium, chef-crafted food solutions and customized corporate dining. $5.4 Billion $650 Million $25 Million B2B Contractual Catering & Corporate Retainers: Recurring service agreements for executive dining, corporate hospitality, and recurring enterprise events. Bespoke Product Supply & Institutional Wholesale: High-margin bulk manufacturing and white-label/branded supply of gourmet food lines to boutique retailers and luxury partners. Experiential & Private Events: Fixed-fee, high-ticket custom culinary curations and Chef's Table experiences for corporate brand activations and executive offsites. Boutique culinary studios and bespoke caterers (e.g., Caara, Food Inc. by Yum Yum Tree, The Moveable Feast). Premium institutional food-service providers and high-end hotel banquet operations (e.g., Oberoi/Taj institutional catering divisions). Emerging artisanal packaged food and gourmet D2C/B2B brands. Direct B2B account outreach to corporate HR/procurement heads and event directors, strategic agency partnerships (luxury PR, creative agencies, and event management firms), industry referrals, and high-visibility showcase pop-ups and brand collaborative activations. Land-and-expand approach targeting Tier-1 luxury brands and enterprise clients in Delhi NCR through high-impact tasting sessions and custom pilot menus. Convert one-off corporate activations into recurring annual catering retainers and institutional supply contracts, followed by geographical expansion into major commercial hubs like Mumbai and Bengaluru. To build India’s premier chef-led culinary group for the enterprise ecosystem—standardizing Michelin-grade culinary innovation at scale across corporate hospitality, premium institutional supply, and pan-India artisanal food retail. Incorporated (LLP / Private Limited) 3cr Yes To access the strategic IIT alumni corporate network, institutional mentorship, and investor ecosystem in Bengaluru. We aim to leverage IITACB’s deep enterprise ties to scale our B2B gourmet culinary offerings, establish institutional corporate dining tie-ups, and structure our business for rapid pan-India commercial expansion. Expand our high-margin B2B corporate catering and enterprise contracts into the South India / Bengaluru corridor. Establish formal institutional procurement and corporate retainer relationships with Global Capability Centres (GCCs) and tech majors. Refine supply chain logistics, unit economics, and standard operating procedures for multi-city kitchen infrastructure. Prepare the business for institutional seed/angel fundraising via investor-connect initiatives. Yes (Open to a hybrid engagement model with in-person milestone visits) Bommasandra and the wider Bengaluru tech corridor host major multinational headquarters, GCCs, biotechnology firms, and corporate campuses requiring elevated corporate dining and executive hospitality. We can serve as a premier culinary partner for enterprise events, executive dining, and bespoke institutional food solutions. IITACB can accelerate this through direct introductions to institutional decision-makers, industrial facility networks, and alumni-led corporate procurement teams. Yes We will use the IITACB facility as our regional corporate expansion base in Bengaluru to conduct enterprise B2B sales meetings, host curated corporate tasting showcases, coordinate regional business development, and tap into incubator conference facilities to pitch to tech enterprise clients and angel investors. Yes Supporting feature Cloud-based inventory and ERP management system integrated with demand-forecasting workflows, automated kitchen order routing, and digital recipe standardization tools to maintain consistency across batch production. Over a decade of proprietary culinary formulation data, standardized recipe yields, ingredient substitution matrices, seasonal pricing indexes, and structured B2B corporate consumption patterns across hundreds of executive events and client preferences in Delhi NCR. Proprietary recipe formulations, Le Cordon Bleu culinary IP, strict standard operating procedures that prevent taste degradation at scale, long-standing supplier integration for clean-label raw materials, and high switching costs created through tailored corporate retainers. Order Fulfillment Accuracy: 99%+ on-time, in-spec enterprise delivery rate. Production Yield Consistency: Variance under 2% across batch recipe formulations. Client Retention & Repeat Rate: B2B annual contract renewal rate. Food Safety & Quality Compliance: 100% audit pass rates on quality checks. We maintain strict compliance with enterprise data handling policies and India’s DPDP Act, ensuring corporate client data and internal proprietary formulation files are securely stored on encrypted cloud drives with restricted, role-based access controls. FSSAI food safety standardizations, government incentives under the PM Formalisation of Micro food processing Enterprises (PMFME) scheme, and MSME priority procurement policies for corporate hospitality and packaging supply. Strict compliance requirements around food safety, cold-chain storage standards, FSSAI licensing mandates, and shifting packaging/plastic waste management regulations. We mitigate these through routine lab testing, certified packaging, and standardized food handling audits. Centralized single-kitchen preparation capacity and local logistics fulfillment. Scaling 10x requires setting up distributed base/commissary kitchens, automated semi-industrial prep equipment, and robust third-party temperature-controlled supply chain integrations. NA (Our in-house expertise is centered on food science, culinary formulation, kitchen engineering, and operational logistics, while using standard enterprise SaaS for technology needs). Owned proprietary database of chef-curated recipe formulas, menu costing algorithms, supplier catalogs, and client preference datasets. No open-source tech stacks or external software code used. By adopting automated demand forecasting tools, integrating smart kitchen IoT monitors for precision cold-chain tracking, and standardizing batch tracking software across new multi-city commissary setups. Currently focused on scaling across India (starting with Tier-1 metropolitan hubs including Delhi NCR, Bengaluru, and Mumbai) with long-term potential for international gourmet packaged food export. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/8SzLDOR01dqs-HollyBelly-Pitch-deck-1.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/8SzLDOR01dqs-HollyBelly-Pitch-deck-1.pdf http://NA Yes. While operating as a high-margin gourmet food business, our mission focuses on culinary sustainability, ethical sourcing, and clean-label nutrition. We actively partner with regional Indian farmers and artisanal producers to procure seasonal, organic ingredients, eliminating synthetic additives and ultra-processed ingredients from corporate and institutional dining. Additionally, we implement strict zero-food-waste kitchen workflows, compost organic scraps, and utilize eco-friendly biodegradable packaging across our B2B delivery formats. NA NA Holybelly Food Boutique has a decade-long proven track record in Delhi NCR delivering bespoke, chef-crafted dining and packaged culinary solutions to luxury brands, high-net-worth individuals, and enterprise accounts. We are applying to IITACB to systematically scale our B2B operations into the South India / Bengaluru corporate corridor by leveraging IITACB's enterprise alumni base and corporate network. checked
Aug 17, 2026 @ 12:19 PM Namita Ratra ratranamita@yahoo.co.in https://www.linkedin.com/in/namitaratra/ +919820520680 1 Our biggest strength is that this problem isn't theoretical for us — it's lived expertise translated into behavioural science. I've spent over a decade building learning and capability functions at global scale — including building Sandoz's L&D function from zero across 30+ countries and 23,000+ associates after its spin-off from Novartis, and earlier managing enterprise learning for 100,000+ associates at Novartis. That means I've sat on the side of the table that designs workforce transitions, and I've also seen up close what happens to people when those transitions fail them. I'm pairing that operational depth with rigorous behavioural science grounding — I'm completing an Executive MSc in Behavioural Science at LSE, and ReBoost's design draws directly on frameworks like Motivational Interviewing, WOOP, and Implementation Intentions rather than generic "resilience" content. Few people building in this space have both the L&D operator experience to know what actually gets adopted inside organisations, and the academic rigor to design an intervention that's evidence-based rather than just well-intentioned. That combination — practitioner credibility plus scientific grounding — is what lets ReBoost move fast without being shallow. ReBoost Hyderabad, Telangana, India ReBoost is an AI-powered behavioural companion for people navigating post-layoff career transitions. Job loss triggers a predictable set of psychological barriers — present bias, avoidance, loss of structure and identity — that generic career coaching and job boards don't address. ReBoost closes that gap by combining Motivational Interviewing, WOOP (Wish-Outcome-Obstacle-Plan), and Implementation Intentions into a guided, AI-driven companion that helps people move from paralysis to action: clarifying what they actually want next, surfacing the obstacles keeping them stuck, and turning intentions into concrete daily behaviours. It's built on over a decade of enterprise L&D and organisational capability experience, paired with a behavioural science foundation, to make career transition support that's evidence-based rather than generic motivational content. Every year, millions of people are laid off — and the support available to them hasn't kept pace with the psychological reality of what they're going through. Job boards assume people are already action-ready. Career coaching is expensive, generic, and often disconnected from behavioural science. And yet the biggest barrier to re-employment usually isn't a lack of information — it's present bias (avoiding the job search because it feels overwhelming today), planning fallacy (underestimating how long the transition will actually take), and a collapse in structure and identity that follows the loss of a job. The result: people stay stuck longer than they need to, not from lack of effort but from lack of the right psychological scaffolding at the right moment. ReBoost solves this by giving people a structured, AI-guided companion — grounded in Motivational Interviewing, WOOP, and Implementation Intentions — that meets them in that stuck moment and helps them convert intention into consistent action, one small step at a time. ReBoost is an AI behavioural companion that guides people through post-layoff career transitions using structured, evidence-based coaching conversations rather than generic advice or static content. It works in three stages: Clarify — Using Motivational Interviewing techniques, ReBoost helps the person surface what they actually want from their next move, working through ambivalence and avoidance rather than pushing generic "next steps" prematurely. Plan — Applying the WOOP framework (Wish–Outcome–Obstacle–Plan), it helps the person name their real goal, the benefit of achieving it, the specific obstacle in their way, and a concrete plan to overcome it — turning vague hope into a realistic, personalised roadmap. Act — Using Implementation Intentions ("if X happens, I will do Y"), ReBoost converts that plan into small, trackable daily actions, checking in regularly to build momentum and hold the person accountable without judgment. Unlike job boards or one-off coaching sessions, ReBoost is designed for the psychological reality of transition — meeting people where present bias and planning fallacy keep them stuck, and using conversation-based AI to nudge them, consistently, toward action. Three things set ReBoost apart, and compound over time: 1. Domain expertise most AI career tools don't have. Most career-tech products are built by technologists layering AI onto job-matching. ReBoost is built by someone who has spent over a decade inside enterprise L&D — building Sandoz's capability function from scratch across 30+ countries, and managing enterprise learning for 100,000+ associates at Novartis. That means the product is designed around how organisations and individuals actually behave during transitions, not assumptions about it. 2. A behavioural science architecture, not a prompt wrapper. ReBoost isn't a generic chatbot with a career-coaching persona. It's structured around specific, research-backed frameworks — Motivational Interviewing, WOOP, and Implementation Intentions — applied to the specific cognitive biases (present bias, planning fallacy, optimism bias) that keep people stuck after job loss. This structure is being validated academically through my LSE Behavioural Science dissertation, giving the product an evidence base competitors built purely on generic LLM prompting won't have. 3. Data moat through longitudinal behavioural tracking. As users move through their transition, ReBoost accumulates a unique dataset on what interventions actually shift behaviour at each stage of transition — obstacle patterns, what nudges convert intention to action, drop-off points. Over time, this becomes a proprietary layer that's hard to replicate without the same volume of real transition journeys. Idea Here's a draft: Who are your target customers? ReBoost has two customer layers: Primary: Individuals navigating post-layoff transitions. Mid-to-senior career professionals (broadly 28–50) who've recently lost their job — through layoffs, restructuring, or role redundancy — and are experiencing the psychological stall that comes with it: avoidance, loss of structure, difficulty converting job-search intentions into consistent action. This includes people in tech, GCC/shared services, and corporate functions where layoffs have been especially concentrated in recent years. Secondary (B2B channel): Organisations conducting layoffs. Companies going through restructuring increasingly want to offer meaningful outplacement support, not just a severance check and a generic job board license. HR and L&D leaders — the audience I know intimately from my own career — are actively looking for outplacement solutions that are more humane and effective than what's currently available. ReBoost can be offered as part of a company's exit/transition support package, creating a B2B2C distribution channel alongside direct-to-consumer. This dual-track approach means ReBoost isn't solely dependent on individual consumers finding and paying for the product — it can also be sold into HR/L&D budgets as part of workforce transition support, a sales motion I'm well positioned to run given my background. Bommasandra and the wider Bangalore market give ReBoost a dense, walkable customer base rather than an abstract TAM. The hub is home to large pharma, biotech, engineering, and manufacturing employers (Biocon, Micro Labs, and others), alongside a fast-growing GCC and IT cluster spilling south from Electronic City — sectors that have all seen significant restructuring and workforce churn in recent years. That's precisely the B2B2C channel ReBoost is built for: HR and L&D leaders at these companies looking for outplacement support that's more humane and effective than a severance letter and a job-board license. My own network compounds this — over a decade in enterprise L&D leadership (Novartis, Sandoz) means I can walk into HR conversations with these companies as a peer, not a cold pitch. IIT ACB can help in three concrete ways: Warm access to the corporate ecosystem — introductions to HR/L&D and CHRO-level leaders at Bommasandra and Bangalore-based companies who are ReBoost's natural early B2B2C customers. Mentorship and validation — access to IIT alumni mentors with startup and behavioural-tech experience to pressure-test the product and go-to-market before I scale outreach. Credibility and infrastructure — being incubated at IIT ACB signals rigor to enterprise buyers who are cautious about AI tools in sensitive HR contexts, and gives me a base to run pilots and gather the early usage data ReBoost needs to build its data moat. Yes Here's a draft: How do you wish to leverage IITACB infrastructure and facilities when you rent seats in this Incubator? I'd use the seats primarily as a working base and a trust signal for enterprise conversations, not just desk space: Dedicated workspace for focused build time — a consistent seat to develop and iterate on ReBoost's AI companion, run user testing sessions, and hold confidential conversations with pilot customers and HR partners in a professional setting rather than over video calls. The alumni network as a structured resource, not incidental networking — with all 23 IITs represented under one roof and 50,000+ Bengaluru-based IIT alumni, I'd actively use the mentoring programmes and informal lounge interactions to find technical co-founders or advisors (I bring the behavioural science and enterprise L&D depth; I'd want to pair that with strong AI/ML engineering talent), and to reach IIT alumni in HR/CHRO roles at target companies for pilot introductions. Events and talks as a testing ground — using IITACB's talks, events, and cultural programming to get ReBoost's proposition in front of a credible audience early, gather feedback, and build visibility before a wider launch. Proximity to the Bommasandra corporate ecosystem — being physically based in the same industrial hub as the companies I want as B2B2C partners means pilots, in-person HR meetings, and site visits are a short trip rather than a logistical hurdle. Yes Not applicable 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/A97OtQdjlGi7-ReBoost_Summative_Presentation_final.pptx, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/A97OtQdjlGi7-ReBoost_Summative_Presentation_final.pptx NA checked
Aug 17, 2026 @ 11:22 AM Dr. Varun Dutt uday@iitmandi.ac.in https://www.linkedin.com/in/venkata-uday-kala-%E0%A4%95%E0%A4%B2%E0%A4%BE-%E0%B0%95%E0%B0%B3-09417315/ http://iiots.in 9805647823 Director We met at IIT Mandi campus and now its almost 8 years we are working together. 2 Our biggest strength is the combination of deep technical expertise, field experience, and strong execution capability. Our team brings together IIT-backed R&D, IoT, AI/ML, embedded systems, geotechnical expertise, and business development, enabling us to take technology from research and prototyping to real-world deployment. Our close understanding of customer and ground-level challenges helps us build practical, reliable, and scalable solutions. Intiot services pvt. ltd. iiots.in Himachal Pradesh Intiot Services Pvt. Ltd. is an IIT Mandi-incubated deep-tech startup developing indigenous IoT, AI, and sensor-based solutions for disaster resilience and environmental monitoring. Our flagship Landslide Monitoring & Early Warning System provides real-time monitoring and timely alerts to help protect lives, roads, and critical infrastructure. We also develop solutions for rockfall, flood, and air-quality monitoring, with a focus on affordable, scalable, Made-in-India technology. Intiot addresses the lack of affordable, reliable, and real-time early-warning systems for landslides and other environmental hazards. Landslides can occur with limited warning, causing loss of lives, road blockages, infrastructure damage, and economic disruption. Our technology enables continuous monitoring of ground conditions and provides timely risk alerts, helping authorities and infrastructure operators take preventive action and improve disaster preparedness. Intiot develops indigenous IoT- and AI-enabled monitoring and early-warning systems for natural and environmental hazards. Our flagship Landslide Monitoring & Early Warning System combines MEMS sensors, geophones, extensometers, weather sensors, edge computing, IoT connectivity, and AI/ML analytics to continuously monitor ground conditions and detect early signs of slope instability. Real-time data is analysed through a cloud platform and delivered via dashboards and automated alerts, enabling authorities to take timely preventive action. The platform is scalable to other hazards such as rockfalls, floods, and air pollution. Intiot combines indigenous MEMS-based hardware, multi-sensor fusion, IoT/4G connectivity, edge computing, and AI/ML analytics into an end-to-end early-warning platform. Our technology is developed and field-validated specifically for India’s challenging mountainous terrain, offering a cost-effective alternative to expensive imported systems. Our proprietary algorithms, growing field dataset, deployment know-how, IIT-backed R&D, and expanding IP portfolio create strong technical and commercial defensibility. Revenue Revenue DDMA, SDMA and NDMA and private players. Intiot’s TAM covers the global market for disaster monitoring and early-warning solutions, including landslide, rockfall, flood, dam, and environmental monitoring. The opportunity spans governments, road and highway authorities, railways, hydropower, mining, construction, smart cities, and other critical infrastructure operators. Increasing climate-related disasters, infrastructure development, and demand for real-time risk monitoring are driving the need for scalable and affordable early-warning technologies globally. Intiot’s SAM focuses on the Indian market for landslide, rockfall, flood, dam, and environmental monitoring systems across government departments, NHAI, PWDs, hydropower companies, railways, mining, smart cities, and critical infrastructure operators. Our immediate focus is on high-risk Himalayan states such as Himachal Pradesh, Uttarakhand, Jammu & Kashmir, and Sikkim, where the need for real-time monitoring and early-warning systems is high. We will subsequently expand into other hazard-prone regions across India. Intiot’s initial SOM focuses on landslide-prone regions and critical infrastructure projects in Himachal Pradesh, Uttarakhand, Jammu & Kashmir, and other Himalayan states. Based on our existing deployments, partnerships, and sales pipeline, we aim to deploy approximately 100–200 monitoring systems over the next 3–5 years. With system sales, installation, AMC, and recurring monitoring revenue, this represents a potential obtainable revenue opportunity of approximately ₹15–30 crore Intiot follows a B2G, B2B and B2B2C revenue model. We generate revenue through the sale and deployment of monitoring systems, site surveys, installation, customization, AMC, and recurring cloud-based monitoring and alert subscriptions. Additional revenue comes from data analytics, system upgrades, integration with existing platforms, and customized monitoring solutions. This combination of upfront system revenue and recurring service income provides a scalable and sustainable business model. Our main competitors include global geotechnical and monitoring companies such as Sisgeo, RST Instruments, Geosense, and Worldsensing, along with Indian system integrators and conventional manual monitoring solutions. Intiot differentiates itself through indigenous manufacturing, MEMS-based low-cost sensing, AI/ML-driven analytics, real-time IoT connectivity, and an end-to-end early-warning platform designed specifically for India’s challenging mountainous terrain. Intiot acquires customers through direct engagement with government departments, NHAI, PWDs, hydropower companies, infrastructure operators, and disaster-management authorities. We use pilot projects, field demonstrations, site surveys, tenders, industry partnerships, referrals, and IIT Mandi’s ecosystem to build credibility and generate leads. Successful pilots are converted into larger deployments, AMC contracts, and recurring monitoring subscriptions, while strategic partners help us expand into new regions and customer segments. Intiot follows a pilot-to-scale B2G/B2B strategy. We target high-risk government and infrastructure projects through direct engagement, site surveys, demonstrations, tenders, and pilot deployments. Successful pilots are converted into large-scale deployments, AMC, and recurring monitoring contracts. We will accelerate growth through partnerships with NHAI/PWDs, hydropower and mining companies, infrastructure firms, system integrators, and technology partners, initially focusing on India before expanding to international markets. Our long-term vision is to make Intiot a global leader in affordable, indigenous AI- and IoT-based disaster resilience and environmental intelligence. We aim to build an integrated early-warning platform covering landslides, rockfalls, floods, air quality, and critical infrastructure. Our goal is to protect lives and assets, strengthen climate resilience, and make advanced monitoring technology accessible to vulnerable regions across India and the world. YES 55 Lacs Yes We are applying to IITACB Incubator to accelerate the commercialization and scale-up of Intiot’s proven deep-tech solutions. IITACB can provide access to industry networks, mentorship, investor connects, technical resources, talent, and strategic partnerships. Bengaluru’s strong technology and infrastructure ecosystem will also help us expand customer reach, strengthen our supply chain, attract investment, and build partnerships for scaling our disaster-monitoring solutions across India and global markets. During the programme, we aim to accelerate commercialization and scale our field-validated disaster-monitoring solutions. Our key goals are to secure strategic customers and investors, strengthen our AI/IoT technology, develop industry partnerships, improve manufacturing and deployment capabilities, and expand our market presence beyond the Himalayan region. We also seek mentorship in business scaling, IP, fundraising, and global market entry to build Intiot into a scalable deep-tech company yes We can leverage the Bommasandra industrial hub and Bengaluru’s deep-tech ecosystem for electronics sourcing, contract manufacturing, prototyping, system integration, and access to infrastructure and technology companies. Bengaluru also offers strong opportunities for investors, talent, enterprise customers, and strategic partnerships. IITACB can help us through industry connects, mentorship, investor access, pilot opportunities, technical resources, and market linkages, enabling Intiot to strengthen its supply chain and scale our disaster-monitoring solutions nationally and globally. Yes We plan to use IITACB’s infrastructure as a Bengaluru base for business development, customer and investor meetings, product demonstrations, prototyping, and industry collaboration. Access to workspaces, meeting facilities, technical resources, and the incubation ecosystem will help us strengthen product development, system integration, talent acquisition, and partnerships. We also aim to leverage IITACB’s industry and investor network to accelerate commercialization and expand Intiot’s market presence across India and global markets. Yes Core engine Intiot uses a layered IoT–AI architecture. Field-level sensors, including MEMS accelerometers, geophones, extensometers and weather sensors, continuously capture ground and environmental parameters. An edge gateway performs data acquisition, preprocessing, sensor fusion and local event detection. Data is securely transmitted through 4G/LoRa connectivity to the cloud platform, where AI/ML models analyse time-series data and identify abnormal patterns and risk levels. A centralized dashboard provides real-time visualization, analytics and system health monitoring, while automated SMS, app and other alerts enable timely action by authorities. Yes. Intiot has a growing proprietary dataset generated from real-world landslide monitoring deployments across Himalayan terrain. It includes time-series data from MEMS sensors, geophones, extensometers, weather parameters, ground movement patterns, and observed landslide events. This field data helps us calibrate and validate AI/ML models, improve detection accuracy and reduce false alarms. As deployments increase, the expanding dataset creates a strong and continuously improving data advantage. Intiot’s defensibility comes from the combination of indigenous hardware, proprietary AI/ML algorithms, multi-sensor fusion, real-world field data, and deployment expertise. Our systems are specifically designed and validated for India’s challenging mountainous terrain and critical infrastructure. Our growing IP portfolio, IIT-backed R&D, established deployments, customer relationships, and accumulated site-specific data create strong technical, operational, and market barriers for competitors. We evaluate our technology through field deployments, controlled testing, and comparison with conventional and commercial monitoring methods. Key metrics include sensor accuracy, detection sensitivity, false-alarm rate, warning lead time, data availability/uptime, communication reliability, response time, power consumption, and system durability. We continuously validate sensor data against ground observations and recorded events, using the results to improve calibration, AI/ML models, reliability, and early-warning performance. Intiot follows a security-by-design approach. Field devices use authenticated and secure communication to transmit data to the cloud, with role-based access controls ensuring that only authorized users can access project information. We maintain secure backups, device authentication, controlled data access, software/firmware updates, and monitoring of system health. Customer and site data is treated as confidential and shared only with authorized stakeholders, in accordance with applicable contractual, regulatory, and government requirements. Yes. Intiot benefits from government initiatives focused on disaster risk reduction, climate resilience, Make in India, Atmanirbhar Bharat, Digital India, and smart infrastructure. Policies promoting indigenous technology, public-sector innovation, and early-warning systems create opportunities for adoption by government and infrastructure agencies. Government R&D grants, startup programmes, public procurement initiatives, and support from institutions such as DST, MeitY, NHAI, and state disaster-management authorities can further enable technology validation and large-scale deployment. Potential regulatory risks include evolving standards for disaster-monitoring systems, government procurement requirements, telecom/connectivity regulations, data-security requirements, and certifications for deployment on critical infrastructure. Government adoption may also require extensive field validation and compliance with project-specific standards. We mitigate these risks through IIT-backed R&D, rigorous field testing, documentation, engagement with relevant authorities, and adherence to applicable Indian regulations and standards At 10X scale, the biggest challenges would be manufacturing capacity, component supply, field installation and maintenance, quality control, and customer support rather than the core technology. Our cloud and IoT architecture is designed to scale, but operations will need to expand significantly. We plan to address this through standardized hardware, multiple suppliers and manufacturing partners, automated cloud infrastructure, regional service teams, remote diagnostics, and robust QA/QC processes. Yes. Intiot has an in-house deep-tech team with expertise in IoT, embedded systems, MEMS and sensor technologies, AI/ML, signal processing, data analytics, cloud platforms, wireless communication, and geotechnical monitoring. The team works closely with IIT Mandi faculty and researchers on R&D, prototyping, testing, and field validation. Our capabilities cover the complete technology stack—from sensor and hardware development to edge computing, AI-based analytics, cloud dashboards, and large-scale field deployment. We use a combination of proprietary field data, publicly available datasets, open-source software libraries, and commercially available electronic components. Open-source tools and libraries are used in accordance with their respective licenses, while our sensor integration, system architecture, data-processing pipelines, AI/ML models, field datasets, and deployment know-how are internally developed and owned by Intiot/IIT Mandi. We have filed multiple patents, including a granted patent for our low-power, low-cost air-quality monitoring technology. Detailed IP references can be shared as required. We follow a continuous improvement approach driven by field data, customer feedback, and system performance metrics. We continuously improve sensor calibration, AI/ML models, detection accuracy, false-alarm reduction, warning lead time, connectivity, power efficiency, and hardware reliability. Increasing deployment data enables better model training and site-specific calibration. Regular field validation, firmware/software updates, remote diagnostics, predictive maintenance, and ongoing IIT Mandi R&D will help us continuously improve system performance. Both. Intiot is initially focused on India, particularly the Himalayan and other hazard-prone regions, where our technology has been field-tested and validated. We plan to expand into global markets with similar disaster risks, including South and Southeast Asia and other mountainous and climate-vulnerable regions. Our strategy is to establish a strong Indian market base and then scale internationally through technology partnerships, infrastructure companies, and local deployment partners. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/fS3pe62UL3nl-Write-up-on-LMS.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/fS3pe62UL3nl-Write-up-on-LMS.pdf http://iiots.in%20 Yes. Intiot is a mission-driven deep-tech startup focused on reducing the impact of natural hazards and protecting lives, communities, and critical infrastructure. Our indigenous monitoring and early-warning systems enable timely detection of landslides and other environmental risks, helping authorities take preventive action. We aim to make reliable and affordable disaster-monitoring technology accessible to vulnerable regions, while strengthening climate resilience, supporting safer infrastructure, and contributing to sustainable development in India and globally. NA Dr. Varun Dutt Intiot is an IIT Mandi-incubated deep-tech startup with field-validated solutions for disaster resilience and environmental monitoring. Our flagship Landslide Monitoring & Early Warning System has been deployed in real-world conditions and is supported by indigenous R&D, proprietary data, an expanding IP portfolio, and strategic partnerships. We are focused on scaling from India to global markets while creating measurable social and economic impact. checked
Aug 17, 2026 @ 11:18 AM Omprakash Ganesan omprakash71614@gmail.com https://www.linkedin.com/in/omprakash-ganesan +918754335756 EKO Health Innovations combines public-systems governance with top-tier strategic execution to build India’s care-mobility infrastructure through Eldoo Care. Omprakash — Co-Founder (Policy, Governance & Institutional Systems): Holds an M.Sc. and M.P.P. from the London School of Economics (LSE) and is an FRSA. As a former Tamil Nadu civil servant, he leverages deep public-sector experience to lead statutory compliance, DPDP regulatory frameworks, and hospital network partnerships. Arun — Co-Founder (Strategy, Operations & Route Economics): Holds an M.S. from TU Berlin with 8+ years in management consulting (EY-Parthenon, Roland Berger), advising Fortune 500 leadership on multi-billion-dollar transformations. He architects Eldoo Care’s platform technology, matching algorithms, and asset-light unit economics. Together, the founders pair grassroots public healthcare depth with analytical rigor to deliver safe, dignified, bed-to-bed assisted transit for mobility-restricted patients. We first crossed paths five years ago through our shared commitment to grassroots social mobility, collaborating on non-profit initiatives designed to empower and mentor first-generation learners across the state. That multi-year foundation forged our operational rhythm, alignment on public impact, and mutual execution trust. Over time, our professional collaboration evolved into Eldoo Care through shared personal reality: as working professionals living away from our hometowns, we experienced firsthand the acute anxiety, logistical friction, and vulnerability of managing aging, mobility-restricted parents from a distance. Combining Omprakash’s public-systems and governance background with Arun’s strategic consulting and operational experience, we transitioned our five-year working dynamic toward building India’s foundational care-mobility infrastructure. 1 Our biggest strength is the complementary convergence of deep public-systems governance and tier-one strategic execution, underpinned by five years of battle-tested working trust and authentic lived experience. Omprakash (M.Sc./M.P.P. LSE, FRSA, ex-Tamil Nadu Civil Servant) brings statutory fluency, DPDP/regulatory compliance, and the institutional credibility required to unlock public and private hospital partnerships. Arun (M.S. TU Berlin, 8+ years at EY-Parthenon & Roland Berger) brings institutional operational architecture, algorithmic matching design, and disciplined unit-economics modeling. Having collaborated for half a decade building grassroots educational initiatives for first-generation learners, we enter this venture with an established operational cadence, shared decision-making trust, and zero co-founder friction. As first-generation learners from remote regions living away from home, our conviction is anchored in firsthand reality: managing the acute vulnerability and transit friction of aging parents from afar. We understand both how hospital leadership evaluates P&L efficiency (OPD slot recovery, IP bed turnover) and how to design scalable, asset-light care delivery without clinical compromise. EKO HEALTH INNOVATIONS Bengaluru Eldoo Care (by EKO Health Innovations) is an asset-light, technology-enabled supportive-care platform that gets India's ageing parents to healthcare, safely, reliably, and with their distant children watching every step. We adapt the broker-orchestration model: rather than owning vehicles or clinics, we orchestrate a credentialed network of trained companions ("CareMates") and mobility partners, and we own the high-margin layer of human trust, clinical advocacy, and the audited care-and-data trail. We launch escorted non-emergency medical transport (NEMT) and planning to expand into home care, remote monitoring, and nutrition, the same vulnerable elderly, more services, and one care plan. India is ageing faster than its care infrastructure. Over 100 million Indians are 60+ today, rising toward ~347 million by 2050, and in southern states 16%+ of the population is already elderly. Simultaneously, migration has dismantled the traditional safety net: children live in distant metros or abroad, and millions of elders effectively navigate hospitals alone. The concrete failure is everyday, non-emergency medical logistics, getting a frail parent to a dialysis session, a chemo cycle, or a post-op review. Emergency ambulances ignore this routine need; unvetted cab and gig-app drivers have zero training in mobility or cognitive care and never step inside the OPD. The clinical consequence is "distance-decay": when getting to care is hard, chronically-ill patients skip it, and skipped appointments convert directly into avoidable, expensive emergency admissions. For the adult child, it is a daily tax of constant, helpless worry. A trained, background-verified CareMate manages the entire journey bed-to-bed: arrives at the elder's home, checks basic vitals, organises diagnostic files, accompanies them in a mobility-appropriate vehicle, handles hospital registration/queues/billing, sits through the consultation and transcribes the doctor's instructions, verifies pharmacy dispensing, and returns the elder safely home, then sends a structured digital debrief to the family within ~30 minutes. The family books and tracks the whole thing through our app (live map, visit timeline, in-app call) and receives an auto-generated visit report with vitals, a plain-language doctor summary, and confirmed medicines. Recurring treatments like dialysis are set up as standing orders with guaranteed weekly slots. Around this sits our platform: AI care-matching, smart triage, chronic-condition nudges, and between-visit health tracking. We do not sell rides, we operate a credentialed supportive-care network governed by an institutional protocol of trust, and we own the care-and-data layer while treating mobility as an asset-light commodity. Four compounding moats: (1) Credentialing network: a verified CareMate + vetted-vehicle supply base (Aadhaar, police check, references, training) is slow to build and hard to copy; it's the barrier, not the app. (2) Closed-loop data flywheel: every ride, in-home observation, and vital sharpens our matching and outcome reporting. (3) Multi-sided lock-in: hospitals cut no-shows, corporates cut absenteeism, insurers cut total cost of care, families gain peace of mind; each side reinforces the others. (4) Regulatory-grade compliance: ECO/GST, MVAG, and DPDP readiness raises switching costs and deters casual entrants. Uber and a local helper each solve one-third of the problem; only an integrated, credentialed, data-instrumented network solves all of it. MVP Users, Pilots, Signups Two primary B2C segments and two secondary B2B channels. Primary: (1) NRI families (US, UK, Gulf, Singapore) whose parents live in Indian metros, they can pay but cannot physically show up; (2) Sandwich-generation professionals aged 30–55 in Tier-1 metros managing aging parents alongside career and children, high disposable income, severe time constraint, paying for reliability and peace of mind. Secondary (B2B): (3) Corporates offering eldercare as an employee-wellness benefit; (4) Hospitals, dialysis centres, and oncology clinics where transport gaps cause missed sessions and cancelled slots. The long-term prize is (5) insurers who package our service as an value-added benefit. TAM — India's total organised eldercare + non-emergency medical logistics + home-healthcare opportunity. India's home-healthcare market alone is estimated in the several-billion-USD range and growing double-digits; layered with NEMT and companion care across 100M+ elders, a defensible TAM framing is on the order of US$8–12B and expanding as the population ages. SAM — urban, digitally-reachable, paying households: elders in Tier-1/Tier-2 metros with adult children who are NRI or metro professionals, plus addressable hospital/dialysis transport volume. A reasonable SAM is roughly US$1.5–2.5B. SOM — what we can realistically capture in 3–5 years starting from the Bengaluru corridors and expanding to Chennai/Hyderabad: a beachhead of recurring dialysis/oncology cohorts plus NRI/professional retail. A grounded 3-year SOM target is US$15–40M of serviceable revenue. Four engines, deliberately diversified so no single payer can sink us: (1) Families/NRIs: subscription family plan (monthly/quarterly/yearly) + per-visit fee; (2) Corporates: per-employee licence + utilisation top-up (our PMPM-style recurring analogue); (3) Hospitals/Clinics: platform fee on completed referrals + integration/reporting SaaS; (4) Partner marketplace: Platform can monetise verified lead-generation and listing fees from vetted partners, medical-equipment rental (hospital beds, oxygen concentrators), post-operative step-down facilities, home diagnostics. A future layer, once the core relationship is established. Three categories: (1) Ride-hailing / gig apps (Uber, Ola): curb-to-curb only, no advocacy, no clinical literacy, no report; they solve transit, not care. (2) Fragmented home-healthcare and nurse-staffing players (Portea, Care24, KareXpert-type providers, local agencies), strong in nursing/attendants but not built around the escorted hospital journey, the family-visibility layer, or NEMT orchestration. (3) Informal local helpers / individual attendants: no credentialing, no accountability, no data trail. Our wedge is the integrated escorted-journey + family-visibility + closed-loop-data product that none of them own end-to-end. B2C: targeted digital campaigns to NRI communities (alumni networks, diaspora associations, expat forums) and metro professionals (LinkedIn, apartment-association groups, parenting/eldercare communities); referral loops (a satisfied NRI child is our best channel). B2B2C: direct partnerships with dialysis centres, geriatric and orthopaedic OPDs where we pitch measurable no-show reduction, this is a warm, recurring, high-intent channel. B2B: corporate HR/wellness teams where eldercare stress is a hidden absenteeism driver. Our lowest-CAC, highest-retention entry is the recurring dialysis/chemo cohort. Land in Bengaluru hospital corridors with the recurring-treatment wedge (dialysis, oncology), where demand is predictable and the ROI to both family and hospital is provable. Sequence the payers: Phase 1: B2C family/NRI retail (cash now, no sales cycle); Phase 2 — corporate wellness + hospital referral SaaS; Phase 3 — insurer contracts. Prove the unit economics and no-show-reduction data in the pilot, then replicate corridor-by-corridor to Chennai and Hyderabad before pan-metro expansion. Eldoo Care’s vision is to become India’s foundational, high-trust care-mobility infrastructure, ensuring no one is denied healthcare due to physical transit barriers. Beginning with our asset-light, wheelchair-accessible NEMT and bedside CareMate network in Bengaluru, our five-year roadmap expands to 60+ Tier-1 and Tier-2 cities. By compounding micro-hub density and hospital integrations, we project scaling to ₹130+ Cr in gross transaction value (~₹40+ Cr net revenue), reaching operating profitability from Year 2. As Indian healthcare matures toward value-based care and insurance-reimbursed Social Determinants of Health (SDOH), Eldoo will serve as the core orchestration layer for insurers and health systems to lower the total cost of care. Beyond patient transport, this high-trust backbone naturally unlocks home health, diagnostics, and accessible everyday mobility, guaranteeing dignified, independent living across urban and semi-urban India. NA Funded by Founders Yes IITACB sits at the intersection of exactly what we need: deep-tech and AI credibility to sharpen our care-matching and RPM stack; proximity to the ₹16bn Bommasandra / Bangalore health-and-bio ecosystem where our hospital, dialysis, and diagnostic partners cluster; and a mentor-and-investor network to help us navigate MVAG aggregator licensing, SDOH reimbursement design, and our seed round. We're building a regulation-heavy, trust-first healthcare platform, the IIT brand, technical rigour, and institutional network materially de-risk both our tech and our go-to-market. (1) Complete and instrument the Bengaluru clinical pilot with hard data, no-show reduction, unit economics, repeat-rate, NPS. (2) Convert 3–5 hospital/dialysis partnerships in the Bommasandra/Bangalore corridor. (3) Harden the AI care-matching and RPM early-warning models with pilot data. (4) Finalise compliance (ECO/GST, MVAG applicability, DPDP) with expert mentorship. (5) Close a seed round via investor-connect. (6) Build the IP and defensibility narrative for scale. Yes, we're open to virtual participation where needed, though given our pilot is Bengaluru-based and our target partners cluster around Bommasandra, on-site presence is genuinely valuable to us and we'd prioritise in-person engagement. Bommasandra is one of India's densest health, bio, and med-device clusters, ringed by hospitals, dialysis chains, and diagnostic labs, precisely our B2B2C supply-and-demand base. We can (1) sign anchor dialysis/oncology/geriatric partners there as our recurring-cohort beachhead; (2) tap the med-device and RPM ecosystem for affordable connected-vitals hardware; (3) recruit CareMates and clinical talent from the surrounding institutional base; and (4) use Bangalore's NRI-heavy, professional demographic as our highest-intent B2C market. IITACB can open these institutional doors, lend clinical-validation credibility to our pilot, and connect us to investors who understand health-tech and SDOH. Yes Co-working and meeting space for founder-and-pilot operations and partner pitches; access to labs/technical facilities to prototype and validate our RPM/connected-vitals integration; mentorship and office-hours for AI, compliance, and go-to-market; the investor-connect and demo-day platform for our raise; and the IIT network for clinical advisors and technical hires. Yes Supporting feature A three-sided platform (Family app, Companion/CareMate app, Ops/Admin console) on a shared services backend. Core services: booking & scheduling (with standing-order/recurring-trip generation), the AI care-matching engine, real-time dispatch and GPS tracking, an SOP-driven visit-execution workflow, an auto-report generator, and a payer/hospital analytics dashboard. A credentialing/verification service gates supply (Aadhaar, police check, references, training) before any companion can accept work. Integration layer exposes APIs for hospital OPD/discharge systems and, later, insurer/TPA partners. Data layer captures the closed-loop trail (profiles, visits, vitals, outcomes) that feeds the models. Built to be no-code/low-code in early phases (landing + WhatsApp/Typeform intake + Airtable dispatch + WhatsApp Business + Razorpay) and to migrate to a hardened custom stack as volume scales, capital-light first, engineered second. The closed-loop care dataset: structured elder health/mobility/language profiles, matched CareMate performance, visit outcomes, transcribed clinical instructions, medicine-adherence confirmation, and (with RPM) between-visit vitals, all linked per member over time. No ride-hailing app or nurse-staffing agency generates this integrated trail. It compounds: more visits to better matching, better condition-detection, better outcome-reporting to payers to stronger contracts to more visits. The credentialing network (slow, trust-based, hard to copy), the closed-loop data flywheel, multi-sided lock-in across families/hospitals/corporates/insurers, and regulatory-grade compliance as a switching-cost moat. A ride-hailing giant can't easily bolt on clinical advocacy and credentialing; a local agency can't build the data-and-tech layer or the multi-payer network. We sit in the defensible middle. Operational metrics: on-time arrival rate, visit-completion rate, no-show/cancellation reduction at partner OPDs (benchmarked toward Modivcare's published 30–50%), reassignment-on-delay latency, and CareMate verification pass-rate (target 100% pre-visit). Product metrics: match-acceptance rate and match quality (did the best-match companion complete successfully), report-delivery time (target 50% target), NPS from adult children (>60 target), and, as RPM matures, avoidable-ER/readmission proxies. Versus competitors whose "reliability" is an untrained driver showing up, our differentiator is a measured, auditable service-level trail. We handle sensitive senior health data, so DPDP Act 2023 compliance is built in from the pilot, not retrofitted: explicit consent, purpose-limitation, encryption in transit and at rest, role-based access, audit logs, and breach-notification processes, with DPDP terms embedded in hospital MOUs and the family-reporting flow. On tax/regulatory compliance: we register for GST from day one as an Electronic Commerce Operator (Section 9(5) CGST), discharge the correct GST on NEMT fares/commission/companion services, and structure vehicle-partner and companion contracts with TDS and background-check obligations. The closed-loop data trail is our product, so protecting it is existential, not a checkbox. Yes. The Rights of Persons with Disabilities (RPwD) Act, 2016 and Supreme Court accessibility mandates raise providers' duty to enable dignified, accessible patient access, the exact friction we remove. Startup India / DPIITgives us the Section 80-IAC tax-holiday path (incorporation window extended to 31 March 2030) and the now-abolished angel tax (from 1 April 2025), easing fundraising. Niti Aayog Reimagining Care, 2026 reports states to establish the National Care Council and the broader national push toward home-based and value-based care and digital health (ABDM) tailwinds our model. As insurance-linked SDOH reimbursement emerges, policy will increasingly pay for exactly what we do. Yes, and we're managing them deliberately. (1) Aggregator licensing: the Motor Vehicles Aggregator Guidelines (MVAG 2020/2025) may apply to our NEMT-aggregation leg via Karnataka's rules (GPS, panic buttons, 24/7 control room, insurance); applicability to a low-volume health aggregator is being confirmed with transport-law counsel. (2) GST treatment: cab-based NEMT does not get the ambulance exemption and companion/subscription services are taxable at 18%; we price to absorb this rather than assume an exemption. (3) DPDP enforcement: health-data handling carries real penalties, hence privacy-by-design. (4) Frequent change: GST rates, aggregator rules, and the new Income-tax Act 2025 (effective 1 April 2026) shift often; we treat compliance as an ongoing, expert-advised function. We view this regulatory complexity as a moat: it deters casual entrants. Honestly assessed: (1) Supply/credentialing is the first bottleneck, CareMate recruitment, verification, and training must industrialise without diluting quality; we mitigate with a standardised credentialing pipeline and tiered training. (2) Matching and dispatch must move from prototype logic to a hardened, low-latency engine with corridor-level route density. (3) The no-code stack (Airtable/Make.com) will hit limits and must migrate to a custom backend with proper data infrastructure. (4) Quality assurance and liability across many simultaneous live visits requires a real Ops command centre and incident-response protocol. (5) Compliance surface grows per city (state aggregator rules differ). We've mapped these; the pilot is designed to stress-test 1 and 2 first. Our founding team combines the exact regulatory, operational, and technological domains required to build India’s care-mobility layer: Arun (Co-Founder | Strategy, Technology & Operations): M.S. (TU Berlin); 8+ years in management consulting at EY-Parthenon and Roland Berger advising on institutional transformation, ecosystem design, and operational scale. Arun leads the technology roadmap, matching-engine architecture, and route economics. Omprakash (Co-Founder | Policy, Partnerships, & Governance): M.Sc. & M.P.P. (LSE), FRSA; former civil servant with the Government of Tamil Nadu specializing in public systems and digital governance. Omprakash leads institutional hospital partnerships, regulatory compliance (DPDP/RPwD Act), and go-to-market strategy. Product architecture and operational workflows are currently founder-led in collaboration with contract full-stack engineers. To scale our dispatch engine and hospital data pipelines post-pilot, we are actively recruiting: Lead Full-Stack / Backend Engineer: To own core booking microservices, hospital EHR/OPD API integrations, and companion dispatch workflows. Data Scientist / Operations Research Specialist: To optimize predictive dispatch algorithms—focusing on multi-stop corridor batching, dead-heading minimization, and multi-variable companion matching (language, mobility certifications, proximity). Mobile & Telemetry Engineer: To build real-time GPS tracking, in-visit SOP milestone checklists, and automated family reporting pipelines. Our application data is owned (first-party, generated by our platform, the proprietary closed-loop dataset). Tooling in the early phase uses standard commercial/SaaS components under their licences (e.g., Razorpay for payments, WhatsApp Business API, Airtable for early dispatch) and permissively-licensed open-source libraries for the app layer. We use no scraped or improperly-licensed third-party datasets. As we build the custom stack, we'll rely on standard open-source frameworks (MIT/Apache-licensed) and retain full ownership of our models and data. The data flywheel is the engine: every visit adds labelled outcomes that retrain the matching and condition-intelligence models, so match quality and prediction accuracy improve with volume. We instrument the operational and outcome metrics above and iterate against them. Pilot data hardens the RPM early-warning thresholds. We'll run structured feedback loops from CareMates (SOP friction), families (NPS, report quality), and hospital partners (no-show impact). As we scale, we move from heuristic matching to learned models and add route-optimisation as corridor density grows. India-first, by design, the demographic wave, the migration-driven access gap, and the absence of an organised solution make India the largest and most urgent opportunity, and the regulatory/cultural specificity rewards a local-first build. But the underlying model is globally portable: the same "children far from ageing parents" problem exists across the diaspora corridors we already serve (Gulf, Southeast Asia) and in other rapidly-ageing emerging markets. We build for India, with an architecture and playbook designed to travel. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/z3CJLxe3yq4r-Eldoo_Care_Pitch_Deck_IITACB.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/z3CJLxe3yq4r-Eldoo_Care_Pitch_Deck_IITACB.pdf Deeply. Our thesis is "The Dignity Metric", eldercare as an infrastructure of absolute trust. The mission is that no ageing parent should face a hospital alone, and geography should never sever a child from their parent's care. The impact is measurable and triple: clinical (better adherence to fewer avoidable admissions), social (dignity and independence for elders, peace of mind for families), and economic (lower total cost of care for the system, and dignified livelihoods for the CareMate workforce we credential and train). We're built by children, for their parents, that's not a tagline, it's the founding motivation. Yes. Both co-founders come from underrepresented backgrounds as first-generation learners from remote, non-metro regions of the state. Navigating public systems, higher education (LSE, TU Berlin), and global institutions required overcoming significant structural and economic barriers. This firsthand lived experience fuels our deep conviction to build accessible systems for overlooked communities. Furthermore, this background directly informs our venture: Eldoo Care is dedicated to solving healthcare mobility for India’s most underserved and socially vulnerable demographic, frail, mobility-restricted senior citizens and individuals with disabilities who lack localized family support. Hariharan - IITM Alumni checked
Aug 17, 2026 @ 11:00 AM Dr. Varun Dutt chandan@iiots.in https://www.linkedin.com/search/results/all/?keywords=Intiot%20Services%20Private%20Limited&origin=RICH_QUERY_SUGGESTION&heroEntityKey=urn%3Ali%3Aorganization%3A71704376&position=0 http://www.iiots.in%20 9805647823 Directors of the company We met at IIT Mandi, and now it's been almost 8 years since we have been working together 2 Our biggest strength is the combination of strong technical expertise, field experience, and a mission-driven team. We bring together IIT-backed R&D, indigenous hardware development, AI/IoT capabilities, and a deep understanding of real-world challenges, enabling us to rapidly develop, deploy, and scale reliable solutions for critical infrastructure and disaster management. Intiot services pvt. ltd. www.iiots.in Himachal Pradesh Intiot Services Pvt. Ltd. is an IIT Mandi-incubated deep-tech startup developing indigenous IoT, AI, and sensor-based solutions for disaster resilience and environmental monitoring. Its flagship Landslide Monitoring & Early Warning System (LMS) provides real-time monitoring and advance alerts to help protect lives, infrastructure, and critical road corridors. Intiot also develops solutions for air quality, rockfall, and flood monitoring, with a focus on affordable, scalable, and Made-in-India technology. Intiot addresses the lack of affordable, reliable, and real-time early warning systems for landslides and other environmental hazards. Landslides often occur with limited warning, causing loss of lives, road blockages, and infrastructure damage. Our indigenous sensor- and AI-based systems continuously monitor ground conditions and provide timely alerts, enabling authorities to take preventive action and improve disaster preparedness. Intiot provides indigenous, IoT- and AI-enabled monitoring and early warning solutions for landslides and other environmental hazards. Our flagship Landslide Monitoring & Early Warning System uses MEMS sensors, geophones, extensometers, weather sensors, edge computing and cloud analytics to continuously monitor ground movement and detect early signs of slope instability. The system delivers real-time data and alerts through a centralized dashboard and communication channels, enabling authorities to take timely preventive action. Our solutions are affordable, scalable, and designed for challenging terrain and critical infrastructure. Our solution combines indigenous hardware, MEMS-based sensing, IoT connectivity, edge computing, AI/ML analytics, and cloud-based monitoring into a single end-to-end platform. Unlike conventional systems that rely heavily on imported and expensive equipment, Intiot offers a cost-effective, locally developed solution designed specifically for India’s challenging mountainous terrain. Our field deployments, proprietary algorithms, accumulated site data, IIT-backed R&D, and growing IP portfolio create strong technical and market defensibility. Revenue Revenue Goverment agencies DDMA, SDMA and NDMA and some privates firms also. Intiot’s TAM includes the global market for landslide, rockfall, flood, dam, air-quality, and other environmental monitoring and early-warning systems. With increasing climate-related disasters, infrastructure development, and demand for real-time monitoring, the addressable market spans governments, road and highway authorities, mining, hydropower, railways, smart cities, and industrial infrastructure. India alone has thousands of kilometres of vulnerable mountain roads and critical infrastructure requiring continuous hazard monitoring, creating a large and growing opportunity for affordable indigenous solutions. Intiot’s SAM focuses on the Indian market for landslide, rockfall, flood, dam, and environmental monitoring systems across government departments, NHAI, state road authorities, hydropower projects, railways, mining, smart cities, and other critical infrastructure. In the near term, we are targeting high-risk Himalayan states such as Himachal Pradesh, Uttarakhand, Jammu & Kashmir, and Sikkim, followed by expansion into other landslide-prone regions of India. This represents a significant opportunity for indigenous, cost-effective, real-time monitoring and early-warning solutions. Intiot’s initial SOM is focused on landslide-prone regions and critical infrastructure projects in Himachal Pradesh, Uttarakhand, Jammu & Kashmir, and other Himalayan states. We aim to capture the market through deployments with government authorities, NHAI, hydropower companies, road agencies, and private infrastructure operators. Based on our existing field deployments, partnerships, and sales pipeline, Intiot can realistically target 100–200 monitoring systems over the next 3–5 years, creating a potential revenue opportunity of approximately ₹15–30 crore from system sales, deployment, AMC, and monitoring services Intiot follows a B2G, B2B and B2B2C revenue model. Revenue is generated through the sale and deployment of monitoring systems, site surveys, installation and customization, annual maintenance contracts (AMC), and recurring cloud-based monitoring and alert subscriptions. Additional revenue comes from data analytics, system upgrades, and integration with existing disaster-management and infrastructure platforms. This combination of hardware sales and recurring service revenues provides both immediate and long-term revenue growth. Our competitors include global geotechnical and slope-monitoring companies such as Sisgeo, RST Instruments, Geosense, and Worldsensing, as well as Indian system integrators and conventional manual monitoring solutions. Intiot differentiates itself through indigenous manufacturing, MEMS-based low-cost sensing, AI/ML analytics, real-time IoT connectivity, and an end-to-end early-warning platform specifically designed for India’s mountainous terrain and infrastructure needs. Intiot acquires customers through direct engagement with government departments, NHAI, PWDs, hydropower companies, infrastructure operators, and disaster-management authorities. We leverage IIT Mandi’s ecosystem, industry partnerships, field demonstrations, pilot projects, tenders, referrals, and technology showcases to build credibility. Successful deployments are converted into AMC, monitoring subscriptions, repeat orders, and expansion to additional sites, while strategic partnerships help us scale across India. ntiot’s go-to-market strategy follows a pilot-to-scale approach. We initially target high-risk government and infrastructure projects through direct B2G/B2B engagement, technology demonstrations, site surveys, and pilot deployments. Successful pilots are converted into larger deployments and long-term AMC and monitoring contracts. We will scale through partnerships with infrastructure companies, system integrators, NHAI/PWDs, hydropower and mining companies, while leveraging IIT Mandi’s ecosystem and our existing field deployments to build market credibility. Our long-term vision is to build Intiot into a global deep-tech company for disaster resilience and environmental intelligence. We aim to create an integrated, AI-driven early-warning platform covering landslides, rockfalls, floods, air quality, and critical infrastructure, enabling governments and industries to predict risks, respond faster, and protect lives and assets. We aspire to make India a global leader in affordable, indigenous disaster-monitoring technology and expand our solutions to vulnerable regions worldwide. yes 55 lacs Yes We are applying to IITACB Incubator to accelerate the commercialization and scale-up of Intiot’s indigenous disaster-monitoring technologies. IITACB’s strong technology ecosystem, industry connect, mentorship, incubation support, and access to funding can help us strengthen our product, expand market access, build strategic partnerships, and scale deployments across India and international markets. We believe the incubation ecosystem will help transform our proven field technology into a scalable global solution. During the programme, we aim to accelerate product commercialization, strengthen our technology and AI capabilities, and expand deployments of our Landslide Monitoring & Early Warning System. We seek mentorship on business scaling, funding, IP and regulatory strategy, customer acquisition, and market expansion. Our goal is to secure strategic partnerships, convert pilots into large-scale deployments, and build a scalable business model for national and global markets. yes Bommasandra’s large industrial ecosystem and Bengaluru’s strong deep-tech, IoT, infrastructure and technology markets can help Intiot build strategic partnerships for manufacturing, component sourcing, system integration and commercialization. We can leverage Bengaluru’s access to technology companies, infrastructure firms, investors and industry customers to scale our disaster-monitoring solutions beyond the Himalayan region. IITACB can support us through industry connects, mentorship, pilot opportunities, funding access, technology partnerships and market linkages, helping Intiot establish Bengaluru as a key hub for product development and national expansion. Yes We would leverage IITACB’s infrastructure for business development, product refinement, customer demonstrations, investor meetings, and industry collaboration. Access to meeting and co-working spaces would help our team engage with Bengaluru’s deep-tech ecosystem, while technical facilities and industry networks can support prototyping, testing, system integration, and scale-up. We also aim to use IITACB’s incubation ecosystem for mentorship, investor connects, talent acquisition, and strategic partnerships to accelerate Intiot’s national and global expansion. Yes Core engine Intiot follows a multi-layer IoT and AI architecture. Field sensors such as MEMS accelerometers, geophones, extensometers and weather sensors continuously collect ground and environmental data. An edge gateway performs data acquisition, preprocessing and sensor fusion, with 4G/LoRa connectivity transmitting data to the cloud. The cloud platform stores and analyses data using AI/ML algorithms to identify abnormal patterns and risk levels. A web dashboard provides real-time visualization, while automated alerts are sent to authorities through SMS, app and other communication channels for timely action. Intiot has built a growing proprietary dataset from real-world landslide monitoring deployments across Himalayan terrain. The data includes time-series measurements from MEMS sensors, geophones, extensometers, weather parameters, ground movement patterns, and site-specific event observations. This field data supports calibration and validation of our AI/ML models, improves early-warning accuracy, and creates a strong data advantage that becomes more valuable as deployments increase across different geological and climatic conditions. Our solution is defensible through a combination of indigenous hardware, proprietary sensor-fusion and AI/ML algorithms, real-world field data, and accumulated deployment expertise. Our systems are specifically optimized for India’s challenging mountainous terrain and cost-sensitive infrastructure projects. Our growing IP portfolio, IIT-backed R&D, established field deployments, customer relationships, and proprietary site data create technical, operational, and market barriers for competitors. We evaluate our technology through field deployments and continuous validation against ground-truth observations and conventional monitoring methods. Key metrics include sensor accuracy, detection sensitivity, false-alarm rate, warning lead time, data availability/uptime, communication reliability, response time, power consumption, and system durability under harsh environmental conditions. We compare these parameters with conventional and commercial monitoring systems during pilot deployments to improve reliability, reduce false alerts, and ensure consistent performance. Intiot follows a security-by-design approach for data privacy and system security. Sensor data is securely transmitted from field devices to the cloud using authenticated communication and access controls. Role-based access ensures that only authorized users can view or manage project data. We maintain secure backups, controlled data access, device authentication, and regular software updates. Customer and site data is treated as confidential, with data sharing limited to authorized stakeholders and applicable contractual, regulatory, and government requirements. Yes. Intiot benefits from government initiatives focused on disaster risk reduction, climate resilience, infrastructure safety, Digital India, Make in India, and Atmanirbhar Bharat. Policies supporting indigenous technology, public-sector innovation, smart infrastructure, and early-warning systems create opportunities for adoption by government departments and infrastructure agencies. Government funding and startup programmes through institutions such as DST, MeitY, NHAI, state disaster-management authorities, and technology incubators can further support R&D, validation, and large-scale deployment. The primary regulatory risks relate to approvals, procurement requirements, data-security standards, telecom/connectivity regulations, and project-specific certifications for deployment on critical infrastructure. Since Intiot operates in disaster monitoring and early-warning applications, acceptance by government and infrastructure agencies may require extensive field validation and compliance with applicable standards. We mitigate these risks through IIT-backed R&D, field testing, documentation, engagement with relevant authorities, and adherence to applicable Indian regulations and standards. At 10X scale, the key challenges would be manufacturing capacity, supply-chain management, field installation and maintenance, data processing, and customer support. Our cloud and IoT architecture is designed to scale horizontally, but deployment operations and quality control would require strengthening. We plan to address this through standardized hardware, multiple manufacturing and component partners, automated cloud infrastructure, regional service teams, remote diagnostics Yes. Intiot has an in-house deep-tech team with expertise in IoT, embedded systems, sensor technology, AI/ML, data analytics, cloud platforms, wireless communication, and geotechnical monitoring. The team works closely with IIT Mandi faculty and researchers to develop and validate indigenous sensing and early-warning technologies. Our expertise spans the complete technology lifecycle—from sensor and hardware development to edge computing, AI-based analytics, cloud dashboards, field deployment, testing, and system integration. We use a combination of proprietary field data generated through our deployments, publicly available datasets, standard open-source software libraries, and commercially available electronic components. Open-source components are used in accordance with their respective licenses, while our sensor integration, system architecture, data-processing workflows, AI/ML models, deployment know-how, and field datasets are internally developed and owned by Intiot/IIT Mandi. We have filed multiple patents, including a granted patent for our low-power, low-cost air-quality monitoring technology. IP references can be provided as required. We follow a continuous improvement cycle based on real-world field data, customer feedback, and system performance metrics. We continuously improve sensor calibration, AI/ML models, false-alarm reduction, warning accuracy, connectivity, power efficiency, and hardware reliability. Increasing deployment data enables better model training and site-specific calibration. We also conduct regular field validation, software/firmware updates, predictive maintenance, and R&D with IIT Mandi to incorporate new sensing technologies and improve system performance Both. Intiot is initially focused on India, particularly landslide-prone Himalayan states and critical infrastructure, where we have strong field validation and customer opportunities. In the next phase, we plan to expand to global markets with similar disaster risks, including Southeast Asia, Nepal, Bhutan, Japan, and other mountainous and climate-vulnerable regions. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/KM2vS5cyTnjC-Write-up-on-LMS.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/KM2vS5cyTnjC-Write-up-on-LMS.pdf http://iiots.in%20 Yes. Intiot is a mission-driven deep-tech startup focused on reducing the human, economic, and environmental impact of natural hazards. Our primary objective is to make reliable and affordable early-warning technology accessible to communities, governments, and infrastructure operators in vulnerable regions. Our Landslide Monitoring & Early Warning System enables timely action to protect lives, roads, bridges, and critical infrastructure. By developing indigenous, scalable technologies for landslides, floods, rockfalls, and air quality, we aim to strengthen disaster resilience and contribute to safer and more sustainable communities in India and globally. NA Dr. Varun Dutt Intiot is an IIT Mandi-incubated deep-tech startup with field-validated technology and experience in deploying indigenous landslide and environmental monitoring systems. Our solutions are designed for challenging terrain, critical infrastructure, and government applications. With strong R&D, an expanding IP portfolio, existing deployments, and strategic partnerships, we are positioned to scale our technology across India and international markets. checked
Aug 17, 2026 @ 10:48 AM Ritwik Raj ritwikr850@gmail.com https://www.linkedin.com/in/ritwik-raj-084b123b9?utm_source=share_via&utm_content=profile&utm_medium=member_android http://NA 917462085177 Founder 1 Our biggest strength is our ability to learn and build quickly with limited resources. We combine strong software/AI skills with a willingness to tackle difficult robotics problems from first principles, validate ideas through working prototypes, and continuously adapt based on technical and customer feedback. FrontierX Robotics https://github.com/aachcoder47/swarm-project Patna We are building an AI intelligence layer that enables one centralized system to coordinate heterogeneous robots and make robotic capabilities reusable across different physical platforms. Industrial robots often operate as isolated systems, requiring significant integration and task-specific engineering to coordinate different robot types. This makes deploying flexible multi-robot systems difficult and expensive. Our platform provides a centralized AI brain that understands tasks, robot capabilities and environmental state, then plans and coordinates actions across heterogeneous robots. We are building it on ROS 2, Open-RMF and Gazebo, with a working PC-based simulation and a roadmap toward physical validation. Our focus is on capability-aware intelligence rather than building another robot or fleet-management system. The architecture aims to let one intelligence layer dynamically compose capabilities across different robot bodies and recover when robot availability or conditions change. MVP Pilots Industrial manufacturers, warehouses, logistics operators, infrastructure/inspection companies, and robotics integrators deploying multiple heterogeneous robots. Na Na Na B2B software and robotics platform: annual enterprise software subscriptions/licensing, implementation fees, and eventually usage-based fees for autonomous robotic operations. Open-RMF and traditional robotics fleet-management platforms; industrial automation/integration companies; and emerging physical-AI/robotics intelligence platforms. Our differentiation is the capability-aware AI layer for dynamically coordinating heterogeneous robot bodies rather than only fleet scheduling or controlling a specific robot. Initially through direct founder-led outreach to manufacturers, warehouses and robotics integrators, technical demonstrations and pilot projects. We will use early pilots to validate the product, generate measurable ROI and expand through enterprise partnerships and robotics integrators. Start with a narrow industrial use case such as autonomous inspection or multi-robot coordination. Deploy a small pilot with an industrial customer, measure operational improvements, then convert successful pilots into annual enterprise contracts and expand across additional robots and facilities. To build an intelligence layer for the physical world where one system can understand, coordinate and continuously adapt fleets of heterogeneous robots. Long term, we aim to make robotic intelligence reusable across machines and enable autonomous physical workforces across factories, logistics, infrastructure and other industrial environments. Na Na Yes We are building a centralized AI intelligence layer for heterogeneous robots and have already developed a working simulation. We are applying to access deep-tech mentorship, robotics infrastructure, industry connections and support in moving from simulation to a physical prototype and industrial pilot. Our primary goal is to validate our architecture on physical robots, develop a functional multi-robot prototype, identify a strong industrial use case, conduct an initial pilot, and establish the technical and commercial foundation needed for scale. Yes Bengaluru's robotics, manufacturing, logistics and technology ecosystem can provide access to potential industrial users, robotics companies, suppliers and engineering talent. IITACB can help us connect with relevant companies for pilot opportunities, provide technical mentorship and infrastructure, and help validate our technology against real industrial requirements. Yes We would use the facilities as a development and testing base for our robotics platform, including prototyping, hardware integration, simulation-to-reality testing, robot networking and system validation. Access to workspace, technical infrastructure, mentors and the surrounding industrial ecosystem would help us accelerate our transition from a software simulation to a physical multi-robot prototype and customer pilot. Yes Core engine Our architecture uses a centralized AI intelligence layer above ROS 2 and Open-RMF. It maintains a representation of robot capabilities and environment state, interprets high-level tasks, decomposes them into executable actions, selects suitable robots, coordinates execution and re-plans based on feedback or failures. Gazebo is currently used for simulation, with the architecture designed to transition to heterogeneous physical robots. Currently none. We are at the prototype stage and do not yet have a proprietary industrial dataset. Our initial development uses simulation and open-source robotics resources. We plan to build proprietary operational data through controlled physical deployments and customer pilots. Our potential defensibility is in the combination of capability-aware task reasoning, heterogeneous robot abstraction, orchestration and failure recovery, rather than in a single model. As we deploy on physical systems, we aim to build proprietary evaluation data, integration knowledge, robot capability models and deployment infrastructure that become increasingly difficult to replicate. We are currently establishing a benchmark in simulation before physical deployment. Key metrics include task completion rate, planning latency, recovery success after robot failures, number of human interventions, performance across different robot configurations, task-specific engineering effort and successful execution of previously unseen tasks. We will compare these metrics against conventional rule-based workflows and existing robotics orchestration approaches. At the current simulation stage, we do not process sensitive customer data. For physical deployments, we plan to minimize data collection, isolate customer environments, encrypt communications and storage, implement role-based access controls and maintain audit logs. Safety-critical robot actions will be subject to deterministic validation and operational constraints rather than relying solely on an AI model. Government support for robotics, AI, advanced manufacturing and deep-tech R&D can significantly accelerate our development through grants, incubators, prototyping infrastructure and industry programs. We are exploring relevant Indian deep-tech and robotics initiatives. Yes. Physical robots operating around people and industrial equipment create safety, cybersecurity and liability requirements. Depending on the deployment environment, industrial safety standards, machinery requirements, data regulations and site-specific compliance may apply. We plan to address these requirements progressively as we move from simulation to controlled pilots. The main risks are centralized planning becoming a bottleneck, communication latency, increased state complexity, robot interoperability, simulation-to-reality differences and safety validation across larger fleets. Our architecture therefore needs hierarchical planning, distributed execution, event-driven updates, fault isolation and deterministic safety layers as it scales. Currently, the core technical development is founder-led. I have hands-on experience in AI/ML and software engineering and am developing the robotics architecture using ROS 2, Open-RMF and Gazebo. As we move toward physical validation, we plan to build a multidisciplinary team covering robotics, controls, embedded systems, mechanical engineering and AI. We currently use open-source robotics infrastructure including ROS 2, Open-RMF and Gazebo, along with relevant robotics simulation and AI/ML libraries. These components are used under their respective open-source licenses. Our orchestration architecture, task reasoning logic, capability representation and application-specific software are being developed by us. We currently do not claim granted patents or proprietary datasets. We will continuously benchmark the system in simulation, introduce increasingly difficult and unseen tasks, test different robot configurations and systematically measure failures. Physical pilots will provide real-world feedback that can be used to improve capability models, planning, perception and recovery. We will maintain regression tests and safety validation so improvements do not compromise reliability. Both. We plan to use India as our initial development and validation market because of its growing manufacturing, logistics and robotics ecosystem, while designing the platform from the beginning for global industrial environments and heterogeneous robot platforms. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/eLsCmEpXt1WW-Beautiful.ai-One-Brain.-Many-Bodies.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/eLsCmEpXt1WW-Beautiful.ai-One-Brain.-Many-Bodies.pdf https://youtu.be/lFrWSDpOpI8?si=gGDpGp04pii0q4_R Yes. Our mission is to make intelligent robotics more accessible and capable of handling complex physical work. By enabling multiple robots to share intelligence and coordinate autonomously, we aim to improve productivity while reducing human exposure to dangerous, repetitive and hazardous tasks across manufacturing, logistics and infrastructure. Na Na I am a 17-year-old student founder building this from India with limited resources. I have already developed a working simulation of the core robotics architecture and am now focused on proving it on physical robots. I am looking for technical mentorship, infrastructure and industry access to turn the research prototype into a real-world system. checked
Aug 17, 2026 @ 10:04 AM Arnab Banerjee arnab15031985@gmail.com http://www.linkedin.com/in/arnab-banerjee-5bb42720 http://NA +919874542242 Founder & Director I’m a first-generation entrepreneur, with 16 years of experience across leading companies including P&G and Heinz, specializing in sales, NPD, GTM strategy, and business development. I am passionate about building B2B and D2C brands and disrupting traditional market through innovation and technology. Currently, I am pursuing an Advanced Entrepreneurship Development Programme from IIT Kanpur while exploring new entrepreneurial opportunities. 1 First-generation entrepreneur | 16+ years with P&G & Heinz | MBA – IISWBM | NPD & GTM strategist | B2B brand builder | Disrupting traditional Market | Advanced Entrepreneurship Development Programme – IIT Kanpur. AquaLeaf NA Kolkata Replacing single-use plastic water bottles with aluminium-free carton packaging Problem Statement India uses millions of single-use plastic bottles every day for drinking and packaged water. Poor collection and recycling systems result in a large amount of plastic waste ending up in landfills, drains, rivers, and the environment. The challenge is to develop a safe, affordable, convenient, and sustainable alternative to single-use plastic water bottles that can reduce plastic waste without compromising drinking-water quality and consumer convenience. 1.Recyclable Gable-Top Carton: Sustainable alternative to single-use plastic and glass bottles. 2.HORECA First: Targeting hotels, restaurants, cafés, resorts and institutional customers. 3.Premium Sustainability: Helps hospitality brands offer an eco-conscious guest experience. 4.ESG Advantage: Supports measurable plastic-reduction and sustainability goals. 5.Lightweight & Stackable: Lower packaging weight and more efficient storage and transportation. 6.Simpler Packaging: No aluminium barrier layer required for water. 7.Fast-Turnover Model: Short shelf life aligns with daily HORECA consumption. 8.Cost-Efficient Logistics: Avoids the complexity and cost of aseptic long-shelf-life packaging. Proprietary Packaging Design|Exclusive Packaging Technology/Partnerships Idea Testimonials Primary: Hotels, Resorts & Restaurants Premium HORECA: 4–5 Star Hotels & Luxury Hospitality Cafés & Premium Restaurants Corporate & Institutional Catering Events, Conferences & Banquets Phase 2: Airlines, Hospitals & Retail ₹43,600 Cr Indian packaged drinking-water market (FY2025), growing ~9–11% annually. HORECA : ~₹16,000 Cr | Hotels • Restaurants • Cafés • Resorts Initial SOM: ₹28–55 Cr B2B Revenue Model Direct sales to Hotels, Restaurants, Cafés & Resorts Recurring monthly supply contracts Bulk pricing with volume-based margins Customized/private-label packaging for hotel chains Premium pricing for sustainable packaging & branding Phase 2: Corporate, Events & Institutional Clients Primary Competitor: Glass bottled-water suppliers |Secondary Competitor: PET/plastic bottled-water brands| Emerging Competitor: Other sustainable packaging solutions| Indirect Competitor: Traditional packaged-water suppliers Direct B2B Sales: Target hotels, resorts, restaurants & cafés. Annual/Monthly Contracts: Lock in recurring HORECA supply agreements. Pilot Programs: Start with selected premium hotels and restaurants. Hotel Chain Partnerships: Approach procurement & sustainability teams. Distributor Partnerships: Build regional HORECA distribution. ESG-led Selling: Demonstrate plastic reduction and sustainability impact. Referral Model: Incentivize existing HORECA clients to introduce new accounts. Private Label: Offer customized packaging for hotel brands. Beachhead: Premium hotels, resorts & restaurants in Eastern India Pilot: Partner with 10–20 flagship HORECA properties Direct Sales: Founder-led B2B sales to procurement & management Contracting: 6–12 month recurring supply contracts ESG Pitch: Position as a premium plastic-reduction solution Private Label: Customized cartons for hotel chains Distribution: Build city-wise HORECA delivery network Scale: Kolkata → Eastern India → Pan-India Expansion: Corporate, events, hospitals & airlines after HORECA validation Key KPI: Contracts signed, litres/property/month, repeat rate & customer acquisition cost Build India’s leading sustainable drinking-water brand for HORECA Replace single-use plastic and glass bottles with recyclable carton packaging Become the preferred sustainable water partner for hotel chains Build a strong Eastern India → Pan-India distribution network Expand into corporate, institutional, travel & retail segments Develop proprietary sustainable packaging technology Create a measurable plastic-reduction & ESG platform Ultimately build a circular, low-carbon beverage packaging ecosystem Stage: Idea / Pre-Seed NA Yes I am applying to TACB Incubation to validate, refine and scale my idea with the right mentorship, industry expertise and ecosystem support. As an early-stage venture, I want to leverage TACB’s network to develop the product, validate the HORECA market, build strategic partnerships and become investment-ready for future growth. Validate the product-market fit with HORECA customers Develop a commercially viable and scalable packaging solution Build pilot partnerships with hotels and restaurants Refine the B2B revenue and go-to-market model Develop a strong supply chain and operational plan Prepare for seed funding and investor readiness Build a roadmap to scale from Eastern India to Pan-India YES Manufacturing Ecosystem: Leverage Bommasandra’s large industrial base to identify packaging, printing, filling, logistics and manufacturing partners. Bommasandra has around 5,000 industrial units and strong road connectivity. Product Development: Use Bengaluru’s engineering and technology ecosystem to refine carton design, filling processes and supply-chain efficiency. Market Validation: Pilot the solution with Bengaluru’s premium hotels, restaurants, cafés and corporate hospitality segment. Industry Connections: Use IITACB’s network of corporates, industry experts and research institutions to develop strategic partnerships. Mentorship: Get guidance from IIT faculty, alumni and industry leaders on packaging technology, business model, scalability and operations. Investor Access: Leverage IITACB’s investor and alumni network to prepare for seed funding and future scale-up. Scale-up: Use Bengaluru as the initial innovation and manufacturing ecosystem before expanding the proven model to Eastern India and Pan-India. Yes If provided a seat at IITACB, I would use the infrastructure as a base for product development, business validation and investor preparation. I would leverage the workspace for focused execution, access to the IIT ecosystem and mentors, meetings with industry partners and investors, and development of the HORECA pilot. The objective would be to use IITACB not simply as an office, but as a launchpad to validate, build and scale the venture. Yes Supporting feature Our business architecture is a B2B, HORECA-first model built around sustainable drinking-water packaging. HORECA Consumption Data: Track water consumption by property, location and season. Demand Forecasting: Predict order volumes and optimize production and inventory. Customer Insights: Understand hotel preferences, pack sizes, pricing and consumption patterns. Logistics Data: Optimize delivery routes, frequency and cost per litre. ESG Data: Provide customers with measurable plastic bottles avoided and sustainability impact. Long-Term Moat: Build a proprietary database that improves pricing, forecasting, operations and customer retention as the network scales. Proprietary Packaging: Develop a water-specific carton optimized for recyclability, strength, moisture resistance and cost, with potential IP around design and closure. Strategic Supply Partnerships: Secure exclusive/long-term agreements with carton converters and filling partners to lock in capacity, pricing and quality. HORECA Network: Build strong, recurring relationships with hotels, resorts, restaurants and cafés, creating distribution and customer-access barriers. ESG Advantage: Provide measurable data on plastic bottles replaced, waste reduction and sustainability impact, helping HORECA customers strengthen ESG reporting. Premium Brand: Position the product as “the sustainable water served by premium hospitality”, turning packaging into part of the guest experience. Supply-Chain Advantage: Build a HORECA-specific sourcing, filling and delivery model designed to achieve lower delivered cost per litre and operational efficiency. Data & Customer Lock-in: Build proprietary consumption and demand data, supported by recurring contracts, automated replenishment and customized/private-label solutions. 1.Recyclability: % recyclable material and recovery potential. 2.Material Efficiency: Packaging weight per litre of water. 3.Leak & Seal Performance: Leakage, seal integrity and shelf-life testing. 4.Moisture Resistance: Carton performance under refrigeration and handling. 5.Strength & Stackability: Compression strength and transport durability. 6.Production Efficiency: Filling speed, rejection rate and manufacturing yield. 7.Cost Efficiency: Packaging + filling + logistics cost per litre. 8.Sustainability: Plastic reduction and carbon footprint per litre vs. PET/glass. 9.HORECA Validation: Customer acceptance, repeat orders and operational feedback. 10.Scalability: Ability to manufacture consistently at commercial volumes. 1.FSSAI Compliance: Ensure packaged drinking water meets applicable FSSAI standards and licensing requirements. 2.BIS Standards: Follow relevant BIS requirements for packaged drinking water. 3.Packaging Compliance: Ensure carton materials, inks, adhesives and closures are food-contact compliant. 4.Legal Metrology: Comply with mandatory labelling, declarations and packaging requirements. 5.Environmental Compliance: Follow applicable Plastic Waste Management and EPR requirements. 6.Quality Control: Implement batch-wise testing, traceability and hygiene protocols. 7.Supplier Compliance: Work only with certified packaging, water-treatment and filling partners. 8.Regulatory Monitoring: Continuously track changes in FSSAI, BIS, EPR and other applicable regulations. Our business benefits from strong policy tailwinds around plastic-waste reduction, EPR, sustainable packaging and corporate ESG adoption, creating a favourable regulatory environment for alternatives to conventional PET water bottles. Our key regulatory risks are food safety, packaging compliance, labelling and environmental obligations. We plan to mitigate these through certified manufacturing partners, accredited testing, compliant food-contact materials, batch-level traceability and continuous regulatory monitoring. 1.Production Capacity: Carton manufacturing and filling capacity may become a bottleneck. 2.Supply Chain: Shortages or price increases in packaging materials could impact margins. 3.Quality Control: Maintaining consistent water and packaging quality across multiple facilities. 4.Logistics: Daily HORECA deliveries become more complex as geographic coverage expands. 5.Working Capital: Larger inventory and longer B2B payment cycles may increase cash-flow pressure. 6.Customer Support: Managing a larger network of HORECA accounts and customized requirements. 7.Technology & Data: Need scalable systems for demand forecasting, inventory and automated replenishment. 8.People & Management: Need experienced teams and clear processes to manage rapid expansion. NO NA 1.Packaging R&D: Continuously improve carton strength, moisture resistance, recyclability and cost. 2.Smart Manufacturing: Partner with advanced filling and packaging facilities to improve efficiency and quality. 3.Quality Technology: Implement digital batch tracking, testing and traceability. 4.Demand Analytics: Use HORECA consumption data for demand forecasting and inventory planning. 5.Route Optimization: Use technology to optimize delivery routes and reduce logistics cost and carbon footprint. 6.Customer Platform: Develop automated ordering, subscription and replenishment systems for HORECA clients. 7.ESG Dashboard: Provide customers with real-time data on plastic reduction and environmental impact. 8.Continuous Innovation: Collaborate with IITs, packaging experts and technology partners to develop next-generation sustainable packaging. Phase 1: Build and validate the business in India, starting with HORECA in Eastern India. Phase 2: Expand across Pan-India through hotel chains and regional distribution. Phase 3: Enter international hospitality markets, particularly markets with strong demand for sustainable packaging. Long-term Vision: Build an India-born sustainable water-packaging brand with global potential. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/8p3fvBrvdQuX-AquaLeaf-Investor-Pitch-Deck.pptx, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/8p3fvBrvdQuX-AquaLeaf-Investor-Pitch-Deck.pptx Our mission is to reduce dependence on single-use plastic water bottles by making sustainable drinking water accessible, convenient and commercially viable for the HORECA industry. Environmental Impact: Reduce plastic waste and promote recyclable packaging. Business Impact: Provide HORECA with a premium, cost-efficient alternative. Social Impact: Encourage responsible consumption and a shift toward sustainable packaging. Long-Term Goal: Make sustainable water packaging the new standard in hospitality. Advanced Entrepreneurship Development Programme – IIT Kanpur | Bengal Business Council Prof Ashwani Kumar IIT Kanpur , I sincerely look forward to the opportunity to be part of the IITACB incubation ecosystem, where I can leverage its mentorship, industry network and infrastructure to validate, build and scale this venture. I believe the incubation centre can play a critical role in transforming this idea into a scalable, sustainable and investment-ready business. checked
Aug 17, 2026 @ 9:43 AM Gaurav Srivastava sandhya.srivastava@siliconsprint.com https://www.linkedin.com/in/gsgaurav/ +91 8810670236 1 AS a team, we complement each other works. Sandhya Srivastava is experienced on the startup working and finance having experience in running several businesses. Gaurav Srivastava has decade of experience leading technical teams and have created several products from scratch for many big tech firms. Lumivoyage https://siliconsprint.com Delhi Leetcode for ASIC design engineer Platform for VLSI design learning and experimenting siliconSprint is a next-generation, LeetCode-style practice platform purpose-built for SystemVerilog and Verilog engineers. It transforms real-world RTL and logic design problems into bite-sized, industry-relevant coding challenges with instant feedback and measurable skill progression. The platform addresses a major gap in hardware education: while software engineers have abundant interactive practice tools, hardware engineers still rely on static textbooks, interviews, or expensive EDA tools. siliconSprint aims to become the daily practice destination for RTL engineers, from students to senior ASIC/FPGA professionals. no proper platform currently that caters the needs of various domains in ASIC design Users Users, Revenue VLSI professionals and learners 27 Billion 3.8 Billion 112 Million Subscription and support hdlbits, edaplayground organic and Ads on Linkedin connections with universities Long term, siliconsprint aim to form a bridge between the fabrication facilities and the independent developers, similar to tiny tapeout such that an independent developer will be able to fabricate the chip independently through the platform. LLP 3000 Yes to gain traction and able to monetize the platform revenue model and marketing yes try to create awareness with the new government program to bring VLSI fabrication to India. Bangalore will be a majority market for the VLSI individual. IIT ACB can help in forming relation with IITs to standardize the teaching and siliconsprint can help in teaching the state of the art techniques to students Yes we aim to form a center to manage our daily activities for the platform. Also the infrastructure help can help us train models to ASIC design methodology aiming for the learning use. Yes Supporting feature The frontend is React, backend is Spring boot. database - mysql, mongodb for the AI, currently using CahtGPT api with various prompts and agents in the workflows in the platform. We have android app published on the playstore. Current platforms aims at building the space generic for coding where designers needs to write verifications tests themselves, which makes them impractical to practice. our vision to train the model specific to interview preparation will make our solution unique and defensible than the competitors. competitors either are aiming at the freshers or just providing tools for users to experiment . siliconsprint is unique in that respect as we provide verification suite to our question base. along with that, we also cater backend practice platform, verification engineers platform and other aspects of VLSI design. out data is encrypted at the database level for password and other security features. for the data privacy we do not aim to monetize the data on the platform. NA the tools of VLSI are resource intensive. Currently the platform is hosted on aws with mid tier EC2 instance. auto scaling is off due to funding constraints. if the system scales at 10x, the tools running will be a bottleneck and might crash the website. We have the consultant that have the knowledge of fine tuning llms and building a solutions using AI the tools verilator, openlane and openroad are the open source tools used in the platform. they are MIT license and anyone can use them the platform progress is snapshot at weekly/monthly basis and analyzed to improve upon the performance. we aim to capture global market for the practice platform. For India we envision to build a tiny tapeout program. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/SdlUv11Szw7V-siliconSprint_pitch_deck.pptx-1.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/SdlUv11Szw7V-siliconSprint_pitch_deck.pptx-1.pdf NA NA checked
Aug 17, 2026 @ 7:05 AM Sushil Kumar Verma sushilverma208016@gmail.com https://www.linkedin.com/in/sushilverma208016/ +91-8574907562 1 Our biggest strength is strong technical execution combined with a clear product vision. We have the engineering capability to build the complete AI stack—from multimodal ingestion, OCR and RAG to scalable backend infrastructure and cross-platform applications—and the ability to rapidly prototype, validate and iterate the product around real user problems. IKnow Lucknow IKnow is a Personal Knowledge OS that turns the scattered information in your digital life into a private, continuously growing AI memory that you can search, understand and reason over. People have enormous amounts of valuable information scattered across phone galleries, PDFs, downloads, documents, notes, books and work files, but there is no intelligent layer that can understand and connect this information. Finding a past prescription, bill, warranty, travel document, meeting decision or information from a book often requires manually searching through hundreds or thousands of files. Existing AI assistants are powerful but generally lack deep, persistent and user-specific context. IKnow solves this information fragmentation problem by creating a continuously growing personal knowledge layer over the user's own data. IKnow allows users to securely add content such as photos, PDFs, documents, books and text notes into personal Knowledge Spaces. AI models process and understand this content using OCR, computer vision, document understanding, embeddings and RAG. The information is indexed and connected so users can ask natural-language questions and receive answers grounded in their own content, with relevant sources for verification. For example, a user can ask “What medicines did the doctor prescribe during my last visit?”, “Where is my washing machine invoice and when does the warranty expire?”, “How much did I spend at restaurants last Sunday?”, or “Explain this topic using only the books and notes I uploaded.” New content can be processed asynchronously as it is added, allowing each user's knowledge base to continuously evolve without retraining the underlying foundation model. IKnow's differentiation is the creation of a persistent, multimodal and user-specific knowledge layer rather than a conventional chatbot or document Q&A tool. It can continuously ingest heterogeneous personal information such as images, PDFs, books and notes, extract structured entities and relationships, and connect information across time and sources. The long-term defensibility comes from the user's continuously growing knowledge graph/context, personalized retrieval and reasoning, domain-specific Knowledge Spaces, multimodal processing pipeline and strong privacy/isolation architecture. New information can be incrementally indexed as it arrives, allowing the system to become increasingly useful without repeatedly training a foundation model. Over time, IKnow aims to evolve from a search-and-answer product into a Personal Knowledge OS capable of reasoning over and taking actions based on a user's chosen information. MVP Signups We want to build the intelligence layer for a person's digital life—moving from simply retrieving information to understanding context, connecting knowledge and eventually helping users make decisions and take actions. Yes We will use Bengaluru as our initial product-validation and scaling market, leveraging its strong technology, startup and industrial ecosystem to test IKnow across personal, education, professional and enterprise use cases. IITACB can accelerate us through AI/ML mentorship, IIT faculty and alumni expertise, industry and corporate connections, pilot opportunities, workspace, investor access and academic collaborations. Its Pan-IIT ecosystem can help us validate the product across domains and build a globally scalable Personal Knowledge OS from Bengaluru. Yes We plan to use IITACB as our Bengaluru product-development and validation base. We would leverage the workspace and meeting facilities for product development, user research, demos and team collaboration; IIT faculty, alumni and industry mentors for AI/ML, RAG, privacy and scalability guidance; and IITACB's workshops, networking and Demo Days for business, GTM and fundraising support. We also aim to use its IIT, academic and industry ecosystem to identify pilot users, partnerships and enterprise use cases, helping IKnow evolve from an MVP into a scalable global Personal Knowledge OS. Yes Core engine 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/lRhWgWnENxyU-IKnow_Pitch_Deck.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/lRhWgWnENxyU-IKnow_Pitch_Deck.pdf NA checked
Aug 17, 2026 @ 2:48 AM Kartik Sabikhi kartik@bulkifyb2b.com https://www.linkedin.com/in/kartiksabikhi/ http://NA +91-7081252252 Kartik Sabikhi - Director (Full Time Business Executor/Operator), Parashar Sabikhi - Consultant Promoter (Marketing) We are family related to each other, Parashar is working as Zonal Sales Manager at Timex Group India Ltd with a demonstrated history of working in the consumer goods industry. Skilled in Channel Management, Account Management, and Retail. 1 Kartik has experienced Horeca industry closely since 2014, worked as Channel partner for Brands in Food Service Industry in Kanpur, now building a one stop platform for Horeca Procorement which is expanding its roots in Indian Geography. Parashar pursued his MBA in Marketing from MIT, Pune. Worked with LG Electronics, Currently working with Timex Group India Ltd, Handling Sales and Trade Channels for West Bengal and North East India. Our biggest strength is the combination of deep on-ground HoReCa experience and strong marketing and trade-channel expertise. The founding team brings hands-on understanding of procurement, distribution, customer relationships and operations, complemented by professional expertise in brand building, sales strategy and market expansion. Bulkify www.bulkifyb2b.com Kanpur Bulkify is a B2B commerce platform for the HoReCa industry, enabling hotels, restaurants and cafés to source food, beverages, packaging and kitchen supplies through a single platform. We combine technology, procurement infrastructure and localized fulfillment to make business purchasing faster, more reliable and cost-efficient. HoReCa businesses rely on multiple fragmented suppliers to procure thousands of products, resulting in inconsistent pricing, limited product discovery, manual ordering, stock uncertainty and significant time spent managing procurement. Bulkify solves this by creating a single, technology-enabled procurement platform tailored to the needs of hotels, restaurants and cafés. Bulkify is a technology-enabled B2B procurement platform built specifically for the HoReCa industry. We bring a wide range of food, beverage, packaging and kitchen supplies onto one platform, enabling businesses to discover products, compare pricing, place orders and manage recurring procurement digitally. Our localized fulfillment model enables faster and more reliable delivery, while data-driven operations help improve availability, pricing and purchasing efficiency. Bulkify’s defensibility comes from combining technology with deep HoReCa market knowledge and localized fulfillment infrastructure. Our growing product catalogue, customer purchasing data, supplier relationships, pricing intelligence and repeat-order behaviour create a compounding advantage. As we expand into more markets, increasing order density improves assortment, availability, procurement economics and fulfillment efficiency, creating stronger network effects and higher customer stickiness. Product-Market Fit Users, Revenue Hotels, Restaurants, Cafes, QSRs and College Canteens/Cafeterias $30 billion (₹2.5 lakh crore) annually in India ₹50,000–60,000 crore (~$6–7B) ₹500–1,000 crore (~$60–120M) Bulkify generates revenue primarily through margins on products sold through its B2B procurement platform. We source products from manufacturers and brands and sell them to HoReCa businesses, earning a margin on each transaction. As the platform scales, additional revenue opportunities include private-label products, supplier-led brand partnerships and technology-enabled services. “The biggest competition today is not another technology platform—it is the highly fragmented traditional procurement ecosystem. Platforms like Hyperpure and Udaan are validating the opportunity, while Bulkify is building a focused, regional-first model for the underserved HoReCa market.” Bulkify acquires customers through a combination of direct sales, referrals, digital acquisition and local market outreach. Our sales team targets hotels, restaurants, cafés, caterers and other food-service businesses, while our digital platform enables customers to discover and reorder products conveniently. We also leverage existing customer networks, brand partnerships, targeted promotions and referral-led growth. As we build density within each market, repeat purchases and word-of-mouth are expected to reduce customer acquisition costs and strengthen organic growth. Our expansion strategy is to build and validate a repeatable city-level playbook before scaling geographically. Each market begins with focused customer acquisition and localized assortment, followed by increasing order density and fulfillment efficiency. Once the model reaches sufficient scale, we plan to accelerate expansion through local operating partners/franchisees supported by Bulkify's technology, brand, procurement systems and operating processes. Our long-term vision is to build India’s leading technology-enabled procurement platform for the HoReCa industry. We aim to make Bulkify the default procurement partner for restaurants, cafés, hotels and food-service businesses by combining a comprehensive product ecosystem, intelligent technology, localized fulfillment and a scalable city-expansion model. Over time, we envision building a connected network across India that makes HoReCa procurement simpler, more transparent, reliable and efficient. Private Limited Company NA Yes We are applying to IITACB Incubator to accelerate Bulkify’s transition from a successful regional HoReCa business into a scalable technology-led platform. We seek access to experienced mentors, industry expertise, strategic networks and fundraising support to strengthen our business model, technology, operations and expansion strategy. We believe IITACB’s ecosystem can help us validate our scale-up strategy, build investor readiness and connect with the right partners to expand Bulkify across India. We aim to strengthen Bulkify’s business model and prepare it for rapid, sustainable expansion. During the programme, we want to refine our technology and operating model, validate our city-expansion strategy, develop a scalable franchise framework, strengthen our financial and unit economics, build investor readiness and connect with strategic mentors, industry partners and potential investors. Our goal is to emerge with a validated and repeatable growth model ready for expansion across multiple cities. Yes Bengaluru offers Bulkify an opportunity to validate and scale our model in one of India’s most dynamic HoReCa and technology markets. The Bommasandra industrial ecosystem can provide access to manufacturers, brands, logistics partners and potential enterprise customers, while Bengaluru’s large and diverse restaurant and café market can help us test our procurement model at greater scale. IITACB can help us leverage its strong network of IIT alumni, industry leaders, mentors and investors to strengthen our technology, operating model and expansion strategy. We see Bommasandra as a potential strategic base for building our South India presence and using Bengaluru as a launchpad for wider expansion. Yes We would leverage IITACB’s infrastructure as a strategic base for building and scaling Bulkify. The workspace would support our core and technology team, while the meeting and collaboration facilities would enable us to engage with mentors, industry partners, suppliers, customers and investors. We also aim to leverage the incubator’s innovation ecosystem, networking opportunities and access to IITACB’s broader industry and academic network to strengthen our technology, operating processes and expansion strategy. Over time, Bengaluru would serve as an important hub for developing our South India presence. Yes Supporting feature Bulkify follows a modular, cloud-based architecture designed to support B2B commerce, procurement, inventory, order management and fulfillment. The platform consists of a customer-facing web and mobile layer, product and catalogue management, pricing and customer-specific business rules, cart and order management, payments, inventory and fulfillment workflows, and backend integrations with our business systems. The architecture is designed to support multiple cities and operating locations while maintaining centralized visibility, data and control. We are progressively building APIs and automation layers to enable integration with suppliers, logistics partners, payment providers and future operating partners. Bulkify is building a proprietary dataset around HoReCa procurement behaviour. As customers transact on our platform, we capture insights across product demand, purchase frequency, basket composition, pricing, seasonality, customer preferences, product substitution and reorder patterns. Combined with market-level data on assortment, availability and fulfillment, this enables us to improve recommendations, inventory planning, pricing and customer retention. As our customer and transaction base grows across cities, this dataset becomes increasingly valuable for understanding and optimizing HoReCa procurement at a granular market level. Bulkify’s defensibility will be built through a combination of localized market density, proprietary HoReCa procurement data, customer relationships and a standardized technology-enabled operating model. As we scale, increasing transaction volumes generate deeper insights into demand, pricing, assortment and purchasing behaviour, allowing us to continuously improve availability, economics and customer experience. Our city-level operating playbook and planned partner-led expansion model will further enable us to replicate this advantage efficiently across markets, creating increasing barriers to competitors as our network grows. We evaluate our technology primarily through business and platform performance metrics rather than feature comparison alone. Key metrics include platform uptime, page and API response time, order success rate, payment success rate, inventory and pricing accuracy, order-processing time, delivery SLA adherence, system error rates, repeat-order rate and customer adoption of digital ordering. We continuously monitor these metrics to identify bottlenecks and improve reliability, scalability and customer experience. As we scale, we intend to benchmark these metrics against industry standards and leading B2B commerce platforms. Bulkify follows a privacy and security-first approach to handling customer, business and transaction data. We limit data collection to information required for operating the platform, apply role-based access controls and authentication, and use secure cloud infrastructure and encrypted data transmission. Payment-related information is processed through authorized payment providers rather than being stored directly by Bulkify. We maintain appropriate access controls, backups, monitoring and audit trails, and are continuously strengthening our policies and processes in line with applicable Indian data protection, taxation and e-commerce requirements. As we scale, we plan to further formalize security audits, vulnerability assessments and compliance controls. No No At 10x scale, the primary pressure points would be inventory planning, fulfillment capacity, supplier coordination, customer support, technology infrastructure and working-capital management. Our current systems can support the present scale, but significant growth will require greater automation, stronger forecasting, scalable cloud infrastructure, standardized operating processes and stronger city-level fulfillment capabilities. We are designing Bulkify’s technology and operating model modularly so these functions can scale independently rather than creating a single point of failure. Our planned partner-led city expansion model will also help us scale operational capacity without proportionally increasing our fixed infrastructure. No, Bulkify currently does not have a dedicated in-house deep-tech team. Our current technology stack is focused on building a scalable B2B commerce and procurement platform, supported by experienced technology partners and internal business expertise. As we scale, we plan to build an in-house technology team with expertise in data engineering, AI/ML, demand forecasting, recommendation systems, automation and platform engineering to develop proprietary capabilities around HoReCa procurement. Bulkify currently uses Zoho’s suite of business and commerce applications as part of its technology infrastructure, along with third-party APIs, cloud services and open-source components where required. These are used under their respective commercial, API or open-source licenses. Our proprietary assets include Bulkify-specific business workflows, configurations, operational processes, customer and transaction data, and business logic developed around HoReCa procurement. We currently do not have registered patents or formal IP filings. As the platform evolves, we intend to develop and protect proprietary technology, automation, data models and algorithms where commercially relevant. Bulkify plans to continuously improve technology performance through real-time monitoring, customer feedback, transaction data and regular performance reviews. We will track metrics such as platform uptime, response times, order and payment success rates, inventory and pricing accuracy, system errors, digital adoption and repeat ordering. We will progressively automate manual processes, optimize integrations and strengthen our cloud infrastructure as transaction volumes grow. Over time, we also plan to build stronger in-house technology capabilities in data analytics, AI/ML, demand forecasting and automation to improve procurement efficiency and customer experience. Currently for India 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/1RAP1Hj6oOYh-Bulkify_IITACB_Investor_Pitch_Deck.pptx, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/1RAP1Hj6oOYh-Bulkify_IITACB_Investor_Pitch_Deck.pptx Dr. Arks checked
Aug 17, 2026 @ 12:20 AM Abhishek Mitra abhikm8010@gmail.com https://www.linkedin.com/in/abhishek-mitra-966006194/ 917204421046 Founder of Civlee building a sovereign social network for India centered around audiobooks. Previously a Senior Data Scientist at Bain and Company Currently not committed to a single cofounder to allow for more agility. Will seek a cofounder after product market fit. 1 Currently not committed to a single cofounder to allow for more agility. Will seek a cofounder after product market fit. Civlee (Equanimity Labs) civlee.com Bengaluru Sovereign social media startup centered around audiobooks Challenging the media oligopoly of Instagram, Youtube and Tiktok via niche focus on audiobooks Civlee is a platform that allows anyone to write fiction using AI and turn it into multi-voice and emotive audiobooks using AI for zero cost. We do not charge for background play unlike Youtube and Instagram. Monetization using ads and ad-free low cost subscriptions. Network effect of a critical mass of users makes a community platform impossible to disrupt Users Users, Signups Book and Audio Book consumers $234.3 Billion (Social Media Global Market Report 2026) $29.0 Billion (Ebooks and Audiobooks) $1.17 Billion (Ebooks and Audiobooks in India, IMARC Group and 6Wresearch) Ad monetization, purchases and subscriptions PocketFM, Audible, Wattpad Hook reels using Instagram, Youtube and other social media platforms SEO through conversion of classics to audiobooks and targeted advertising to build a core of daily active users To build an Indian sovereign social media platform that aggregates all long-form audio content consumers (audiobooks, webnovels, podcasts, audio monologues) onto one platform by becoming the Youtube for Audio. We aim to undercut global giants by offering background play for free among other consumer surpluses. OPC Pvt Ltd Bootstrapped Yes I am an IIT Jammu alumni, a member of IIT ACB short term membership and seek to involve myself in the IIT ACB ecosystem My goal is for our platform to cross the 1000 DAU threshold with the help of strategic advice, ecosystem connections with the optionality to raise a pre-seed round if we have defensible traction Yes We offer personalized advertising deals to any Bommasandra or allied industrial groups that would like to advertise on our platform to reach Indian and global consumers No If capital permits we would utilize the seat facilities to meet other startup founders and experts Yes Core engine We use LLMs to help write fiction novels and use open source TTS models to generate fiction audiobooks for cents. We use Python for backend, NextJS for frontend and are ready on day one to convert our webapp to mobile apps to Android and IOS through our capacitor compatible architecture. We have the capacity to train the cheapest vernacular text to speech models in languages like Kannada, Tamil, Bengali etc Proprietary vernacular TTS models that allow us to offer audiobook generation compltely for free and network effects. As a Masters in AIML from IIT Jammu, I have been trained to develop 10B parameter plus models and have a network of data scientists who can do the same. So we have a talent moat as well. A single audiobook of 1000 words costs us a maximum of $0.01 (1 cent) to generate including LLM costs and Text to speech. Competitors like Eleven Labs would cost close to $0.25 for the same. 25x cost advantage. Even Indian labs like Sarvam would cost on the order of 10 cents (10x price advantage). We can show our cost per book generation if anyone would like to verify. We have a Grievance Redressal Officer and comply with all Indian IT and Copyright regulation. We take compliance very seriously and allow for user data deletion subject to retention requirements by Indian IT Law (about 180 days in archives). We benefit from increasing consumer spending capacity as we are ad monetized We are impacted by IT and Digital Intermediary regulation but are proative in ensuring compliance. Currently its highly scalable with usage of greenlet events, async network requests. We can handle upwards of 500 live connections so a 100K users a day is handleable by us. I as founder am the AI deep tech expert. I hold an MTech in Artificial Intelligence and Machine Learning from IIT Jammu. My masters thesis was in non-training methods to increase audio accuracy scores of audio generation models. I was one of the likely first 5 Indian users to have built an application with GPT2 that ranked on the first page of Hackernews. We will use AI4Bharat datasets for training vernacular TTS models. They are largely MIT or Apache licensed. As I move into delegation oriented role in the startup I will find Data Scientists and AI Research Engineers from my network to handle core model development. I have access to other engineering and non-tech hiring networks also. Building primarily for global markets with India as a potential starting point. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/HJpcy3HfP4jh-Civlee_-Home-of-creation-4.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/HJpcy3HfP4jh-Civlee_-Home-of-creation-4.pdf http://Our%20platform%20is%20live%20at%20-%20civlee.com We are a for-profit startup but have launched "Project Hearall" (https://civlee.com/project-hearall) a pro bono initiative to convert all 70,000 global public domain classic books into audiobooks for public consumption for free. NA Commander Pradeep Prasad checked
Aug 16, 2026 @ 11:22 PM Khush Duggar khushduggar811@gmail.com http://linkedin.com/in/khushduggar/ http://NA 6206157038 Khush Duggar, COO, 4th year Dual Degree, Bioscience and Biotechnology; Aryan Rajak, CEO, 4th year Dual Degree, Bioscience and Biotechnology; Krishna Kant, CTO - Molecular & Nanotechnology, 4th year Dual Degree, Bioscience and Biotechnology; Rudranarayan Pradhan, CTO - Electronics, 4th year Dual Degree, Mechanical Engineering 6 months since we started working on the idea; we have known each other for 2 years and have worked in the same lab. 2 We share a common goal and are completely aligned on the idea, with the perfect mix of all backgrounds working perfectly together in a structured way. KiFayti Kharagpur LIG based sensors for water and soil testing for the detection of heavy metals, pesticides and other chemicals Diagnosis of water and soil quality at a much affordable, accessible and quick Our innovation is a complete point-of-need water screening system comprising single-use LIGMIS test strips and a compact, portable electrochemical reader. Each strip integrates a three-electrode sensing cell with passive microfluidic channels, fabricated through one-step laser writing on inexpensive polyimide film. The laser directly converts the polymer surface into porous, conductive 3D laser-induced graphene (LIG), simultaneously defining electrodes and fluidic architecture without cleanroom processing, photolithography, or expensive substrates, enabling rapid, scalable, and remarkably low-cost manufacturing. The core sensing strategy targets four priority contaminant classes: heavy metals (cadmium and lead), the carbamate pesticide carbofuran, nitrates, and phenolic compounds. Selectivity and sensitivity for each analyte are engineered by functionalizing the LIG working electrode with tailored nanomaterials. Copper nanoparticles provide electrocatalytic activity for nitrate reduction; carbon quantum dots enhance electron transfer kinetics and provide abundant surface functional groups for heavy metal preconcentration and pesticide detection; and additional nanohybrid modifiers are selected per target contaminant. Crucially, these modifications are achieved via single-step electrodeposition and complementary deposition routes including atomic doping, magnetron sputtering, physical vapor deposition (PVD), or drop casting, allowing systematic optimization of each sensor chemistry while keeping fabrication simple and reproducible. By deliberately avoiding enzymes and biological recognition elements, our strips eliminate cold-chain storage, short shelf life, and fragility, the chief failure modes of existing biosensor strips, making them robust for field deployment in harsh Indian environmental conditions. In use, a water sample is wicked into the microfluidic channel, and the reader performs voltammetric analysis (e.g., anodic stripping voltammetry for metals), delivering quantitative results within minutes. Results can be logged and geotagged via smartphone connectivity, building contamination maps over time. The system targets industries, pollution control boards, agricultural extension services, NGOs, and community water testing programs, replacing costly permanent probes with affordable, distributed screening. The technical core lies in materials engineering, not assembly. We exploit laser-induced photothermal conversion of polyimide into hierarchical 3D porous graphene, a non-trivial laser–polymer interaction requiring precise control of fluence, scan speed, and atmosphere to tune porosity, sheet resistance, and electrochemical surface area. Onto this, we engineer analyte-specific nanohybrid interfaces (copper nanoparticles, carbon quantum dots, doped heterostructures) via single-step electrodeposition, atomic doping, magnetron sputtering, PVD, and drop casting, each demanding optimization of nucleation, adhesion, and electrocatalytic behavior. Achieving ppb-level selectivity for Cd, Pb, carbofuran, and nitrates on a disposable, enzyme-free platform constitutes genuine electrochemistry and nanofabrication research. Idea Hydroponics and aquaculture farms, QC labs, Industries innvolving hazardous waste water treatment, JalJeevan Mission 1.1Bn$ 73-180CR INR 7.2 - 20 Cr INR Razor and Blade model ICP-MS and AAS Labs NA NA State-level government contracts, ensuring safe water to all Indians, especially in rural India, making sure no child loses IQ due to heavy metal poisioning, as current JalJeevan mission does not tests for heavy metals now in their kits, they just test it for 9 basic parameters. NA NA Yes Mentoring and right guidance from industry leaders A minimum-viable product and a basic market entry, i.e., the first customer Yes Bommasandra isn't just a nearby industrial zone for KiFayti. It is effectively a live customer base for LIGMIS. The cluster houses Biocon, Syngene, AstraZeneca, and over a hundred pharma and biotech manufacturers who are all statutorily required to monitor effluent for heavy metals like lead and increasingly boron under KSPCB and CPCB norms. Right now, that testing is lab-based, slow, and expensive, which is exactly the gap our LIG electrochemical platform is built to close with real-time, field-deployable, multi-analyte detection. I would use IITACB's Bommasandra location to pursue pilot conversations directly with these companies' EHS and compliance teams, positioning LIGMIS as an on-site effluent monitoring tool rather than a lab replacement to get a faster sales cycle than our current B2G water-utility angle. From IITACB specifically, I would want: Domain mentors from pharma CROs and manufacturing, like Biocon or Syngene adjacent alumni, to pressure test our sensor's performance claims against industry grade ICP-MS benchmarks since this is a real gap in our validation data. Warm introductions into EHS and compliance functions at Bommasandra companies for pilot MOUs. Non-dilutive funding guidance, looking at Karnataka's Biotech Policy and KBITS schemes which we haven't explored compared to our current BIRAC or DST NIDHI focus. Government industry bridge access, since IITACB explicitly positions itself as the interface between IITs, industry, and government, making it directly useful for de-risking our B2G procurement timeline. No NA Yes Supporting feature It is much cheaper and faster than the existing ICP-MS and AAS labs for heavy-metal testing. We can get instant results through our sensors, which are enabled with geotagging for large water bodies and agricultural fields. We track limit of detection, limit of quantification, sensitivity, linear range, selectivity against interfering ions, reproducibility across batches, response time, and cost per test. We compare ourselves against lab methods like ICP-MS and AAS, which are accurate but expensive and slow, and against portable test strips or meters, which are fast and cheap but less accurate and usually single analyte. Right now we're working on Lead against certified standards, but full comparison across all analytes in our 9-analyte claim isn't done yet. We don't have a live product data pipeline yet, so this is more of a plan than something built. Going forward, we'll follow India's DPDP Act for any data linked to a person, like a farmer's identity tied to soil readings. If we sell to government bodies, the CPCB data-sharing rules would apply as well. Our plan is to encrypt data in transit and at rest, keep client data anonymised or aggregated by default, and be clear in contracts that raw readings belong to the client. It's fair to say this is a roadmap item right now, not something already implemented. Yes. On the funding side, BIRAC BIG, DST-NIDHI and IIT KGP TTO grants are non-dilutive options we're pursuing, along with Startup India recognition for tax benefits. On the demand side, government programs like Jal Jeevan Mission and CPCB monitoring mandates create real demand for water quality sensors, and the Soil Health Card scheme supports our agri angle around boron deficiency in orchards. A few. We may need BIS or CPCB certification before selling to government buyers, and since our sensor category is genuinely new, there may not be a clear existing standard to certify against, which could slow approval. The Legal Metrology Act may apply once we begin making commercial measurement claims. DPDP Act compliance becomes relevant once we handle personal data. There's also an IP risk: we're planning a provisional patent filing around December 2026, and any public disclosure before then, such as at a pitch event, could undermine patentability in some cases. India provides a 12-month grace period for our own prior disclosure, but it needs to be tracked carefully rather than assumed safe. Most likely in this order: fabrication consistency breaks first, since we're currently making electrodes manually on a single laser setup. Manual calibration and quality checks won't scale either; we'd need an automated QC process. Our 9-analyte panel claim is still unproven at scale, so pushing volume before that's solid adds risk. Team capacity is honestly the biggest constraint right now; we're four students, not a manufacturing operation. Sourcing electrode materials at higher volumes could also become expensive or hard to obtain. And government sales cycles don't get faster just because we scale; that's a relationship bottleneck, not a tech one. Yes, we're a student team based in Prof. Vinay Patel's One Health Technologies Lab at IIT Kharagpur. I, Aryan Rajak, lead the team, and Krishna Kant, Khush Duggar, and I are pursuing a dual degree in Biotechnology. Krishna has expertise in automations and nanochemistry, helps in the detection of analytes, while khush helps with everything in business side. Rudranarayan is pursuing a dual degree in Mechanical engineering and is working on the reader and electronics part in parallel. We'll keep using our optimization pipeline to explore parameter space we haven't tested yet, like line interval settings. We'll add analytes to the panel one at a time, validating each properly before claiming it. Once we have pilots running, real-world data on things like interference and electrode wear will feed back into better calibration. We're also planning to implement remote calibration updates via firmware, so we can improve accuracy without needing to replace hardware in the field. Both, first serving in India, then taking it globally the most cheap and affordable way to check heavy metals in water and soil 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/Zo4AjEUGvrJy-AryanRajak_DeepTech_KiFayti.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/Zo4AjEUGvrJy-AryanRajak_DeepTech_KiFayti.pdf https://drive.google.com/file/d/1Mbl5I-kTeUlSvRHRU1sgLH6LlY8UQfpa/view?usp=drivesdk At the core, this is about serving India's own people with India's own technology. Millions of farmers across the country lose crop value every year to soil issues like boron deficiency, without ever knowing the real cause, simply because no affordable field test exists for it. Millions more depend on water sources that go untested for heavy metal contamination because proper testing requires sending samples to a city lab, waiting weeks, and paying more than most people can afford. We built KiFayti because we believe protecting our farmers' land and our citizens' drinking water shouldn't depend on expensive imported lab equipment or foreign-made sensors. This is a chance to build genuinely indigenous deep tech, developed and owned in India, that reduces our dependence on costly foreign alternatives and puts reliable testing directly into the hands of our own farmers, gram panchayats, and public health bodies. For us, this isn't just a business opportunity; it's about using our education from an Indian institution to solve an Indian problem, for our own people, in a way that strengthens the country's self-reliance in an area that touches food security and public health directly. That's the mission driving this team every day. In terms of the space we're building in, yes, we sit in a gap that almost nobody is building for. On one end you have expensive lab equipment like ICP-MS and AAS, accurate but completely out of reach for a farmer or a small municipal body. On the other end you have cheap field kits, colorimetric strips and basic meters, affordable but often unreliable and limited to one analyte at a time. Almost nobody is building for the middle ground, something accurate enough to trust, portable enough to use in the field, and affordable enough to actually deploy at scale in India. That empty middle is exactly where KiFayti sits, and honestly, that's part of why we think this problem is still unsolved. It's not a lack of demand, it's that the space between "too expensive" and "too unreliable" has been ignored. Venkat Ravi Teja Villa checked
Aug 16, 2026 @ 10:30 PM Sushil Kumar Verma sushilverma208016@gmail.com https://www.linkedin.com/in/sushilverma208016/ 8574907562 1 Technology + Operations + Leadership Greenly Lucknow Greenly is a Gardening-as-a-Service and Green Spaces Management platform providing plants, garden setup, landscaping and recurring maintenance services to homes, apartments, offices, housing societies, commercial properties and real-estate developers. Greenly also builds a trained and managed gardener network, creating organized employment while delivering reliable and technology-enabled gardening services. Gardening and landscaping services in India are highly fragmented and largely informal. Individual customers struggle to find reliable gardeners, select suitable plants and manage recurring needs such as watering, pruning, fertilization, pest control and plant replacement. At the B2B level, builders, housing societies and commercial properties need reliable partners for landscaping, plant supply, gardener management and long-term maintenance. At the same time, many gardeners lack stable employment, training and consistent access to customers. Greenly provides an end-to-end platform for creating and maintaining green spaces. For B2C customers, Greenly offers plant discovery and delivery, garden design and installation, gardening subscriptions, trained gardeners, pest control, plant care and replacement services. For B2B customers, Greenly provides landscaping, plant supply, gardener/workforce management and recurring garden maintenance for real-estate projects, housing societies, offices and commercial properties. Greenly will use technology for service booking, gardener scheduling, customer garden profiles, maintenance tracking and quality monitoring, creating a reliable and scalable alternative to fragmented traditional gardening services. Greenly combines plant commerce, landscaping, recurring garden maintenance and a managed gardener workforce in one integrated platform. Instead of being only a nursery, gardener marketplace or landscaping contractor, Greenly manages the complete lifecycle of a green space—from plant selection and design to installation, maintenance, plant health, replacement and redesign. A trained and technology-managed gardener network, customer garden profiles, service history, scheduling and quality monitoring can create operational efficiency and customer retention. On the B2B side, long-term relationships with builders, housing societies and commercial properties through landscaping and Annual Maintenance Contracts (AMCs) can create recurring revenue and strong customer relationships. Idea Signups B2B and B2C To build Greenly into India's leading technology-enabled green-space management platform, serving homes, businesses, housing societies and real-estate developers through plants, landscaping, maintenance and trained gardening professionals. We aim to organize the fragmented gardening industry, create sustainable employment for gardeners and make green-space management reliable and effortless across India. Yes Bengaluru can serve as an ideal launch and validation market for Greenly because of its large technology, real-estate, corporate and industrial ecosystem. We plan to leverage the Bommasandra industrial hub and wider Bengaluru market to pilot Greenly's Gardening-as-a-Service model with residential communities, corporate offices, industrial campuses, builders and housing societies. The dense concentration of businesses and properties can help us efficiently validate recurring garden-maintenance, landscaping and managed-gardener services before expanding to other Indian cities. IITACB can significantly accelerate this journey through its incubation infrastructure, experienced IIT alumni and industry mentors, corporate and academic connections, investor network and Bengaluru ecosystem. We would particularly benefit from mentorship in business model validation, B2B sales, operations and workforce management, technology/product development, AI-based plant and garden management, and fundraising. IITACB's industry and academic network can also help us identify pilot customers and partners, while its investor ecosystem can support Greenly in scaling from an initial Lucknow/Bengaluru pilot into a pan-India green-space management platform. Our goal is to use Bengaluru as a high-value validation and innovation market while leveraging IITACB's ecosystem to build Greenly into a scalable, technology-enabled company that creates organized employment for gardening professionals and provides reliable green-space management to both consumers and businesses across India. Yes We plan to use IITACB's workspace as the operational base for Greenly's product development, customer research, B2B sales and pilot operations. We would leverage meeting facilities for customer and partner discussions and use IITACB's mentorship, industry/academic network, technical expertise and investor ecosystem to validate our business model, build our technology platform and establish B2B partnerships. Our goal is to use the incubator as a launchpad for scaling Greenly from a Bengaluru pilot into a pan-India green-space management platform. Yes Supporting feature 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/83NdPEjJlkPH-Greenly_Pitch_Deck.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/83NdPEjJlkPH-Greenly_Pitch_Deck.pdf NA checked
Aug 16, 2026 @ 10:25 PM Sushil Kumar Verma sushilverma208016@gmail.com https://www.linkedin.com/in/sushilverma208016/ +91-8574907562 1 Working on core problem Greenly Lucknow Greenly is a Gardening-as-a-Service and Green Spaces Management platform providing plants, garden setup, landscaping and recurring maintenance services to homes, apartments, offices, housing societies, commercial properties and real-estate developers. Greenly also builds a trained and managed gardener network, creating organized employment while delivering reliable and technology-enabled gardening services. Gardening and landscaping services in India are highly fragmented and largely informal. Individual customers struggle to find reliable gardeners, select suitable plants and manage recurring needs such as watering, pruning, fertilization, pest control and plant replacement. At the B2B level, builders, housing societies and commercial properties need reliable partners for landscaping, plant supply, gardener management and long-term maintenance. At the same time, many gardeners lack stable employment, training and consistent access to customers. Greenly provides an end-to-end platform for creating and maintaining green spaces. For B2C customers, Greenly offers plant discovery and delivery, garden design and installation, gardening subscriptions, trained gardeners, pest control, plant care and replacement services. For B2B customers, Greenly provides landscaping, plant supply, gardener/workforce management and recurring garden maintenance for real-estate projects, housing societies, offices and commercial properties. Greenly will use technology for service booking, gardener scheduling, customer garden profiles, maintenance tracking and quality monitoring, creating a reliable and scalable alternative to fragmented traditional gardening services. Greenly combines plant commerce, landscaping, recurring garden maintenance and a managed gardener workforce in one integrated platform. Instead of being only a nursery, gardener marketplace or landscaping contractor, Greenly manages the complete lifecycle of a green space—from plant selection and design to installation, maintenance, plant health, replacement and redesign. A trained and technology-managed gardener network, customer garden profiles, service history, scheduling and quality monitoring can create operational efficiency and customer retention. On the B2B side, long-term relationships with builders, housing societies and commercial properties through landscaping and Annual Maintenance Contracts (AMCs) can create recurring revenue and strong customer relationships. Idea Signups Our long-term vision is to build Greenly into India's leading technology-enabled green-space management platform, making gardening and landscaping accessible, reliable and effortless for both individuals and businesses. We aim to serve homes, apartments, offices, housing societies and real-estate developers through an integrated ecosystem of plants, landscaping, garden maintenance and trained gardening professionals. Over time, Greenly will build a large organized network of gardeners, use technology and AI for garden management and plant health, and create sustainable employment opportunities. Our goal is to transform the fragmented gardening and landscaping industry into a professional, scalable and trusted service ecosystem across India. Yes Bengaluru can serve as an ideal launch and validation market for Greenly because of its large technology, real-estate, corporate and industrial ecosystem. We plan to leverage the Bommasandra industrial hub and wider Bengaluru market to pilot Greenly's Gardening-as-a-Service model with residential communities, corporate offices, industrial campuses, builders and housing societies. The dense concentration of businesses and properties can help us efficiently validate recurring garden-maintenance, landscaping and managed-gardener services before expanding to other Indian cities. IITACB can significantly accelerate this journey through its incubation infrastructure, experienced IIT alumni and industry mentors, corporate and academic connections, investor network and Bengaluru ecosystem. We would particularly benefit from mentorship in business model validation, B2B sales, operations and workforce management, technology/product development, AI-based plant and garden management, and fundraising. IITACB's industry and academic network can also help us identify pilot customers and partners, while its investor ecosystem can support Greenly in scaling from an initial Lucknow/Bengaluru pilot into a pan-India green-space management platform. Our goal is to use Bengaluru as a high-value validation and innovation market while leveraging IITACB's ecosystem to build Greenly into a scalable, technology-enabled company that creates organized employment for gardening professionals and provides reliable green-space management to both consumers and businesses across India. Yes We would like to use IITACB's infrastructure as Greenly's base for building and validating our initial operations. The workspace will be used by our founding team for product development, business operations, customer research, B2B sales and coordination with our gardening workforce. We would also like to leverage meeting and conference facilities for discussions with potential customers, real-estate developers, housing societies and partners. Beyond physical infrastructure, we would particularly value IITACB's incubation ecosystem, including mentorship, industry and academic connections, networking opportunities, investor interactions and access to relevant technical expertise. We plan to use these resources to develop Greenly's technology platform for customer service booking, gardener scheduling, garden management and operational tracking, while simultaneously running pilot projects in Bengaluru. Our objective is to use the incubator as a launchpad to validate the business model, establish B2B partnerships, develop the technology and operational processes, and prepare Greenly for expansion into multiple Indian cities. Yes Supporting feature 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/G61jFGwdlUtL-Greenly_Pitch_Deck.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/G61jFGwdlUtL-Greenly_Pitch_Deck.pdf NA checked
Aug 16, 2026 @ 8:31 PM vishwajeet kumar vishwajeet0209@gmail.com https://www.linkedin.com/in/vishwajeet-kumar-473109174/ +917378120558 Founder & CEO, CarbClex Private Limited I am the Founder & CEO of CarbClex, building a farmer-first climate intelligence and carbon infrastructure platform focused on making agricultural productivity, sustainability, and carbon markets accessible at farm level. I hold a B.Tech in Electrical Engineering from IIT (BHU) Varanasi and have approximately 3.5 years of experience in high-scale technology and payments systems. I previously worked with Dream11, where I was part of the payments engineering team handling systems operating at significant transaction volumes during major sporting events. I also have experience in UPI/payments technology and building scalable backend systems. At CarbClex, I lead the overall company strategy, product architecture, technology, data infrastructure, business development, carbon-market strategy, and fundraising. We are building an integrated platform connecting farmers, agricultural data, MRV, carbon accounting, AI-driven farm intelligence, and corporate sustainability requirements. Our current focus is to build a granular agricultural data layer covering farmers, farms, plots, crop cycles, soil, inputs, practices, yield, emissions, and MRV evidence. This foundation will enable us to develop AI-driven recommendations, carbon intelligence, productivity insights, and eventually a scalable climate-tech infrastructure for agriculture. My technical background allows me to work closely with the engineering team on architecture and product development, while my current role is increasingly focused on building the organization, validating the business model, developing partnerships, and scaling CarbClex across India and international markets. Role: Founder & CEO Organization: CarbClex Private Limited Education: B.Tech, Electrical Engineering, IIT (BHU) Varanasi I am currently a solo founder and do not have a co-founder at this stage. I founded CarbClex independently and have been working full-time on the company, product development, technology, business strategy, customer discovery, and market validation. I have built and managed the initial team and external partnerships required to develop and validate the product. As CarbClex scales, I remain open to bringing in complementary leadership and co-founder-level talent where it can add significant strategic or technical value. 1 Our biggest strength is high ownership and speed of execution. We combine strong technical capabilities with a deep understanding of the agricultural, carbon, and climate-tech ecosystem. As the founder, I bring a strong engineering and product background, including experience building and operating high-scale technology systems. At CarbClex, this allows us to move quickly from identifying a problem to designing, building, testing, and iterating the solution. We are also highly data-driven and focused on building long-term infrastructure rather than a single-point solution. Our approach combines farmer-level data, AI, MRV, carbon accounting, agricultural intelligence, and scalable technology, while continuously validating assumptions through field-level execution. Our ability to operate with a lean team, learn rapidly from farmers and industry stakeholders, and translate those learnings into technology and scalable processes is currently our biggest advantage. Carbclex Private limited https://carbclex.tech/ Bengaluru CarbClex is building a farmer-first climate intelligence and carbon infrastructure platform that helps agriculture become more productive, measurable, and climate-aligned. We build a granular digital layer around farmers, farms, plots, crop cycles, soil, agricultural practices, inputs, yield, emissions, and MRV data. This enables us to provide farmers with actionable intelligence while helping enterprises measure agricultural emissions, monitor sustainability performance, develop high-quality carbon projects, and connect verified climate outcomes with carbon markets. Our long-term vision is to build an AI-powered intelligence infrastructure for every acre, combining agricultural data, MRV, carbon accounting, predictive analytics, and AI-driven recommendations. CarbClex is initially focused on agricultural value chains in India, with the platform designed to scale into international markets including the EU, Australia, and other climate-sensitive agricultural markets. Agriculture generates significant environmental impact, but the underlying data needed to measure, manage, and improve that impact is highly fragmented and difficult to access at the farm and plot level. Farmers often lack access to reliable, data-driven guidance on how their farming practices affect productivity, input efficiency, soil health, emissions, and long-term profitability. At the same time, companies and carbon-market participants struggle to obtain granular, reliable, and auditable agricultural data required for Scope 3 emissions measurement, sustainability reporting, MRV, and high-quality carbon projects. Today, much of this information is collected manually, through disconnected systems, periodic surveys, or generic assumptions. This creates three major problems: Farmers lack actionable intelligence to make better production and sustainability decisions. Enterprises lack granular supply-chain data to accurately measure and manage agricultural emissions and sustainability performance. Carbon and climate projects face data and MRV challenges, making it difficult to establish credible baselines, monitor interventions, quantify outcomes, and build scalable projects. CarbClex is solving this by creating a farm-level data and intelligence infrastructure that connects agricultural activity, productivity, emissions, sustainability, and MRV into a single system. This data foundation can then power AI-driven recommendations for farmers and reliable intelligence for enterprises and climate markets. Our goal is to move agriculture from assumption-based measurement to continuously improving, data-driven decision-making at the level of every acre. CarbClex is building a farmer-first agricultural intelligence and climate infrastructure platform that converts fragmented farm-level data into actionable intelligence for farmers, enterprises, and climate markets. Our solution starts by creating a granular digital representation of every farm and plot. We capture and organize data across the complete crop cycle, including farmer and land information, GPS boundaries, soil characteristics, crops, inputs, irrigation, farming practices, yield, weather, interventions, and supporting evidence. On top of this data foundation, CarbClex is building multiple intelligence layers: Farm Intelligence: AI-driven recommendations to improve productivity, input efficiency, soil health, and farm economics. Carbon Intelligence: Farm- and activity-level estimation of greenhouse-gas emissions, carbon intensity, and potential climate impact. MRV Infrastructure: Structured data collection, evidence management, monitoring, and verification workflows required for credible sustainability and carbon projects. Yield & Risk Intelligence: Models that help understand the relationship between farming practices, soil conditions, climate risks, and expected productivity. Enterprise Intelligence: Supply-chain and agricultural sustainability dashboards that help companies measure Scope 3 emissions, monitor interventions, assess suppliers, and track climate targets. Carbon Project Infrastructure: The underlying data and calculation layer required to develop, monitor, and eventually monetize high-quality agricultural carbon projects. The platform is designed as a continuous data loop: farmer activity generates data → data is analyzed by our calculation and AI engines → actionable recommendations are generated → farmer actions and outcomes are captured again → the system becomes increasingly accurate and useful. Our long-term vision is to create “Intelligence for Every Acre”—a scalable infrastructure layer that connects agricultural productivity, climate impact, MRV, and carbon markets while creating direct economic value for farmers. We are initially building and validating this infrastructure in India and intend to expand it to international agricultural and climate markets. CarbClex's defensibility comes from building a granular, continuously improving farm-level data and intelligence layer, rather than operating as a standalone carbon-credit marketplace or a generic agricultural advisory platform. Our key differentiators are: 1. Farm-level longitudinal data moat We are building structured datasets at the farmer, farm, plot, and crop-cycle level. Over time, this creates a proprietary longitudinal dataset covering farming practices, inputs, soil, yield, interventions, emissions, and outcomes. The increasing depth and history of this data makes the platform progressively harder to replicate. 2. Action → Outcome feedback loop We are not only collecting data; we aim to connect recommendations with actual farmer actions and subsequent outcomes. This creates a continuous learning loop where the system can understand which interventions work under specific soil, crop, climate, and farm conditions. 3. Integrated intelligence infrastructure Instead of building separate tools for carbon accounting, MRV, farm advisory, sustainability reporting, and enterprise analytics, CarbClex is building a common underlying data and calculation architecture that can support all of these use cases. 4. MRV-ready data architecture Our data model is designed from the beginning to capture the evidence, activity data, temporal information, and traceability required for credible measurement, reporting, and verification. This can reduce the friction involved in developing scalable agricultural climate projects. 5. AI built on proprietary domain data AI is not the product by itself. Our advantage is the combination of AI with proprietary agricultural data, calculation engines, agronomic context, and real-world outcome data. As the dataset grows, the intelligence layer can become increasingly specific to individual farms, crops, regions, and agricultural conditions. 6. Farmer + Enterprise network effects Farmers generate granular ground-level data and receive actionable value from the platform. Enterprises can use aggregated, permissioned intelligence for supply-chain sustainability, Scope 3 measurement, climate programs, and procurement decisions. This creates a two-sided ecosystem where increasing participation strengthens the value of the platform. Ultimately, our defensibility is expected to come from the combination of proprietary longitudinal data, continuous farmer-action feedback, domain-specific intelligence, MRV infrastructure, and an integrated technology architecture. This creates a compounding data and intelligence advantage that becomes stronger as CarbClex scales Users Users CarbClex serves three primary customer segments: 1. Agricultural Enterprises & Supply-Chain Companies Large food, FMCG, agri-processing, retail, and agricultural companies that source directly or indirectly from farmers and need granular visibility into their supply chains. We help them with Scope 3 emissions measurement, sustainability monitoring, supplier intelligence, climate-risk assessment, and tracking of agricultural interventions. 2. Carbon Market & Climate-Finance Participants Carbon project developers, carbon-market participants, sustainability organizations, and climate-focused enterprises that require reliable farm-level data, calculation infrastructure, monitoring, reporting, and verification (MRV) to develop and manage agricultural climate projects. 3. Farmers & Farmer Organizations Farmers, FPOs, cooperatives, and agricultural networks are the foundation of our platform. CarbClex provides them with farm intelligence, productivity insights, input-efficiency recommendations, climate intelligence, and opportunities to participate in verified sustainability and carbon programs. Our initial focus is on high-value agricultural value chains and organized buyers where farm-level data, sustainability requirements, and climate commitments create a strong economic need for our platform. Over time, we aim to build a two-sided ecosystem where farmers generate and benefit from high-quality agricultural data, while enterprises pay for intelligence, measurement, compliance, sustainability, and climate solutions built on that data. NA NA NA CarbClex follows a B2B2F (Business-to-Business-to-Farmer) model, where enterprises and climate-market participants are the primary paying customers while farmers are the core data and impact network. Our revenue streams are: Enterprise SaaS / Intelligence subscriptions – recurring subscriptions for agricultural supply-chain intelligence, Scope 3 measurement, sustainability dashboards, climate-risk analytics and supplier monitoring. Carbon & MRV services – fees for farm-level data collection, carbon accounting, MRV infrastructure, monitoring and project support. Carbon project development fees and revenue share – project development and participation in revenues generated from eligible agricultural carbon projects. Data & API products – APIs and data products for carbon calculations, agricultural emissions, sustainability analytics and other enterprise applications. Farmer-side monetization – over time, selected premium intelligence, services and outcomes generated through farmer actions can create additional revenue while keeping the core farmer experience accessible. Our objective is to transition from project-based revenue toward recurring, high-margin enterprise intelligence and infrastructure revenue, with carbon and MRV providing an additional monetization layer. CarbClex competes across several adjacent categories rather than against a single company. Agricultural intelligence & farmer platforms: Companies such as nurture.farm provide farm advisory, digital agriculture services, sustainability programs and carbon-related programs. nurture.farm demonstrates the convergence of farm services, sustainability and carbon programs at scale. Agricultural carbon & MRV: Global players include Boomitra, Indigo Ag, Agreena, Agoro Carbon Alliance, Nori and AgriCapture. The agricultural carbon market already includes technology-led companies focused on carbon farming, MRV and farmer participation. Digital agriculture / precision agriculture: Large agricultural technology companies provide individual components such as farm analytics, precision agriculture, remote sensing, inputs, crop intelligence and farm management. Our differentiation: CarbClex is not positioning itself only as a farmer advisory app or carbon-credit developer. We are building a common farm-level data and intelligence infrastructure connecting: Farmer → Farm → Plot → Crop Cycle → Practices → Outcomes → Emissions → MRV → Enterprise Intelligence → Climate Markets This allows the same underlying data layer to serve farmer intelligence, enterprise sustainability, carbon accounting, MRV and future AI applications Our customer acquisition strategy is primarily enterprise-led and partnership-driven, supported by field-level farmer acquisition. Enterprise acquisition We target agricultural supply-chain companies, food and FMCG companies, agri-processors, sustainability teams, carbon-market participants and climate-focused organizations. We acquire these customers through: Direct founder-led enterprise sales Strategic partnerships with agri-processors, FPOs, sugar mills and supply-chain organizations Sustainability and climate-industry networks Pilot projects that demonstrate measurable business value Industry conferences, roundtables and climate/agriculture ecosystems Partnerships with MRV, satellite, agricultural and carbon-market organizations Farmer acquisition Farmers are acquired primarily through field operations, FPOs, local agricultural networks, enterprise supply chains and partner organizations. Our strategy is to use enterprise relationships to create farmer distribution rather than relying entirely on expensive direct-to-farmer digital acquisition. As the farmer network grows, product-led engagement, recommendations, incentives and outcomes from the platform are expected to improve retention and organic adoption. Our go-to-market strategy is enterprise-led, field-enabled and data-compounding. Phase 1 — Build the farm network We start by establishing a high-quality farmer and farm/plot data network in selected agricultural clusters. Field teams and partners onboard farmers and capture structured data across the crop cycle. Phase 2 — Enterprise pilots We use the farm network to work with agricultural enterprises, processors, food/FMCG companies and climate organizations on specific problems such as: Scope 3 agricultural emissions Supplier sustainability Farm-level climate intelligence MRV Sustainable agriculture programs Carbon project development Phase 3 — Convert pilots into recurring contracts Once measurable value is demonstrated, we convert customers from individual projects into recurring enterprise intelligence and SaaS relationships. Phase 4 — Expand geographically and vertically We will expand across additional crops and agricultural value chains in India and subsequently into EU, Australia, Middle East and other international markets where agricultural sustainability, emissions reporting and climate-risk requirements create strong demand. The fundamental GTM flywheel is: Acquire farmers → build proprietary farm-level data → generate intelligence → demonstrate enterprise ROI → acquire enterprise customers → fund more farmer adoption → collect more longitudinal data → improve intelligence. Our long-term vision is to build “Intelligence for Every Acre” — a global agricultural intelligence and climate infrastructure layer connecting every farm to better decisions, measurable outcomes and climate markets. We envision CarbClex becoming the infrastructure through which agricultural activity can be continuously understood across productivity, soil health, resource efficiency, climate risk, emissions, sustainability and economic outcomes. At the farmer level, this means providing an intelligent system that understands the individual farm and continuously recommends actions that can improve productivity, resilience and profitability. At the enterprise level, it means providing a trusted source of farm-level intelligence for supply-chain sustainability, Scope 3 emissions, climate-risk management, procurement and transition planning. At the climate-market level, it means creating reliable data and MRV infrastructure that can make agricultural climate projects more measurable, scalable and economically viable. Our ambition is not to build another agriculture app or another carbon-credit marketplace. We want to build the underlying intelligence infrastructure for climate-aligned agriculture, starting in India and eventually serving agricultural ecosystems globally. In the long term, CarbClex aims to create a compounding network of farmers + data + AI + enterprises + climate finance, where better data leads to better decisions, better farm outcomes and measurable climate impact. Incorporated Bootstrapped Yes We are applying to IITACB because CarbClex is at a stage where technology validation, enterprise access, domain mentorship and fundraising support can significantly accelerate our growth. IITACB provides a unique combination of the IIT alumni ecosystem, industry connections, experienced mentors, investor access and a physical innovation environment in Bengaluru. The incubator is specifically designed to connect startups with IIT alumni, corporates, research institutions and investors. For CarbClex, the most valuable opportunity is to leverage this ecosystem to strengthen our AI and agricultural intelligence architecture, enterprise business model, carbon/MRV strategy, IP and international go-to-market strategy. We also see Bengaluru as an important strategic market for building relationships with technology companies, climate-tech investors, agricultural enterprises and sustainability leaders. During the programme, our primary objectives are: Strengthen product-market fit by converting our early field traction into repeatable enterprise use cases. Build and validate our AI intelligence layer on top of our growing farm-level dataset. Strengthen our MRV, carbon accounting and agricultural intelligence architecture. Develop repeatable enterprise sales and partnerships with agricultural, food, FMCG and sustainability organizations. Establish strategic partnerships with IIT researchers, technology providers, MRV organizations and industry partners. Prepare CarbClex for our next institutional fundraising round through stronger metrics, business model validation and investor readiness. Build the foundation for expansion from India into EU, Australia, Middle East and other international agricultural markets. Our goal is to leave the programme with a significantly stronger product, validated enterprise use cases, strategic partnerships and a clear path toward scalable growth and institutional fundraising. Yes. We are open to virtual participation when required, while preferring hybrid/in-person engagement for important mentor meetings, investor interactions, workshops, enterprise meetings and ecosystem-building activities. Bengaluru is strategically important for CarbClex because it provides access to a dense ecosystem of technology companies, agritech and food companies, climate-tech startups, investors, enterprise decision-makers and highly skilled engineering talent. We would use the Bommasandra location as a Bengaluru operating and collaboration base while continuing our agricultural field operations in Uttar Pradesh, Bihar and other target regions. Specifically, we want to leverage the Bengaluru ecosystem to: Develop partnerships with agricultural and food supply-chain companies. Connect with sustainability and ESG teams of large enterprises. Access climate-tech and deep-tech investors. Recruit and collaborate with AI, data science and engineering talent. Develop research and technology collaborations around AI, remote sensing, agricultural modelling, carbon accounting and MRV. Build partnerships with satellite/MRV and agricultural technology companies. Establish Bengaluru as our technology, enterprise-sales and fundraising hub. IITACB can help us by providing high-quality mentorship, IIT alumni access, industry connections, investor introductions, research collaborations, workshops and physical infrastructure. IITACB's stated mission includes connecting IIT alumni, industry, government and startups, while its incubator specifically offers mentorship, networking, incubator/lab space and investor access. This combination is particularly valuable for CarbClex because our next stage requires not only technology development but also enterprise validation, institutional partnerships and global market preparation. Yes We would use the IITACB infrastructure as a Bengaluru technology, strategy and business-development base for CarbClex. Our primary use cases would include: Product and engineering collaboration. AI/ML and agricultural intelligence development. Data architecture and MRV technology development. Enterprise and investor meetings. Mentor interactions and technical reviews. Workshops and knowledge-sharing sessions. Partnership discussions with IIT alumni, corporates and technology organizations. Fundraising preparation and investor-connect activities. Collaboration with researchers and domain experts. We would continue our field operations and farmer onboarding in agricultural regions while using Bengaluru as the central hub for technology development, enterprise partnerships, fundraising and strategic expansion. Yes Core engine CarbClex follows a modular, data-centric architecture designed around a canonical farm-level data model. At a high level: Data Collection Layer → Data & Identity Layer → Calculation Engines → AI/Intelligence Layer → MRV & Evidence Layer → Application/API Layer → Enterprise Analytics The core data model links: Farmer → Farm → Plot → Crop Cycle → Crop Stage → Soil → Inputs → Practices → Yield → Emissions → Interventions → Outcomes → Evidence Our technology stack currently includes Java/Spring Boot, MySQL, Redis, Kafka, AWS services, S3, Lambda, SQS, InfluxDB, React and observability infrastructure. The calculation layer includes specialized engines for baseline scenarios, project scenarios, adjustments, emissions, carbon revenue, timelines and agricultural/yield modelling. The intelligence layer can consume structured farm data and calculation outputs to generate predictions, recommendations, risk signals and enterprise insights. The architecture is designed to allow individual engines to evolve independently while maintaining a common underlying data and identity model. Our primary data advantage is the development of a longitudinal, farm-level agricultural dataset. Instead of relying only on satellite imagery, public datasets or generic agricultural assumptions, we are building structured data linked to: Farmer Farm and plot boundaries Crop cycles Soil characteristics Agricultural inputs Irrigation Farming practices Crop stages Yield Interventions Emissions MRV evidence Outcomes over time The most important advantage is not simply the volume of data but the relationship between interventions and outcomes over multiple crop cycles. As the platform scales, this creates an increasingly valuable dataset that can be used to train, calibrate and validate farm-specific intelligence and models. Our defensibility comes from the combination of: 1. Proprietary longitudinal data Farm-level data collected repeatedly across crop cycles becomes increasingly difficult to reproduce. 2. Action → Outcome feedback loop We intend to connect recommendations with actual farmer actions and subsequent outcomes, allowing our intelligence models to continuously improve. 3. Domain-specific calculation engines Our platform incorporates agricultural, emissions, carbon and MRV-specific logic rather than relying solely on generic AI models. 4. Integrated infrastructure We connect farm data, agricultural intelligence, carbon accounting, MRV and enterprise sustainability within a common architecture. 5. Distribution + data network Our field operations and partnerships create a mechanism for continuously expanding the underlying dataset. 6. AI on proprietary domain data The defensible layer is the combination of AI with proprietary farm data, domain models, calculations and real-world outcomes—not the underlying foundation model itself. Over time, these elements create a compounding data + intelligence + distribution moat. We evaluate the platform at multiple levels rather than using a single technology metric. Software performance We track: API latency Throughput Error rates Availability Database performance Queue processing latency Calculation execution time Infrastructure utilization Data pipeline failures Data quality We measure: Completeness Accuracy Consistency Duplicate rates GPS/plot-data validity Missing-value rates Evidence completeness Data lineage and traceability Model performance As our models mature, we will evaluate: MAE/RMSE for continuous predictions Precision/recall/F1 where classification is appropriate Calibration and uncertainty Prediction drift Regional/crop-level performance Back-testing against historical outcomes Out-of-sample validation Recommendation adoption and outcome improvement Reliability For critical calculations, we use deterministic calculation engines, validation rules, audit trails and versioned methodologies rather than allowing an LLM to directly determine regulated or financial outputs. Our objective is to continuously benchmark model and platform performance against field observations, independent datasets, established methodologies and relevant industry standards. We follow a privacy-by-design and security-by-design approach. Our architecture separates identity, operational, analytical and access-control concerns. Access is controlled through authentication and authorization mechanisms, with role-based access for different users and organizations. Key principles include: Data minimization Role-based access control Encryption in transit and at rest Secure cloud infrastructure Audit logging API authentication and authorization Environment separation Backup and disaster-recovery mechanisms Controlled access to farmer and enterprise data Data lineage and provenance Consent and purpose-based data collection where applicable For enterprise customers and international expansion, we will progressively align the platform with applicable requirements including India's Digital Personal Data Protection framework, GDPR and other relevant data-protection requirements. We also intend to establish formal security and compliance processes as enterprise adoption scales, including periodic security assessments and appropriate certifications where commercially required. Yes. Several policy and regulatory developments support the broader ecosystem in which CarbClex operates. India's emerging Carbon Credit Trading Scheme and agricultural carbon-market framework can increase demand for reliable emissions data, monitoring and MRV infrastructure. Government programs promoting sustainable agriculture, soil health, water efficiency, climate-resilient agriculture, digital agriculture and carbon-market participation also create opportunities for technology infrastructure. Internationally, increasing requirements around Scope 3 emissions, supply-chain transparency, sustainability reporting and climate disclosures are creating demand for more granular agricultural data. These policy developments do not form the sole basis of our business model; they strengthen the underlying market demand for measurable agricultural sustainability. Yes. The primary regulatory risks include: Changes in carbon-market regulations and methodologies Changes in carbon-credit eligibility or accounting standards Requirements for third-party validation and verification Data-protection and cross-border data-transfer requirements AI governance and emerging AI regulations Environmental and sustainability-claim regulations Changes in international carbon-market rules Potential restrictions around agricultural or satellite-derived data We manage these risks by designing the platform to be methodology-agnostic, auditable and modular, maintaining clear data provenance and avoiding dependence on a single carbon standard or regulatory framework. We also distinguish between technology-generated estimates and independently verified carbon outcomes, particularly where regulatory or market requirements require third-party verification. The most likely bottlenecks at 10x scale would initially be data ingestion, field-data quality, database workloads, asynchronous processing, model inference and operational processes, rather than the core product concept. At 10x scale we expect: Significantly higher API and database load Larger volumes of geospatial and crop-cycle data Higher event-processing requirements Increased storage and analytical workloads Greater model-inference demand More complex tenant isolation and enterprise workloads Field-level data-quality challenges Higher operational coordination requirements Our architecture already uses distributed components such as Kafka, queues, Redis, cloud storage and modular services, allowing individual components to scale independently. Our scaling strategy is to progressively introduce stronger data partitioning, caching, asynchronous processing, read replicas, workload isolation, model-serving infrastructure and automated data-quality pipelines as volume increases. We currently have an in-house technology team, although we are still building the deeper AI/ML specialization required for the next stage of the platform. The existing engineering capability includes: Backend engineering Distributed systems API development Database architecture Cloud infrastructure Data pipelines Event-driven systems Frontend engineering Product engineering The founder brings an engineering background from IIT (BHU) and previous experience working on high-scale payment systems. Our next hiring/technical-development phase is focused on strengthening dedicated expertise in: Machine learning Geospatial intelligence Agricultural modelling Computer vision/remote sensing LLM applications Statistical modelling Climate/carbon science We also plan to leverage external domain experts, research collaborations and IIT ecosystem expertise where appropriate. Our technology uses a combination of proprietary data, licensed/authorized third-party data, public/open datasets and open-source software components. Proprietary / owned Our proprietary assets include: CarbClex's farm/farmer/plot/crop-cycle data model Internally collected farmer and farm data Internal calculation logic Carbon-intensity and emissions calculation workflows Yield simulation and intelligence logic MRV data structures and evidence workflows Internal APIs and application architecture Internal product and operational workflows Open source / standard components We use established open-source frameworks and libraries within their respective licenses, including components across our Java, Spring, database, frontend, cloud and data-processing ecosystem. Third-party / external datasets Where external agricultural, weather, satellite, emission-factor or other datasets are required, we use sources according to their respective licensing and usage terms. We do not claim ownership of third-party datasets. We maintain a distinction between source data, licensed data, derived data and CarbClex-generated proprietary data. We currently do not have a granted patent/IP registration that we are representing as a core competitive asset. As novel technology components mature, we will evaluate appropriate patent, copyright, trade-secret and contractual protections. We are building a continuous improvement loop: Data → Model → Recommendation → Farmer Action → Outcome → Validation → Model Improvement Our technology improvement process will include: Continuous data-quality monitoring Automated testing Model back-testing Field validation A/B testing where appropriate Model drift monitoring Crop/region-specific calibration Human/domain-expert review Versioned calculation methodologies Monitoring of recommendation outcomes Continuous benchmarking against independent datasets Regular infrastructure performance optimization The most important long-term improvement mechanism will be the increasing volume of longitudinal farm-level outcome data, which allows our models to move from generic recommendations toward increasingly farm-, crop- and region-specific intelligence. Both. India is our initial market because it provides a large agricultural base, significant climate and productivity challenges, strong potential for farm-level data generation, and an emerging carbon/sustainability ecosystem. Our architecture is being designed to support international expansion without rebuilding the core platform. This includes configurable: Emission factors Carbon methodologies Regulatory requirements Crops and agricultural practices Geographic boundaries Units and currencies Data-privacy requirements Reporting standards Enterprise workflows After establishing the platform in India, our planned international expansion includes the EU, Australia, Middle East and other agricultural markets where climate reporting, agricultural sustainability, supply-chain transparency and carbon-market infrastructure are growing requirements. Our long-term objective is therefore to build globally applicable agricultural intelligence infrastructure, starting with India as our primary validation and scale market. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/CzuEAOVMiuB3-CarbClex_Pitch_Deck-.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/CzuEAOVMiuB3-CarbClex_Pitch_Deck-.pdf Yes. CarbClex is a mission-driven climate-tech company focused on making agriculture more productive, resilient, measurable and climate-aligned. Our mission is to build “Intelligence for Every Acre”—giving farmers access to data-driven intelligence while creating the infrastructure required for enterprises and climate markets to measure and act on agricultural sustainability. We believe the transition to climate-aligned agriculture will only scale if it creates economic value for farmers, rather than treating farmers only as participants in carbon projects. Our impact model therefore focuses on three interconnected outcomes: 1. Farmer impact We aim to help farmers improve productivity, input efficiency, soil health, climate resilience and farm economics through actionable, farm-specific intelligence. 2. Climate impact By measuring agricultural practices and outcomes at farm and plot level, we aim to enable more credible emissions reduction, carbon sequestration, sustainable agricultural practices and climate-resilience interventions. 3. System-level impact We are building the data and MRV infrastructure that can help enterprises understand agricultural supply-chain emissions, implement sustainability programs, and channel climate finance toward measurable interventions. Our approach is based on the principle that better data → better decisions → better farm outcomes → measurable climate impact. We intend to measure impact through metrics such as farmers reached, acres covered, productivity and input-efficiency improvements, soil and resource outcomes, emissions/carbon impact, farmer income impact, and verified climate outcomes. Our long-term ambition is to create a scalable infrastructure where millions of farmers can participate in the climate transition while benefiting economically from it, and where enterprises can obtain reliable, measurable and actionable intelligence about the agricultural systems on which their supply chains depend. NA NA checked
Aug 16, 2026 @ 12:55 PM Pallavi arora arorapallavi1982@gmail.com https://www.linkedin.com/in/pallavi-arora-70a1086/ +918527001408 Founder PanIIT summit , 6 months 1 Collaboration CosmicDrift NA Banglore Cosmic Drift is a holistic mental wellness and personal transformation ecosystem designed to support people through different dimensions of life — mind, emotions, relationships, career and purpose Mental issues like stress anxiety depression Cosmic Drift is a holistic mental wellness and personal transformation ecosystem designed to support people through different dimensions of life — mind, emotions, relationships, career and purpose. We aim to bring together a trusted network of mental-health professionals, psychiatrists, psychologists, therapists, healers, relationship coaches, career counsellors, life coaches, yoga and meditation practitioners, and wellness experts under one ecosystem. Through the right combination of professional support, coaching and holistic practices such as meditation, breathwork, yoga, mindfulness and manifestation, Cosmic Drift helps individuals navigate stress, emotional challenges, relationship transitions, career uncertainty and personal growth — enabling them to build greater clarity, resilience, confidence and purpose. Our philosophy is simple: Transformation begins within. AI driven solution and tangible ways to measure stress depression insomnia etc MVP Signups Students, corporate employees and people from 18-65 years age group Urban Indian adults who could potentially spend on mental wellness, mindfulness, life coaching, stress management and personal development . Rs 20k - 25k Cr Digitally active, English-speaking urban adults in India, especially professionals aged 22–45, who are willing to pay for structured wellness/coaching Rs 4k-5k Cr Realistically capturable market over the first 5 years through Bengaluru + major Indian metros + digital channels Rs 50-100 Cr B2C + B2B2C hybrid model. For B2B : Companies, colleges, IITs, startups and institutions pay Cosmic Drift for: * Employee wellness programs * Stress-management workshops * Yoga + breathwork + meditation * Goal clarity/productivity programs * Women’s wellness programs * Campus mental-wellness programs and B2C - we have * ₹49–₹99 introductory workshops * ₹1,000–₹3,000 individual sessions/workshops * ₹5,000–₹15,000 structured transformation programs * ₹20,000+ premium 90-day transformation/coaching programs * Eventually: monthly membership/subscription. A marketplace/platform model where vetted coaches, yoga practitioners, meditation teachers and wellness experts deliver programs through Cosmic Drift. B2C programs + B2B institutional programs + subscription/membership + platform commission. Direct/adjacent competitors * YourDOST — counselling and emotional wellness * Mitr — mental wellness/community * Amaha — therapy and mental healthcare. Indirect competitors * Life coaches * Yoga/meditation centres * Wellness apps * Independent therapists/coaches * Corporate wellness providers. Cosmic Drift sits between clinical mental healthcare and generic wellness—focusing on preventive mental wellness, self-awareness, clarity, mindfulness and personal transformation. Founder-led distribution will be the initial growth engine, while partnerships will become the scalable acquisition channel. Strongest acquisition channel - 1. Founder-led content 2. Instagram & YouTube 3. LinkedIn for corporate customers 4. Workshops in colleges/IITs 5. Corporate wellness partnerships 6. Communities and referrals 7. Strategic partnerships with yoga/meditation/wellness organisations Phase 1 — Validate | 0–6 months Focus on Bengaluru. Target: * Young professionals * Startup founders * College/IIT students * Women professionals Offer: * Meditation * Breathwork * Yoga * Manifestation * Goal clarity * Stress reduction * Personal transformation workshops Objective: 100–500 paying customers + strong testimonials + identify the highest-converting use case. ⸻ Phase 2 — Scale | 6–18 months Expand digitally across: Bengaluru → Delhi NCR → Mumbai → Hyderabad → Pune → Chennai Build: * Structured programs * Membership * Corporate wellness packages * College programs * Expert network Start measuring: * CAC * Conversion rate * Repeat purchase * LTV * Referral rate * Program completion * NPS ⸻ Phase 3 — Platform | 18–36 months Move from a founder-led coaching business to a technology-enabled wellness ecosystem. Cosmic Drift becomes a platform connecting people with: Yoga + Breathwork + Meditation + Coaching + Emotional Wellness + Personal Growth + Community Our long-term vision is to build a lifelong personal transformation ecosystem where people don’t seek help only when they are in crisis, but proactively invest in their emotional wellbeing, clarity, relationships, purpose and personal growth NA - not yet incorporated, Cosmic Drift is currently at the early-stage/pre-incorporation stage. I am in the process of formalising the venture and evaluating the most appropriate structure for scaling it. I am specifically looking for incubation support to validate the business model, build the initial team and establish the right institutional and technology foundations before scaling. NA Cosmic Drift has not raised external institutional funding yet. It is currently founder-funded/bootstrapped. At this stage, my priority is validation, customer acquisition and establishing product-market fit before raising external capital. Yes I am applying to IIT ACB because I want to build Cosmic Drift as a scalable, evidence-informed mental-wellness venture rather than simply as an individual coaching practice. IIT ACB can provide the ecosystem, mentorship, academic connections, technology capabilities and institutional network required to make that transition. I am particularly interested in leveraging India’s traditional knowledge systems—yoga, meditation, breathwork and mindfulness—in a structured, measurable and contemporary wellness framework. I believe the IIT ecosystem can help me bring scientific rigour, technology and scalability to this model. During the incubation programme, I want to: 1. Validate Cosmic Drift’s target customer and strongest use cases through real customer pilots. 2. Develop a scalable and repeatable product/service architecture. 3. Run pilot programmes with corporates, colleges and institutions. 4. Build an evidence-based framework combining yoga, breathwork, meditation and personal transformation. 5. Establish the business model, technology roadmap and metrics required for raising external funding and scaling. My goal is to leave the incubation programme with validated customers, measurable outcomes, institutional pilots and a clear path to scale—not simply with a concept or presentation. Yes , Yes, I am open to virtual participation where appropriate. However, I would strongly value physical participation for mentor interactions, workshops, networking, access to infrastructure and collaboration with the IIT ecosystem. I see virtual participation as complementary rather than a replacement for being physically present at the incubator. I am looking for IIT ACB to help me bridge the gap between a founder-led wellness venture and a scalable, evidence-informed technology-enabled company. The biggest value for me would be mentorship, research and academic collaboration, institutional pilots, technology expertise, business-model validation and access to the investor ecosystem. 1. Mentorship * Business model * Go-to-market * Pricing * Fundraising * Scaling 2. Academic expertise * Psychology * Behavioural science * Yoga/meditation research * Indian Knowledge Systems * Human wellbeing 3. Pilot access * IIT ecosystem * Corporates * Students * Institutions 4. Technology * Product architecture * AI/data capabilities eventually * User analytics * Digital delivery platform 5. Credibility * Institutional validation * Research collaborations * Evidence-based positioning 6. Fundraising * Investor introductions * Pitch refinement * Financial modelling * Fundraising readiness Yes I would use the incubation space primarily as a collaboration and innovation hub rather than simply as office space. I would use the infrastructure for: * Building the founding/early team * Conducting customer discovery and workshops * Developing and testing Cosmic Drift’s digital product * Conducting pilot programmes * Meeting mentors, researchers and potential partners * Working with IIT faculty/students on research and technology * Conducting small wellness/meditation/breathwork sessions where permitted * Using meeting and collaboration spaces for institutional and corporate discussions * Participating in the incubator’s events, workshops and startup ecosystem The physical presence at IIT ACB would also help Cosmic Drift build credibility and create meaningful collaborations with academia, technology and industry. Yes Not applicable The architecture will be modular so that AI, recommendation models and new wellness interventions can be introduced without rebuilding the entire platform. At present, Cosmic Drift does not have a large proprietary dataset. This is one of the key assets we intend to build during incubation. Through structured user consent, we plan to collect longitudinal, outcome-oriented data around intervention type, engagement, user goals, self-reported wellbeing, stress levels, completion and behavioural outcomes. Over time, this can create a proprietary dataset linking user profiles → interventions → engagement → outcomes, which can improve personalisation and recommendation quality. Our defensibility will not rely on a single algorithm. It will come from the combination of proprietary intervention frameworks, longitudinal outcome data, personalisation technology, expert network, institutional partnerships and brand/community. 1. Proprietary intervention framework A structured combination of: Yoga + breathwork + meditation + mindfulness + coaching + goal/purpose work 2. Outcome data Over time: Which intervention works for which user and under what circumstances? 3. Personalisation engine The system becomes increasingly capable of recommending the right intervention. 4. Expert network A curated network of qualified practitioners/coaches. 5. Institutional distribution Relationships with: IITs → colleges → corporates → organisations 6. Brand/community A trusted consumer wellness brand. We will benchmark against our own baseline initially, and subsequently against relevant industry/product benchmarks rather than claiming superiority before sufficient data is available. Technology metrics Product * DAU/MAU * Session completion * Feature adoption * Retention * Churn * Conversion AI * Recommendation acceptance rate * Recommendation relevance * Personalisation accuracy * User feedback score * Hallucination/error rate for generative AI * Human-review agreement System * API latency * Uptime * Crash rate * Error rate * Response time * Scalability/load testing Wellness outcomes * Pre/post intervention self-assessment * Engagement * Programme completion * User-reported stress/clarity/wellbeing * NPS * Repeat usage Cosmic Drift will follow a privacy-by-design approach. We will collect only data necessary for the service, obtain informed user consent, clearly communicate how data is used, provide appropriate deletion/access mechanisms and segregate personally identifiable information from analytics wherever practical. We will implement: * Encryption in transit and at rest * Role-based access control * Secure authentication * Audit logging * Data minimisation * Consent management * Regular backups * Vulnerability monitoring * Restricted access to sensitive data * Vendor/security assessments As the platform scales, we will align our practices with applicable Indian data-protection requirements and relevant international privacy frameworks for overseas users. Fir India we can check legal team on Digital Personal Data Protection Act, 2023 and associated rules Policy support around preventive mental wellbeing, workplace wellbeing, digital wellness, youth mental health and India’s traditional knowledge systems could significantly accelerate adoption. We see an opportunity to build a scientifically structured bridge between traditional Indian wellness practices and modern preventive wellbeing. The primary regulatory risk is the boundary between preventive wellness and regulated healthcare. We intend to remain clearly positioned within preventive wellness and personal development unless and until we build the clinical capabilities, professional oversight and regulatory framework required for healthcare services. Key risks: 1. Medical/clinical claims 2. AI health claims 3. Personal data 4. Practitioner qualifications 5. Advertising claims At 10X scale, our biggest challenges would initially be human scalability, content personalisation, infrastructure reliability, practitioner quality control and customer-support capacity rather than the basic technology itself. We are deliberately designing the architecture and operating model to separate high-value human intervention from repetitive processes that can be automated. Current bottleneck 10X solution- Founder dependency Standardised protocols + expert network Manual sessions Digital/self-guided programmes Personalisation Recommendation engine Customer support AI-assisted support + human escalation Practitioner quality Certification + QA framework Data Scalable cloud architecture Analytics Centralised data/analytics layer Currently, Cosmic Drift does not have a dedicated full-time deep-tech team. Technology development is being approached incrementally, with the intention of building an in-house product/engineering capability as the product validates. One of the reasons I am seeking IIT ACB incubation is precisely to access technical mentorship, researchers, student talent and potential technology collaborators while building the core team. At present, Cosmic Drift primarily uses standard commercial/cloud and open-source technology components rather than proprietary ML infrastructure. We are not currently dependent on a large proprietary dataset. We intend to build a continuous improvement loop using user feedback, engagement metrics and outcome data. Models and recommendation systems will be evaluated periodically, with human oversight for high-impact wellness interactions. We will use controlled experiments/A-B testing where appropriate and monitor model drift, reliability and safety. India is our initial market because the problem is highly relevant, the cost structure allows us to validate the model efficiently, and India provides a unique opportunity to combine modern technology with yoga, meditation, breathwork and Indian knowledge systems. However, the underlying platform is being designed for global users. After establishing product-market fit in India, we see significant opportunities in markets such as the US, UK, Middle East and other countries with large Indian and wellness-oriented populations. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/foH9RJNb7rL5-CA49CC71-C9E8-4851-A32B-8F47C960C2F6.png, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/foH9RJNb7rL5-CA49CC71-C9E8-4851-A32B-8F47C960C2F6.png Yes. Cosmic Drift is a mission-driven preventive mental-wellness and personal-transformation venture. Our mission is to make emotional wellbeing, mindfulness, stress management and personal growth more accessible and proactive, particularly for people who may not seek help until they reach a crisis point. We aim to combine evidence-informed approaches with yoga, breathwork, meditation and technology to create measurable and scalable wellbeing interventions. Over time, we want to make quality mental-wellness support more accessible across different socioeconomic groups, educational institutions and workplaces. Our impact will be measured not only through revenue, but also through reach, engagement, programme completion, user-reported improvement and sustained wellbeing outcomes. Yes. I am a woman founder building a technology-enabled startup, and women continue to be underrepresented among technology founders and startup leadership, particularly in deep-tech and technology-led ventures. I see this as an opportunity to encourage more women with significant industry experience to transition into entrepreneurship and technology-led innovation. Vivek Jha NA checked
Aug 16, 2026 @ 12:37 PM Mohit Chand mohit@maqlabs.com https://www.linkedin.com/in/mohit-chand-607b9834/ http://NA 7600952755 Mohit Chand (CEO): 11+ yrs in design, BMS & energy-conversion products for Aerospace & Automotive Industry, Prior venture (as a founding team) acquired by Ford, proven hardware credibility.M.tech IIT Gandhinagar. We were batch mates at IIT GN, we have been bouncing ideas for over a decade to build products in Energy domain. 1 Have proven hardware product capability & was closely involved in the development of my last startup as a founding team, which was later acquired by Ford. MaqLabs https://maqlabs.com Pune MaqLabs builds grid-tied solar inverters for C&I that grow with your energy needs. To add battery storage later, C&I businesses must rip out their on-grid solar inverters and start over. Start grid-tied. Drop in a module to add storage. No rip-out, ever. Battery, genset or fuel-cell blocks click into open ports on the installed inverter : live, on-line module installation (patent pending). No player in the solar inverter space sells modular designed which can be expanded as your energy needs due to high technical complexity, our prior industry experience helps us design this product. MVP Testimonials Commercial/Industrial space which are going solar $3B $1B $100M Direct sale of hardware Inverter with a Energy Management System as SaaS Sungrow, Deyee: Chinese Players, Ornate Solar: Indian Player Through EPC channels & direct sales pitch Land & Expand, we land our base inverter (grid-tied) first then later expand the modules for battery connectors, DG set connectors with High margin To establish a Virtual Power Plant enabler, this will allow peer-to-peer energy transaction using our hardware as an energy router. Private Limited NA Yes To get right mentorship and help to raise funds To pin-point our product strategy via mentorship and to raise our Seed fund YES We are looking to expand our presence in Bangalore which will help us utilise the facility as much as possible. Getting right industry partner in Bangalore is a great add. Yes Want to utilise the facility as a main base in Bangalore for our team to expand from there. Yes Supporting feature MaqLabs builds a modular, DC-coupled grid-tied solar inverter for C&I (10–125 kW). PV, grid, and add-on energy modules all couple to a single shared internal DC bus through standardized ports, and one supervisory controller orchestrates power flow across them using predictive load/generation analysis. The base unit ships grid-tied; battery, diesel-genset, and fuel-cell modules can be added later into open ports on the already-installed, live inverter — no rip-out or re-installation. Every unit is connected, enabling a fleet-wide energy-management layer (EMS) on top of the hardware. Every installed inverter continuously captures site-level generation, load, and fault-signature telemetry that off-the-shelf inverters don't expose — a unique behind-the-meter data footprint for each C&I site. Over a fleet, this lets us model load growth and predict when a site's economics tip toward storage (driving the module upsell), and build fault-likelihood/generation-loss insights that competitors relying on basic monitoring can't replicate. The data is first-party, generated by our own hardware, and compounding as the install base grows. our reinforcing moats: (1) a patent-pending method for live, on-line insertion of modules onto a shared DC bus — the hard engineering others would have to design around; (2) architectural lock-in — once our base inverter is installed, storage/genset/fuel-cell expansion happens through our proprietary modules, not a re-tender; (3) team credibility — we've designed and shipped BMS and energy-conversion hardware before, including a prior venture acquired by Ford, so this is a re-build of proven capability, not a first attempt; and (4) Made-in-India, DCR-ready manufacturing at grid-tied price, which imported/SKD competitors can't match on cost, compliance, and local service simultaneously. We benchmark on the standard inverter metrics — peak/weighted (CEC/euro) conversion efficiency [97 %], MPPT tracking efficiency [98%], output THD [4%], and thermal derating behaviour — plus reliability metrics: field availability/uptime [99 %], MTBF, and warranty-return rate. For the storage path we track round-trip efficiency and module-add response time. Beyond spec-sheet parity, our differentiator is measured at the site level: reduction in transition cost/downtime when adding storage (target: zero rip-out, zero plant shutdown), and fleet-wide fault-prediction accuracy from our EMS. All designs are validated to the relevant IS/IEC and CEA grid-connectivity standards and are DCR-compliant. Data is captured on an indigenously built logger with a hardened firmware/software stack, kept resident in India, and transmitted over encrypted channels with signed, authenticated over-the-air firmware updates to prevent tampering. Access is role-based, and the connected fleet is protected against rogue-device and unauthorized-command exposure — a gap we specifically designed against versus offshore loggers common in the market. We align to CEA cyber-security guidelines for connected grid assets and applicable data-protection norms (India's DPDP Act), and customer site data is used for their own optimization and, only in aggregated/anonymized form, for fleet insights. Yes, several tailwinds: DCR/ALMM localization requirements favour Made-in-India equipment; the PLI scheme and Make-in-India push support domestic power-electronics manufacturing; C&I open-access and net-metering/banking rules improve solar economics; and, most directly, emerging ESO/state BESS mandates and viability-gap funding for storage accelerate exactly the storage-add motion our modular architecture is built for. DPIIT startup recognition also provides fee, tax, and procurement benefits. Yes: (1) evolving CEA grid-connectivity and safety/cyber-security codes for inverters and connected assets; (2) mandatory BIS/IEC certification and DCR/ALMM listing timelines, which gate market access; (3) policy volatility in net-metering, banking, and open-access rules that affects customer ROI; (4) import-duty and component-sourcing shifts (cells, semiconductors) that move BOM cost; and (5) additional safety/compliance regimes as we add battery, genset, and fuel-cell modules. We mitigate by designing to standards up front, keeping the build indigenous/DCR-ready, and staying certification-ahead of each module launch. The hardware architecture scales, but the operational layers get stressed first: (1) supply chain — securing cells and power semiconductors at volume without BOM cost creep; (2) field service and spares — a 10x install base needs a much denser support/spares network across India; (3) the EMS backend and OTA pipeline — managing firmware, security, and telemetry across a large connected fleet reliably; (4) manufacturing QA consistency; (5) certification bandwidth as SKUs/modules multiply; and (6) working capital for inventory. Our roadmap addresses these through the EPC channel for reach, connected-by-default fleet tooling, and staged capacity expansion. Yes. Mohit Chand (Co-founder/CEO) — IIT Gandhinagar, M.Tech Power Electronics, 11+ years in design, BMS and energy-conversion products, prior venture acquired by Ford. Dr. Sreejith Raveendran (Co-founder/CTO) — IIT Delhi, PhD Power Electronics, 12+ years R&D in converter control, grid integration of renewables, motor-drive control, and hybrid-topology system architecture. Pratyush Bhatt (Co-founder/CBO) — IIT Gandhinagar, ex-SolarSquare, built its hybrid solar+storage vertical from zero to ₹10 Cr+ in 18 months, owning the full techno-commercial and factory-to-rooftop QA stack. The core team has designed and delivered production power hardware before — this is deep power-electronics expertise, not a software team entering hardware. We do not depend on third-party proprietary datasets — our operating data is first-party, generated and owned by our own installed hardware. Our control/edge firmware is developed in-house (owned IP); where we use open-source components. The "MaqLabs" trademark; and our proprietary hardware designs and firmware as trade secrets/owned IP. Our connected inverter fleet creates a closed feedback loop: real-world generation, load, thermal, and fault telemetry from every installed unit feeds directly back into R&D, so we improve from field data rather than lab assumptions. Software and control-algorithm gains ship to the entire installed base via signed over-the-air updates — improving efficiency, MPPT behaviour, and predictive orchestration without a truck roll. In parallel we run a staged hardware-revision roadmap (topology, thermal, and component optimization) and expand the module ecosystem (battery, genset, fuel cell), each validated against IS/IEC and CEA standards before release. The team's power-electronics depth lets us iterate on both silicon-level design and system-level control in-house. Both, sequenced deliberately — India first, then global. India is the beachhead: a large, fast-growing C&I solar market where DCR/localization and emerging storage mandates directly favour a Made-in-India, modular architecture, and where we can set the modular standard before incumbents lock the market into non-modular hardware. Once proven and certified at scale here, the same architecture extends to other global emerging markets with similar grid-tied-to-storage transition dynamics. Our patent and certification strategy is being built with that international path in mind. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/NaD8TZiMaOO8-MaqLabs_Deck_v4_VC.pptx, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/NaD8TZiMaOO8-MaqLabs_Deck_v4_VC.pptx https://youtu.be/oIYZkV4o-a4 Yes. MaqLabs exists to accelerate India's clean-energy transition by removing the biggest hidden barrier to storage adoption: the rip-out. Today, most C&I solar is installed on grid-tied inverters with no path to storage, so adding batteries later means scrapping a perfectly good inverter — capital lost and functioning hardware sent to e-waste. Our modular, DC-coupled architecture lets a business start grid-tied at low cost and add battery, genset, or fuel-cell capacity later without replacing anything, which lowers the capital barrier to storage, prevents avoidable electronic waste, and pulls more renewable + storage onto the grid faster. The impact compounds at scale: every connected inverter is a node that can be aggregated into a virtual power plant, making the grid more flexible and dispatchable and sharing grid-services value back with customers. It's also a Make-in-India deep-tech mission — building indigenous, DCR-ready power electronics and reducing dependence on imported/SKD hardware. NA NA MaqLabs is built by a team that has shipped power-electronics and energy-conversion hardware before (including a prior venture acquired by Ford). We have a customer-NRE-validated, scaled-down solar + battery proof point, are raising pre-seed to reach a certified 10 kW production prototype and first C&I pilots through EPC partners, and have a provisional patent being filed on our live modular-insertion method. We'd value IITACB's incubation for lab/prototyping infrastructure, certification support, and access to the C&I and investor network. checked
Aug 16, 2026 @ 9:38 AM Neeraj Govind Dhopte neeraj.dhopte@translab.io https://www.linkedin.com/in/neeraj-dhopte-8b0a6850?utm_source=share_via&utm_content=profile&utm_medium=member_ios +91-9980564646 Gaganjit - CEO, Neeraj - Executive Director We have worked together from more than 10 years. We met at one joint implementation at a bank. All We are complementing each other role and both are techies. Have coverage of 50% of banks in India and have expanded globally. We have built a Data & AI Agentic platform. Tantor AI Private limited https://tantor.ai/ Bangalore Data &AI platform with Agentic Mesh to build Agentic Applications Banking and Healtcare. Example Credit Underwriting and KYC through Agentic AI We have built 20+ banking Agentic AI apps on our Tantor platform with a scope of adding 100 more . Data Federation with UI based Agentic mesh Product-Market Fit Revenue, Pilots, Signups Banking and Healthcare 300 Million Dollars NA NA Subscription based NA We have services base and reach with strong sales team. We have 60% of banks and hospitals our services customer which is making easy for penetration. Sales , Linked in, OEM hardware partners and have signed with Big 4s NA Private limited Bootstrap Yes I am an alumni and reach with IIT ACB incubator we can reach to incestors NA Yes NA No NA Yes Core engine a NA NA NA NA NA NA We are micro services architecture and scalable. Yes. People with 20+ years of experience in banking and healthcare NA NA Both 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/xhDLXp9ktWFB-Tantor_Short_Presentation.pptx, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/xhDLXp9ktWFB-Tantor_Short_Presentation.pptx http://NA NA NA Gmail checked
Aug 16, 2026 @ 8:08 AM Vishal Kashyap 14.vishal@gmail.com https://www.linkedin.com/in/vishalkashyap1/ 9108168555 2 YoLearn.ai Bengluru Ai tutor Scallig quality education AI ip protected books Revenue yes Yes yes Yes Core engine 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/696AsW9haul9-Investor-Memo-1.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/696AsW9haul9-Investor-Memo-1.pdf na checked
Aug 16, 2026 @ 7:47 AM Vishal Kashyap 14.vishal@gmail.com https://www.linkedin.com/in/vishalkashyap1/ 9108168555 2 IIT and Industry background YoLearn.ai Bengluru AI tutors Scaling of quality education Agentic AI converting books into iBooks(Intelligent) Ip protected books Users Revenue K-12 Industry educationa and traning Yes Interact with local inddutry Yes Core engine 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/jHMDiKPTENhB-InvestorMemo.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/jHMDiKPTENhB-InvestorMemo.pdf NA checked
Aug 14, 2026 @ 6:01 PM Aditya Raj rj09aditya@gmail.com https://www.linkedin.com/in/aditya-raj-422213277/ http://N/A +91 7209543317 Aditya Raj (Founder & CMO): Entrepreneur and marketing leader with deep experience in brand building and creative agency operations (Founder of Paletterse), driving overall strategy, business growth, and market positioning for Hungrr. Yashraj (Co-founder & Technical Lead): Core technologist and engineer managing product architecture, technical development, and system operations for the platform. We are cousin brothers who share a strong bond and a common vision for building impactful tech solutions. We have been working together closely on Hungrr since mid-March 2026, combining our respective strengths in engineering and business strategy to build, develop, and scale the platform. All Our biggest strength as a team is our unique combination of deep family trust and highly complementary skill sets. As cousin brothers working closely together, we share a seamless communication channel and a unified vision. Aditya drives business growth, brand strategy, and market positioning, while Yashraj leads technical architecture and product engineering. This strong synergy allows us to execute fast, adapt dynamically, and build Hungrr with complete alignment. hungrr N/A Patna, Bihar Hungrr is a multi-cart platform that lets user order food from multiple restaurant in a single checkout. Hungrr solves two major problems: it eliminates redundant delivery fees by letting users order from multiple local kitchens simultaneously in a single checkout, and it helps independent restaurants by offering a fair, low-commission model that protects their profit margins. Hungrr is an app that lets you order food from different local restaurants at the same time with a single checkout. Instead of paying extra delivery fees for each place, our delivery person picks up all your items in one trip. This saves you money and helps local restaurants keep more of their hard-earned money by charging them very low fees. Hungrr’s uniqueness and defensibility lie in our multi-vendor cart architecture and intelligent batched delivery logistics. While traditional platforms lock users into single-kitchen orders and burden local restaurants with high commissions, Hungrr enables simultaneous multi-restaurant checkout and combines orders into a single optimized delivery trip. This creates a powerful defensible moat through a three-sided benefit: customers save on redundant delivery fees, independent kitchens retain higher margins through our sustainable low-commission model, and our hyper-local market focus allows us to build strong community-driven network effects and operational efficiency that incumbents find difficult to replicate in emerging urban micro-markets. Idea Testimonials Urban consumers, students, and working professionals looking for food variety and convenience, alongside local independent restaurants and cloud kitchens seeking a fair, sustainable delivery platform. India's total online food delivery and quick-commerce market. Online food delivery market across emerging Tier-1 and Tier-2 urban centers and student micro-markets in India. High-density student hubs, residential clusters, and urban micro-markets in our initial rollout locations like Patna. A sustainable low-commission model for restaurant partners, complemented by premium delivery tiers, subscription perks for frequent users, and in-app promotional placements. Zomato and Swiggy Targeted digital marketing, hyperlocal social media campaigns, student and local influencer partnerships, and cross-promotions with onboarded restaurant partners. Executing a hyper-local pilot launch in targeted urban micro-markets and student hubs, focusing on high-density merchant onboarding, community engagement, and leveraging our unique multi-vendor checkout to drive organic word-of-mouth growth. To build India's leading unified multi-vendor food delivery ecosystem that redefines urban food logistics. Our vision is to empower local culinary entrepreneurs with fair and sustainable economics while transforming the customer ordering experience through intelligent batched delivery and multi-kitchen convenience. N/A 0 Yes We are applying to IITACB Incubator to gain access to world-class mentorship, strategic guidance, and a robust founder network as we scale Hungrr, our unified multi-vendor food delivery platform. During the programme, we aim to refine our multi-vendor cart architecture, optimize our batched delivery unit economics, build key industry connections, and prepare for our upcoming scaling phase and fundraising milestones. Yes We can leverage Bangalore's advanced tech talent pool, vibrant startup ecosystem, and dynamic urban market insights to scale our technical infrastructure and operational strategies. IIT ACB can help us bridge local execution with expert mentorship, strategic industry connections, and investor networks to accelerate Hungrr's growth. Yes We wish to utilize the collaborative workspace for our founding team (Aditya Raj and Yashraj) to drive product development and operations, interact closely with resident mentors and fellow founders, and leverage incubator facilities for focused execution and team synergy. Yes Core engine Built on a scalable cloud-native microservices architecture using modern frontend frameworks (React Native/Flutter) and robust backend technologies (Node.js/Python). The core engine incorporates proprietary routing and algorithmic models for multi-vendor cart synchronization, dynamic order bundling, and intelligent batched delivery route optimization, integrated via secure RESTful APIs. Our proprietary data advantage lies in hyper-local consumer ordering patterns, multi-kitchen cart affinity data, and optimized batch delivery route metrics specific to emerging urban micro-markets, enabling superior demand forecasting and logistics efficiency. Hungrr is defensible through our unique multi-vendor cart architecture and intelligent batched delivery logistics. While traditional platforms lock users into single-kitchen orders, Hungrr enables simultaneous multi-restaurant checkout and optimized single-trip delivery. This creates a strong defensible moat via sustainable low commissions for local merchants and lower delivery overhead for customers. We evaluate performance and reliability using key engineering metrics, including order synchronization latency, route optimization efficiency, multi-vendor cart success rate, API response times, and system uptime, benchmarked against standard industry delivery SLAs. We ensure data security through end-to-end encryption (SSL/TLS for data in transit and AES-256 for data at rest), secure tokenized payment integrations (PCI-DSS compliant gateways), role-based access control, and strict adherence to local data privacy regulations. Government initiatives promoting digital public infrastructure, Startup India framework benefits, and policies supporting local MSME commerce and fair marketplace practices positively contribute to our business growth. Standard food safety and hygiene regulations (such as FSSAI compliance for our restaurant partners), municipal delivery and labor guidelines, and data privacy regulations (like India's Digital Personal Data Protection Act) regarding user and transactional data. A sudden 10x surge in traffic could strain concurrent multi-vendor cart synchronization, real-time dispatch routing calculations, and database connection pools during peak lunch and dinner rush hours if server infrastructure auto-scaling isn't fully optimized. Yes, our in-house technical team has strong expertise in full-stack engineering, cloud-native microservices architecture, algorithmic routing, and real-time data processing for multi-vendor logistics. We utilize standard open-source frontend and backend frameworks (such as React Native/Flutter and Node.js) under permissive open-source licenses (MIT/Apache 2.0). Our proprietary IP includes our custom multi-vendor cart synchronization logic and batched delivery routing algorithms. Through continuous automated performance monitoring, tracking order synchronization latency and API response times, regular code profiling, and iterative tuning of our route optimization and dispatch algorithms based on real-world delivery data. India 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/GgH7wu5lx4w3-Hungrr_Pitch_Deck.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/GgH7wu5lx4w3-Hungrr_Pitch_Deck.pdf Yes. Hungrr is impact-focused on both environmental and economic fronts. Environmentally, our intelligent batched delivery logistics combine multiple orders into a single trip, significantly reducing fuel consumption and urban carbon emissions compared to traditional single-order deliveries. Economically, we empower local independent kitchens and culinary entrepreneurs by replacing heavy, margin-squeezing commissions with a fair, sustainable low-commission model. NA NA Hungrr was selected among the top 1000 out of over 26,000+ applicants in the nationwide Vande Bharatam initiative. We are currently in our pre-launch phase, actively preparing for our upcoming pilot rollout in Patna, Bihar, with a long-term vision to scale our unified multi-vendor delivery model across growing urban markets in India. checked
Aug 14, 2026 @ 3:52 AM Charan Teja charan@fitcrave.co https://www.linkedin.com/in/charan-teja-78218b255?utm_source=share_via&utm_content=profile&utm_medium=member_android +91 8897444632 Charan Teja - Founder & CEO. IIT Kharagpur, dual-degree (2021–26). Leads product, strategy, and partnerships end-to-end, and has personally driven the build across FitCrave's meal planning, meal recognition, chatbot, community, kitchen operations, and delivery systems. Currently leading the IIT Hyderabad campus pilot from the ground up. Team of 6 across tech and operations All six of us are friends and batchmates from IIT Kharagpur. We'd each experienced the same problem firsthand no institutional food or nutrition service actually adapts to what you're eating and where you're eating it and kept waiting for the market to solve it. When it didn't, we decided to build it ourselves. We've known each other since our time at KGP and have been working together on FitCrave since then. 1 We're not guessing our way through this. Two of us come from top-tier strategy consulting, which shows up in how we've thought about unit economics and go-to-market instead of winging it. We've got product experience from scaling a services marketplace, and a designer who makes sure the app actually feels considered, not just functional. Two engineers have taken us from an idea to nine working repos app, AI backend, kitchen ops, delivery, all live. And we brought in a chef and business consultant with 20+ years in the industry who's advised 50+ restaurants across Hyderabad, so the part that kills most food startups actual kitchen economics isn't something we're figuring out as we go. FitCrave fitcrave.co in India FitCrave is an AI-powered wellness platform that turns everyday nutrition and fitness data into a personal longevity system reading what you eat, how you train, and how you recover, and turning it into daily guidance that compounds into long-term healthspan. In cities, health tracking is fragmented a nutrition app, a fitness app, a wearable, and a delivery app that all ignore each other. Nobody connects what you eat today to how you'll age. People want to optimize for the long game energy, metabolic health, longevity but the tools force them to manually stitch together logging, coaching, and food, and most give up within weeks. FitCrave unifies the loop: AI-powered photo logging with mandatory confirmation, so nutrition data stays accurate; adaptive meal and workout plans built around real dietary needs and allergies; wearable integration pulling sleep, recovery, and heart data into a single longevity-oriented health score; an AI coach that explains the "why" behind every recommendation; and a marketplace of macro-verified meals that auto-log with zero estimation error when ordered. One system, from decision to data to delivery. Most health apps optimize for today's calorie count. We optimize for a compounding score across nutrition, recovery, and training the same inputs longevity science actually tracks and we close the loop with verified data instead of estimates: photo confirmation over guessed logs, wearable data over self-report, and kitchen-verified nutrition over app-estimated meals. That accuracy compounds into a dataset competitors relying on generic AI recognition can't replicate. MVP Pilots Health-conscious urban Indians aged 18–35 students and working professionals in Tier 1 and Tier 2 cities who want AI-guided nutrition and fitness but are underserved by generic tracking apps, plus corporate wellness programs looking for a measurable employee health benefit. ₹9,116 Cr (~$1.09B) combined AI fitness SaaS (₹716 Cr) and healthy food delivery (₹8,400 Cr) across India's urban health-conscious population, growing 21–44% CAGR. ₹2,890 Cr (~$346M) fitness-aware urban Indians aged 18–35 in Tier 1 and Tier 2 cities where FitCrave can realistically operate, combining SaaS reach (₹890 Cr) and dark-kitchen delivery across a planned 10-city footprint (₹2,000 Cr). ₹196 Cr (~$23.5M) ARR realistic 5-year capture at 1,00,000 paying users and roughly 10,000 daily kitchen orders, our base case against a conservative floor of ₹102 Cr and a bull case of ₹380 Cr. Three lines: subscription SaaS (₹299–499/month for students and professionals), B2B corporate wellness contracts (~₹190/employee/month), and margin on dark-kitchen food orders (~₹85 net per order). Subscription drives recurring revenue; the kitchen adds margin and produces the verified nutrition data the AI depends on. HealthifyMe and MyFitnessPal on nutrition tracking; Zomato and Swiggy's healthy-focused offerings and cloud-kitchen brands like EatFit on food delivery. None combine AI-driven personalization with owned kitchen fulfillment that gap is where we compete. Campus-first distribution through student networks and institutional partnerships (our current IIT Hyderabad engagement), which gives materially lower CAC (₹100–250) than paid acquisition, then expansion into metro professionals and B2B corporate wellness contracts as the kitchen network grows. Land through low-CAC campus channels where students already have an unmet need and no competitor targets them specifically, prove kitchen unit economics at one location, then expand city by city metros next, followed by corporate wellness contracts with each new market anchored by a physical kitchen rather than software alone. India has a diagnosis industry and a food industry, and they don't talk to each other. A doctor tells you you're B12 deficient or pre-diabetic, hands you a printout, and disappears for three months. What you eat every single day the part that actually determines whether you get better is left entirely to you, in a country where most people eat what a hostel mess or a work canteen decides for them. FitCrave becomes the layer that closes that gap. We partner with diagnostic labs for at-home biomarker and blood testing, and with doctors and nutritionists who own the clinical call. Then we do the part nobody else does: we turn their prescription into what you actually eat, meal by meal, verified not a PDF you forget by Tuesday. Our AI keeps you on the doctor's plan every day between visits; the doctor stays the one steering it. That's the business. Not another tracking app. The infrastructure that makes a health plan actually happen and every meal, every correction, every retest becomes data that makes the next recommendation sharper. In five years, we're not selling an app. We're selling adherence the one thing the entire healthcare industry has never solved and we're the only ones building it from the food up. FitCrave Private Limited Bootstrapped. Yes We're building FitCrave's Phase 2 expansion into metro cities, and Bangalore is our next market after our current campus traction at IIT Hyderabad. We need what IITACB specifically offers at this stage: investor connects for our seed round, mentorship from founders who've scaled consumer health or food businesses, and a foothold in Bangalore's startup ecosystem as we move from a campus-first model into corporate wellness and metro consumer acquisition. Close our seed round, validate FitCrave with Bangalore's tech workforce as our first metro market, and build the corporate wellness pipeline that the Bommasandra hub makes possible. We also want structured guidance on the harder parts of scaling food-tech kitchen unit economics, compliance, and go-to-market sequencing from mentors who've actually done it. Yes Bommasandra's tech and pharma workforce is precisely our Segment C customer employees at companies with wellness budgets who need AI-guided nutrition but currently get generic, disengaging corporate wellness programs. That's a direct path into our B2B channel: FitCrave as the wellness benefit provider for companies in the hub, not just a consumer app hoping for organic downloads. IIT ACB's value to us is specific: warm introductions to companies in Bommasandra for pilot corporate contracts, investor access for our seed round, and mentorship on the operational side of scaling a hybrid tech-plus-kitchen model in a new city sequencing that we haven't had to solve yet at IIT Hyderabad Yes A physical presence in Bangalore turns our Bommasandra pitch from a plan into something we can execute immediately IITACB seats mean our team is on the ground for the corporate wellness conversations we're targeting in the hub, not running them remotely from Hyderabad. Beyond that, we'd use the incubator as our metro-city base of operations: a stable environment for the engineering and ops work of adapting FitCrave from a campus-first product to a Bangalore consumer and corporate launch, direct access to IITACB's mentor network for the parts of scaling food-tech we haven't had to solve yet kitchen operations in a new city, compliance, metro go-to-market and proximity to the investor connects and founder community that come with being physically present rather than a name on an application. Yes Core engine AI (Google Gemini) drives the core product loop, not a bolt-on chatbot: mess menu reading via vision extraction, meal photo recognition and logging, personalized meal and workout plan generation, and an AI coaching layer. We don't hold filed IP no patents. Our defensibility is architectural and data-driven rather than algorithmic: the combination of persisted institutional food context, Indian dietary constraint modeling, and (long-term) a proprietary correction dataset from user-verified food logs. None at meaningful scale yet we're early. The mechanism is built into the product by design: every AI-logged meal requires user confirmation, and every correction is designed to become training data specific to Indian regional dishes, mess-hall food, and household portion sizes exactly what global nutrition databases handle poorly. That's the intended moat; it accumulates with usage rather than existing today. AI food recognition is commoditizing every competitor will have equivalent capability within a year. Our defensibility is the combination: a persisted institutional menu (mess/canteen) nobody else models, dietary constraint handling built for how India actually eats Jain, eggetarian, fasting patterns rather than a bolted-on vegetarian toggle, and owned kitchen fulfillment producing verified, zero-estimation-error nutrition data no pure software competitor can generate. Honestly, this is early we haven't yet built a formal benchmarking practice. What we're instrumenting now: crash-free session rate, API latency by endpoint, AI recognition accuracy measured against a ground-truth set of weighed Indian meals (not yet run), and an automated allergen/dietary-constraint validator rejection rate as a proxy for AI output reliability. We're building the measurement discipline alongside the product rather than claiming numbers we don't have yet. We're pre-launch and treating this as a gating requirement, not an afterthought. Architecture: Firebase Auth for identity with server-side token verification, encryption in transit, India-region data residency. As we finalize our public launch, we're implementing granular DPDP-aligned consent (separate, revocable consent for health data processing, location, marketing, and model training), application-layer encryption for sensitive health fields, and a full data export and deletion pipeline. We've run our own internal security audit ahead of launch and are closing findings before onboarding real users at scale. DPIIT Startup India recognition, already secured, which gives us tax benefits and simplified compliance. ONDC's interoperable commerce protocol is a potential future distribution channel for our kitchen network without the 20–30% commission structure of the incumbent delivery platforms. Several, and we're building for them rather than around them: DPDP Act obligations given we process health data; FSSAI licensing for kitchen operations; GST invoicing for food delivery; App Store and Play Store payment policy, which requires native in-app purchase for digital subscriptions on iOS; and a clear internal line between wellness guidance and medical claims, since we never want FitCrave positioned as diagnosing or treating conditions. Three things, honestly assessed: our AI layer has no rate limiting or cost controls today, so cost scales linearly with usage with no ceiling that's a near-term fix. Our dual-database architecture (MongoDB plus Firestore) would need a clearer single source of truth to avoid consistency issues at higher write volume. And the real bottleneck isn't software at all it's kitchen capacity, which is physical and doesn't scale the way code does; we're deliberately proving unit economics at one location before assuming this scales. Not a dedicated ML research team we're an application engineering team building on top of Google's Gemini API rather than training our own models. Two engineers own the full application build across mobile and backend. Our depth is in system architecture and integration, not foundation model research, and we're honest that our current moat is data and product design, not a novel algorithm. Google Gemini (licensed commercial API, not open source) is our core model. Application stack uses open-source frameworks under standard licenses Flutter, FastAPI, LangChain, LangGraph, MongoDB. Firebase and Cloud Run are licensed commercial infrastructure. We hold no filed patents or IP registrations today; our proprietary asset is our own application code and, over time, our user-correction dataset. User corrections on AI-logged meals feed back into food and portion accuracy over time that pipeline is a build priority, not yet fully live. We're establishing automated testing and monitoring as we approach launch, and we'll migrate off Gemini 2.5 Flash before its October 2026 retirement, benchmarking replacement models on our actual prompts rather than assuming pricing or quality parity. India first, deliberately. Our expansion sequence is campus network → metro cities → corporate wellness within India, with Southeast Asia and the Middle East as later phases once the India model particularly kitchen unit economics is proven. We're not building for global simultaneously; India has to work first. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/Pb7NCDMD0J3L-FitCrave_pitchdeck_2026-compressed.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/Pb7NCDMD0J3L-FitCrave_pitchdeck_2026-compressed.pdf Yes. FitCrave exists because institutional eaters, working professionals, hostel students, PG residents, canteen workers get no say in what they eat and no tool that adapts to it, and that gap has real health consequences at scale in India. Our mission is to make personalized, accurate nutrition guidance and genuinely healthy food accessible to people whose food choices are structurally constrained, starting with students and working professionals who can't afford to fail their health while building their careers. Long-term, we want food-based intervention the kind that can meaningfully help conditions like B12 deficiency or pre-diabetes to be something a normal person can access and afford, not a premium service reserved for people who can already pay for private nutritionists and lab work. NA Venkata Ravi Teja Villa We're not looking for a badge on our website we want the kind of tactical, industry-tested guidance that shortens our path to getting this right: pressure-testing our kitchen unit economics, sharpening our go-to-market as we move into Bangalore, and learning from people who've actually scaled a hybrid tech-and-physical-operations business before we make expensive mistakes learning it ourselves. FitCrave exists to make real, personalized nutrition guidance and genuinely healthy food reachable for people who don't currently have access to it that's the product we're trying to build, and IITACB is the kind of environment that gets us there faster and with fewer wrong turns. checked
Aug 14, 2026 @ 2:25 AM Rahul Raj resumeupgrader.rn@gmail.com https://www.linkedin.com/in/rahulraj2001/ https://resumeupgrader.com +918905936141 Rahul Raj: CEO (Vision & Strategy), IIT Dharwad B.Tech in CS. Niteesh Kamal Chaudhary: CTO (Tech & Innovation), IIT Dharwad B.Tech in CS. We met at IIT Dharwad during our B.Tech in Computer Science and have been working together on this startup for over a year. 2 Our biggest strength is our deep technical expertise from IIT Dharwad, combined with a strong understanding of user pain points in resume screening and recruiting. Resume Upgrader https://resumeupgrader.com Dharwad, Karnataka Resume Upgrader offers instant resume analysis and ATS-friendly tailoring for job seekers, and a bulk filtering recruitment platform for employers. Job seekers face ATS rejections with generic resumes, while employers struggle to filter top candidates from bulk applications. Instant resume analysis against JDs, rendering tailored ATS-friendly resumes, and one-click applications. For employers, 'Hire Smarts' enterprise ATS filtering and scheduling platform. Our proprietary dual-sided platform provides real-time personalized resume feedback to candidates while offering highly accurate AI-driven screening and workflow automation for recruiters. MVP Testimonials Job seekers needing ATS resume optimization, and corporate employers or recruitment agencies looking to filter bulk applications. $27.6 Billion+ $2.76 Billion+ $220 Million+ B2C subscription for premium candidate features, and B2B SaaS enterprise pricing tiers for employers. Rezi, ResumeWorded, Jobscan, and traditional ATS systems like Greenhouse or Lever. SEO and organic content, career portals, partnership with colleges/bootcamps, and direct B2B sales for employers. Target college graduating students via student partner programs, offer free resume reviews, and target mid-market recruitment agencies with a 14-day free trial. To become the global leader in AI-driven end-to-end recruitment, matching candidates to roles with zero friction and creating a decentralised talent verification protocol. Yes NA Yes To leverage mentoring from senior IIT alumni, connect with early-stage investors, and access Bangalore's active recruitment market. Validate our recruiter enterprise dashboard, launch pilot programs with mid-sized companies, and raise seed funding. Yes, we are open to virtual participation, though we prefer physical collaboration where possible. We can connect with hundreds of manufacturing and tech companies in Bommasandra to pilot our recruiter bulk filtering platform. IITACB can facilitate direct warm introductions to HR leaders in these companies. Yes We will use the co-working space, meeting rooms for client presentations, high-speed internet, and regular networking events to build partnerships. Yes Core engine We use fine-tuned Llama-3-8B model hosted on AWS EC2 G5 instances for parsing and ranking. The backend is built with FastAPI/Python, frontend in React, and PostgreSQL for our primary database. We have collected and anonymized over 10,000 verified resumes mapped against real interview feedback from IIT Dharwad alumni and partner hiring managers. Our proprietary dataset of verified resume feedback and our custom fine-tuned Llama-3 parsing model which has higher accuracy on Indian resumes than generic LLMs. We evaluate using accuracy, precision, and recall on a holdout test set of 1,000 resumes. Our parsing accuracy is 94% compared to 82% for generic LLMs, and latency is under 500ms. We encrypt all candidate data in transit and at rest using AES-256. We perform automated data anonymization for parsing, and strictly adhere to GDPR principles. Digital Personal Data Protection (DPDP) Act in India helps us by requiring companies to handle user data more securely, driving adoption of compliant screening tools like ours. Potential changes in AI regulation or discrimination laws regarding algorithmic bias in recruitment. We mitigate this by ensuring human-in-the-loop review. Database query latency on full-text search and API rate limits on third-party integrations. We are addressing this by implementing Redis caching and horizontal scaling. Yes, our co-founder Niteesh Kamal Chaudhary has deep expertise in NLP and ML models, and we have 2 part-time software engineers working on backend. We use open-source Llama-3, PyTorch, and HuggingFace transformers library. The model is licensed under Meta Llama 3 Community License Agreement. All code built on top is owned by us. By active learning: collecting feedback on misclassified resumes from users to refine our fine-tuning training dataset, and exploring larger models like Llama-3-70B. We are building for both, starting with India (since we understand the market and local talent pools) and planning to expand globally next year. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/zoyERrGyw33O-Pitchdeck_Resume_Upgrader.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/zoyERrGyw33O-Pitchdeck_Resume_Upgrader.pdf https://drive.google.com/file/d/1GTklQKroqbw7Ak-PSssQI5ihI0Bkv2K9/view?usp=sharing Yes, we are helping college students and early-stage professionals from underrepresented backgrounds get equal visibility by optimising their resume parsing accuracy and matching them with open opportunities. NA IIT Dharwad NA checked
Aug 14, 2026 @ 12:47 AM Shreyas Kalva shreyaskalva6@gmail.com https://www.linkedin.com/in/shreyaskalva/ http://NA +918660415746 Shreyas Kalva, Co-Founder & CMO, Persuing B.E in Computer Science & Business Systems (2024-2028). Kanishk Singh, Founder & CEO, Persuing B.E in Computer Science & Design (2024-2028) We meet each other in one of the Networking Events where we got to know that we both are from same college & got connected to each other. So right now, we both are working with each other since 13 months building the Future of Student Identity. 2 Our biggest strength is the combination of technical expertise and strong business, design, and market understanding within the team. We move quickly from identifying a problem to building, testing, and positioning a solution. Each founder brings a different strength - technology, product, business development, marketing, and design - allowing us to execute end-to-end without relying heavily on external resources. ShowWork https://www.showwork.in/ Bangalore ShowWork is an AI-powered professional identity platform for students and developers that automatically transforms their real work into a complete, continuously updated professional presence. By integrating with platforms such as GitHub and LinkedIn, ShowWork understands a user's projects, skills, achievements and experience, and converts them into professional portfolios, resumes, project showcases and content. Its key differentiator is JD-curated professional identity — automatically adapting a user's resume, portfolio and showcased projects to match the requirements of each specific job description. Students and early-career professionals are doing meaningful work, but struggle to effectively convert that work into a strong professional identity. Their projects, skills and achievements are scattered across GitHub, LinkedIn, certificates and other platforms, while resumes and portfolios often become outdated or require constant manual updates. The problem becomes even bigger when applying for jobs. A candidate may apply to 10 different roles but typically uses one generic resume and portfolio, or manually edits them for every application. This is time-consuming, inconsistent and often fails to highlight the experience most relevant to each role. We are solving the larger problem of professional identity management — helping individuals continuously turn their actual work into a professional presence and automatically position themselves differently for different opportunities. ShowWork acts as an automated professional identity layer for students and developers. Users connect their existing professional platforms, such as GitHub and LinkedIn, and ShowWork uses AI to understand their projects, contributions, skills and achievements. It then transforms this information into professional assets such as resumes, portfolios and detailed project showcases. The core of the platform is our JD-curated professional identity system. When a user targets a specific job description, ShowWork analyzes the role requirements and automatically identifies the most relevant skills, projects and experiences from the user's existing profile. It then generates a role-specific resume and portfolio that positions the candidate around what that particular employer is looking for. This means a user's professional identity is no longer static. The same underlying work can automatically be presented differently depending on the opportunity - without the user having to manually rewrite their resume, rebuild their portfolio or decide which projects to showcase every time they apply. Our biggest differentiator is that ShowWork is not simply an AI resume builder or portfolio builder. We are building an automated professional identity management system. The platform combines two powerful layers: 1. Work-to-Identity Automation: ShowWork connects with platforms such as GitHub and LinkedIn to continuously understand what a user has actually built, contributed to and achieved, reducing the need for manual professional profile management. 2. JD-Curated Identity: Instead of maintaining one generic resume and portfolio, ShowWork understands a specific job description and automatically determines which skills, projects and experiences should be emphasized for that opportunity. It then generates a tailored professional representation around those requirements. This creates a fundamentally different workflow: instead of users manually creating a resume → building a portfolio → finding a job → editing everything again, ShowWork starts with the user's real work and continuously transforms it into the right professional identity for each opportunity. Over time, the combination of a user's work history, professional data, generated assets and job-specific positioning can create a highly personalized professional identity layer that becomes increasingly useful as the user's career evolves. In short: ShowWork doesn't just help users create a resume. It automatically manages, builds and adapts their professional identity around both their work and the opportunities they want. MVP Pilots, Signups Primary customers are college students, fresh graduates and early-career developers who need to build and continuously maintain a strong professional identity while applying for internships and jobs. Our initial focus is on students and developers who actively build projects on GitHub and maintain professional profiles on platforms such as LinkedIn. Our secondary B2B2C customers are colleges, universities and placement cells that want to improve students’ employability and help them automatically create job-ready professional profiles, resumes and portfolios. Over time, we also see employers and recruiters as a customer segment for discovering and evaluating candidates based on verified work and skills. $1.5B+ $300M $15M Freemium for individuals, with premium AI features and JD-curated resumes/portfolios. B2B2C partnerships with colleges and placement cells will be our primary revenue channel, with future recruiter monetization. Simplify, Teal, Rezi, Kickresume, LinkedIn and traditional portfolio/resume builders. We acquire users through college communities, student networks, social media, referrals and partnerships with colleges and placement cells. We also leverage developer communities and platforms such as GitHub and LinkedIn to reach our target users. We plan to start by reaching students and developers where they already spend time - college communities, student clubs, developer communities, LinkedIn, social media and referrals. Instead of pushing ShowWork as just another career tool, we want users to experience the value firsthand: connect their existing work and see it automatically turned into a professional identity. As we build a strong base of users, we will work with colleges and placement cells to bring ShowWork to students at scale and make it part of their placement preparation. This also gives us a strong distribution channel as students enter the job market. Over time, we plan to expand to recruiters and companies, creating a two-sided ecosystem where individuals build their professional identity around their actual work, while companies can discover relevant talent through it. Our vision is to build the professional identity infrastructure for the next generation workforce. ShowWork will continuously understand a person's work, skills and achievements and automatically turn them into the right professional identity for every opportunity - from resumes and portfolios to project showcases and professional content. Ultimately, we aim to become the layer connecting what people actually build with how the world discovers and hires them. NA NA Yes We are applying because we want to take ShowWork from an early-stage product to a scalable business. IITACB’s access to experienced mentors, investors and the startup ecosystem can help us sharpen our business model, validate our market and become more investor-ready. We want to strengthen our product-market fit, get honest feedback from experienced founders and investors, refine our go-to-market strategy and build meaningful investor connections. Most importantly, we want to understand what it takes to scale ShowWork from early adoption into a larger professional identity platform. Yes, we are fully open to virtual participation and can actively participate in all programme sessions, mentoring and investor interactions. Bangalore gives us access to a strong pool of students, developers, startups and technology companies who are directly relevant to ShowWork. The Bommasandra industrial ecosystem and wider Bangalore market can help us build partnerships, understand hiring needs and expand our user and institutional network. IITACB can support us through its industry connections, mentorship, investor network and access to experienced founders. Yes We would use the space as a base for focused product development, team collaboration, mentor meetings and discussions with potential partners and investors. Being part of the incubator ecosystem would also help us collaborate with other startups and build stronger industry connections. Yes Core engine ShowWork uses a modular web architecture with a frontend application, backend services, database and AI layer. The platform integrates with APIs such as GitHub and LinkedIn to collect relevant professional data, processes it through our application layer, and uses LLM APIs for profile understanding, resume generation, portfolio creation and JD-based curation. The architecture is designed to scale independently across product, AI and infrastructure layers. We do not claim a proprietary data advantage at this stage. However, as users build their professional identity on ShowWork, we can develop structured insights around projects, skills, job descriptions and career profiles. Over time, this creates a growing first-party professional identity dataset that can improve our curation and personalization. Our defensibility comes from combining work-data integrations, automated professional identity building and JD-based personalization in one system. Instead of simply generating a resume from user input, ShowWork continuously understands a user's actual work and can transform the same underlying profile into different resumes, portfolios and project showcases based on specific opportunities. Over time, user history, personalization and accumulated professional identity data can strengthen this system. We evaluate the platform based on AI output relevance, JD-to-profile matching accuracy, generation time, API response time, system uptime, error rates and successful completion of resume/portfolio generation workflows. As we scale, we will benchmark these metrics against user feedback and competing workflows to continuously improve reliability and output quality. We follow a privacy-first approach, particularly because ShowWork works with professional and career-related data. We use authenticated API access and aim to follow least-privilege access principles, secure data transmission and controlled storage. Users should have transparency and control over the information connected to their account, with appropriate mechanisms for data deletion and access management. We will continue strengthening our security and compliance practices as the platform scales. Currently, there are no specific policy interventions that our business depends on. However, India's focus on digital skilling, employability, AI adoption and improving outcomes for students and early-career professionals creates a supportive ecosystem for ShowWork. The main risks relate to data privacy, user consent and third-party platform API policies, particularly when handling professional information from platforms such as GitHub and LinkedIn. We plan to follow applicable data protection requirements, use authorized API access and maintain clear user consent and data controls. At 10x scale, the main challenges would be AI/API costs, API rate limits, database load and concurrent processing of resume and portfolio generation. We are designing the architecture to scale these components independently and will use caching, asynchronous processing and infrastructure scaling to manage increased demand. Yes. Our technical co-founder leads the engineering side of ShowWork, with expertise in software development, AI integration, backend systems and product engineering. The team is building the core platform in-house, while leveraging established AI models and APIs where appropriate. We currently use publicly available and user-authorized data through platforms such as GitHub, along with third-party AI APIs and standard open-source software libraries. These are used under their respective API terms and open-source licenses. Our core product logic, workflows, JD-curation system and platform implementation are developed in-house. We will continuously improve the system through user feedback, evaluation of AI output quality, JD-to-profile relevance, generation speed, reliability and API performance. As usage grows, aggregated product insights will help us improve our curation logic, personalization and overall user experience. We are starting with India, particularly the large student and early-career developer market, while building the product for global use from the beginning. Since the core problem of managing professional identity and tailoring profiles for different opportunities is global, we see strong potential to expand into international markets. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/5r9D25VZgXBS-SHOWWORK_PITCH_DECK_GENERAL_compressed.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/5r9D25VZgXBS-SHOWWORK_PITCH_DECK_GENERAL_compressed.pdf Yes. ShowWork is built around making professional opportunities more accessible to students and early-career professionals. Many capable individuals have strong skills and projects but struggle to present them effectively because professional identity building is still largely manual and dependent on polished resumes or networks. Our mission is to change this by helping people turn the work they actually do into a strong, continuously updated professional identity, and automatically curate it for the opportunities that matter to them. We want to reduce the gap between what someone can actually do and how effectively they can showcase it to the world. NA NA checked
Aug 13, 2026 @ 11:27 PM Vijaysekar Varma Ellanti vijay.ellenti@gmail.com http://www.linkedin.com/in/vijayvarmaellenti 9900377394 1 Ground Execution V Farms Tirupati Vfarms is an agriculture company building an Agriculture-to-Energy platform, connecting agricultural resources, energy crops and biomass with multiple energy and value-add opportunities such as CBG, bioenergy and bioethanol. We work across cultivation, Precision Farming, agricultural feedstock development, aggregation, logistics and technology-enabled operations, combining agricultural expertise with process innovation to build scalable and efficient agriculture–energy systems. Our long-term vision is to build circular agriculture systems that contribute to energy security, rural value creation and the Net Zero transition. Agriculture and the energy sector are not sufficiently connected. Agricultural resources often remain underutilised or are not efficiently linked to emerging energy and value-add opportunities, while energy projects face challenges in securing reliable, economical and consistent agricultural resources. Vfarms is addressing this gap by connecting cultivation, energy crops, biomass, aggregation, logistics and technology with multiple energy pathways such as CBG, bioenergy and bioethanol — enabling better resource utilisation, rural value creation and a more scalable Agriculture-to-Energy ecosystem. Vfarms is building an Agriculture-to-Energy platform that connects the complete agricultural value chain with multiple energy and value-add pathways. We work from the farm level through Precision Farming, energy-crop cultivation and biomass development, followed by feedstock aggregation, logistics and value addition. We then connect these resources to suitable energy pathways such as CBG, bioenergy and bioethanol, supported by process innovation and Digital Operations Infrastructure including SCADA, ERP and Carbon MRV systems. This integrated approach enables better resource utilisation, reliable supply, operational efficiency and scalable agriculture–energy projects Vfarms combines deep agricultural ground knowledge with Precision Farming, process innovation and technology-enabled operations. Our approach starts with the agricultural ecosystem rather than a single energy technology — covering cultivation, energy crops, biomass development, aggregation, logistics and value creation, and connecting them to multiple energy pathways. Our Digital Operations capabilities, including SCADA integrations, ERP rollouts and Carbon MRV systems, add a technology and operational layer that improves efficiency, traceability and scalability. This is further strengthened by our understanding of operations and execution, energy-market demands and requirements, and the ability to integrate these capabilities into a single Agriculture-to-Energy platform that is difficult to replicate quickly MVP Our primary customers are energy companies, CBG and bioenergy project developers, industrial users of renewable gas and biomass, and organisations looking for reliable agricultural feedstock and energy solutions. We also work with farmers, landowners, aggregators and other agricultural ecosystem partners who form the supply side of the Agriculture-to-Energy value chain ₹50,000+ Crore ₹10,000 crore ₹100–300 crore Vfarms follows a multi-stream B2B revenue model across the Agriculture-to-Energy value chain. Revenue will come from agricultural and energy-crop development, feedstock supply and aggregation, biomass/value-added products, project development and operational support for bioenergy projects, and technology-enabled services such as SCADA integration, ERP/digital operations and Carbon MRV. As the platform scales, Vfarms can also participate in long-term supply and strategic partnerships with CBG, bioenergy and other energy-sector players. Vfarms operates across multiple parts of the Agriculture-to-Energy value chain, so competition is fragmented rather than concentrated in a single category. Our competitive landscape includes CBG/bioenergy project developers, biomass and feedstock aggregators, energy-crop companies, agricultural technology and Precision Farming providers, and digital/operational technology providers. However, most players focus on one part of the value chain. Vfarms aims to differentiate by integrating agricultural expertise, farm-level execution, feedstock and biomass, energy-market understanding, process innovation and digital operations into one Agriculture-to-Energy platform. We don't compete with one company across the entire value chain. Vfarms is building an integrated capability across these traditionally fragmented layers Vfarms follows a B2B, relationship-driven customer acquisition model. We build relationships directly with CBG and bioenergy project developers, energy companies, industrial users, farmers, landowners, aggregators and other ecosystem partners. Customer acquisition is driven through strategic partnerships, industry networks, project-based engagements, pilot projects and on-ground agricultural relationships. As we demonstrate capability through successful projects, we aim to convert these relationships into long-term supply, operations and technology partnerships.** Vfarms will follow a phased, B2B and partnership-led go-to-market strategy. We will initially focus on selected agricultural regions and establish Vfarms Excellence Centres as on-ground hubs for agricultural research, Precision Farming, energy-crop development, demonstrations and farmer/landowner engagement. From these centres, we will build relationships with farmers, landowners, aggregators and other agricultural partners, while simultaneously engaging CBG, bioenergy and industrial customers to understand their requirements. We will start with pilot projects and targeted partnerships, demonstrate our Agriculture-to-Energy capabilities on the ground, and then scale through long-term supply, project development, operations and technology partnerships. Our long-term vision is to build Vfarms as a scalable Agriculture-to-Energy platform contributing to India’s energy transition and economic growth. We aim to connect India’s agricultural resources with multiple energy and value-add pathways. Over time, we want to create circular agriculture–energy systems that generate value for farmers, strengthen rural economies, contribute to energy security and support India’s energy transition towards Net Zero. Yes We believe IITACB can help us bridge agriculture, energy, technology and commercialisation through its ecosystem, networks and industry connections, while providing access to the right mentors, technical expertise and strategic partnerships needed to develop and scale Vfarms’ Agriculture-to-Energy platform across India. to connect investors and mentors with expertise in Agriculture, Renewable Energy, Bioenergy, ClimateTech and Rural Infrastructure, who can bring not only capital and strategic guidance, but also industry expertise, technology capabilities, market access and partnerships to help scale Vfarms’ Agriculture-to-Energy platform across India. YES We can leverage the Bengaluru industrial ecosystem to identify energy and biomass requirements, develop B2B partnerships, and explore multiple Agriculture-to-Energy opportunities such as CBG, biomass pellets, other bioenergy pathways and carbon-credit opportunities. Yes We would like to use IITACB’s infrastructure as a base for developing and coordinating Vfarms’ Agriculture-to-Energy initiatives. We aim to leverage the workspace and meeting facilities for collaboration with mentors, industry partners, technology providers and potential customers, while using the incubator ecosystem to support research, technology validation, project development and business development Yes Supporting feature 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/lUa7hqOI1abx-Vfarms_Connecting_Agriculture_with_Energy.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/lUa7hqOI1abx-Vfarms_Connecting_Agriculture_with_Energy.pdf Vfarms is building an impact-focused Agriculture-to-Energy platform with a mission to connect India’s agricultural strength with its energy transition. We aim to create additional economic opportunities for farmers and rural communities by connecting agricultural resources, energy crops and biomass with emerging energy and value-added pathways such as CBG, biomass and other bioenergy solutions. Our impact extends beyond energy. Through Precision Farming, process innovation and technology-enabled operations, we aim to improve resource efficiency, create rural employment and entrepreneurship opportunities, and bring rural communities into the emerging energy economy. By developing circular agriculture–energy systems, including opportunities for by-product utilisation and carbon management, Vfarms aims to contribute to India’s energy security, cleaner energy transition and long-term Net Zero goals. Our mission is to make agriculture an active participant in India’s energy transition while creating sustainable economic, social and environmental value. RaviTeja checked
Aug 13, 2026 @ 4:45 PM UMESH SANGLE nuviatechdevices@gmail.com https://linkedin.com/company/nuviatech https://www.nuviatechdevices.com/ +919769692684 Umesh Sangle – Co Founder and CEO: Leads business strategy commercialization partnerships fundraising and market development. He brings a strong medtech innovation and entrepreneurial background with experience translating healthcare problems into scalable medical device solutions. Anand Janunkar – Co Founder and CTO: Leads product engineering R and D manufacturing and technical development. He brings strong experience in medical device design prototyping product development and translating clinical requirements into affordable manufacturable healthcare technologies. Together the founders combine business execution product engineering clinical collaboration and commercialization capabilities required to build and scale Nuviatech. Umesh and Anand met during their association with BETiC, IIT Bombay, where both were involved in medical device innovation and translational product development. Their shared interest in solving real-world healthcare challenges, particularly through affordable and accessible MedTech, led them to collaborate closely on product design, prototyping, clinical feedback, and validation activities. Over time, their complementary strengths—Umesh in mechanical engineering, product strategy, and commercialization, and Anand in electronics, embedded systems, and product development—formed the foundation for Nuviatech Devices. They have worked together for over three years and continue to collaborate closely in person 2 Our biggest strength is the complementary expertise across technology, business, clinical care, and commercialization within the team. Umesh Sangle brings product engineering, quality systems, business strategy, and market execution; Anand Janunkar leads electronics, embedded systems, product design, and technical development. Dr. Rupesh Ghyar adds deep MedTech commercialization, regulatory, and strategic experience; and Dr. Sanjay Aher brings frontline neonatology expertise and clinical validation. Together, we cover the full MedTech journey—from identifying unmet clinical needs and building the product to validating it, navigating regulation, and scaling adoption—while staying focused on affordable and accessible neonatal care. NUVIATECH DEVICES PRIVATE LIMITED https://www.nuviatechdevices.com/ MUMBAI Nuviatech Devices is a medtech startup building an integrated portfolio of affordable, accessible and indigenous neonatal medical devices. Our hero product NuviaGlow addresses neonatal jaundice through advanced phototherapy, followed by NuviaWarm for neonatal thermal care and a growing pipeline of technologies addressing critical newborn-care needs. Our vision is to build a comprehensive neonatal care platform designed for hospitals across India and emerging markets. Millions of newborns require timely intervention for conditions such as neonatal jaundice, hypothermia and other complications, yet access to quality neonatal equipment remains unequal. Conventional neonatal devices can be expensive, bulky, infrastructure-dependent and concentrated in well-equipped hospitals, creating significant challenges for smaller hospitals and resource-constrained healthcare facilities. This can lead to delayed treatment, referrals, increased cost of care and preventable complications. Nuviatech is addressing this accessibility gap by building affordable neonatal technologies designed around real clinical needs and the operating realities of Indian healthcare facilities. Nuviatech is building a portfolio of affordable and clinically relevant neonatal medical devices that brings essential newborn care closer to the point of need. Our hero product NuviaGlow is an advanced neonatal phototherapy solution designed to provide effective treatment for neonatal jaundice while improving affordability, portability and ease of deployment. NuviaWarm extends our platform into neonatal thermal care by addressing hypothermia and temperature stabilization. Our broader product pipeline is being developed to address additional critical neonatal-care needs, creating a unified portfolio rather than a single-product company. Our solutions are developed through clinician-led need identification, indigenous engineering and iterative validation, with a strong focus on clinical performance, affordability, usability and manufacturability. Through this platform approach, Nuviatech aims to equip NICUs, SNCUs, maternity centres, district hospitals and resource-constrained facilities with high-quality neonatal technologies designed for India and scalable to other emerging markets. Nuviatech's differentiation lies in building an integrated neonatal technology platfoProduct-Market Fitrm specifically around the clinical and economic realities of emerging healthcare systems. Rather than competing through a single device, we are developing a complementary product portfolio led by NuviaGlow for neonatal jaundice and NuviaWarm for thermal care, creating opportunities for deeper hospital relationships and portfolio-based expansion. Our competitive advantage combines clinician-driven product development, indigenous engineering, affordability, portability, ease of use and design for scalable local manufacturing. Continuous engagement with neonatologists and healthcare stakeholders enables us to translate unmet clinical needs into practical products. Our defensibility is further strengthened through product engineering know-how, regulatory progress, intellectual property development, clinical partnerships and an expanding neonatal product pipeline. MVP Pilots Our target customers are NICUs, SNCUs, government hospitals, medical colleges, private maternity hospitals, pediatric hospitals, children’s hospitals, neonatal-care centres, ambulance / transport-care providers, NGOs, CSR healthcare programs, and distributors supplying neonatal medical equipment. We are initially focusing on hospitals and newborn-care centres in Maharashtra, Gujarat and high-burden Indian states where affordable, portable and reliable neonatal jaundice and hypothermia-care solutions are urgently needed. ₹7,000–11,000 Cr+ in India, covering neonatal phototherapy, neonatal warming, infection-prevention consumables and integrated newborn-care devices across government hospitals, private hospitals, NICUs, SNCUs, maternity hospitals and pediatric-care networks. ₹1,500–2,500 Cr, representing the reachable Indian market across NICUs, SNCUs, medical colleges, government hospitals, private maternity hospitals, pediatric hospitals, children’s hospitals and distributor-led neonatal equipment channels. ₹25–50 Cr in the next 3 years, based on Nuviatech’s phased deployment plan across priority states, early hospital adoption, distributor-led sales, recurring consumables, AMC/service revenue and 300 → 700+ → 1,500+ cumulative device deployment targets. Nuviatech follows a device + consumables + service revenue model. Revenue will come from direct device sales of NuviaGlow and NuviaWarm, recurring sales of sterile disposable NuviaShield sleeves, AMC/service contracts, distributor-led sales, institutional deployments, CSR/government-supported procurement and future licensing / white-label opportunities for related warming and neonatal-care technologies. Our competitors include existing neonatal phototherapy and warming equipment providers such as GE Healthcare, Natus/BiliSoft, Phoenix Medical Systems, Fanem, Nice Neotech and other Indian neonatal equipment manufacturers. However, Nuviatech differentiates through portable, affordable, baby-friendly, intensive phototherapy and smart warming devices with integrated safety monitoring, consumable revenue model, India-focused pricing and compliance-ready product development. We acquire customers through clinical validation, neonatologist engagement, hospital demonstrations, early pilot deployments, distributor partnerships, medical conferences, pediatric and neonatal networks, incubator and ecosystem referrals, CSR healthcare networks, government / institutional procurement channels and direct engagement with hospital administrators and biomedical teams. Our early adoption strategy focuses on proving clinical usability, safety, ROI and operational value inside hospitals before scaling through distributor-led expansion. Our GTM strategy is phased. In Phase 1, we will deploy initial units in selected hospitals and neonatal-care centres for early commercial validation, clinical feedback and customer adoption. In Phase 2, we will scale through distributors across Maharashtra, Gujarat and other priority states, supported by hospital demonstrations and neonatal-care networks. In Phase 3, we will expand through multi-state distribution, government / CSR partnerships, AMC/service support, recurring consumables and future CE/FDA readiness for international markets. Nuviatech’s long-term vision is to build India’s Essential Neonatal Care Platform — an affordable, portable and globally competitive medical-device platform for neonatal jaundice, hypothermia, infection prevention and integrated newborn care. We aim to make critical newborn-care technologies accessible beyond advanced NICUs, reaching district hospitals, maternity centres, pediatric hospitals, transport care and underserved regions. Our goal is to become a trusted Indian medtech company with scalable devices, recurring consumables, strong clinical validation and global market readiness. Nuviatech Devices Pvt. Ltd. is a legally incorporated private limited company registered in India. CIN: U26600MH2025PTC442175 The company is DPIIT-recognized and is building affordable neonatal medical devices focused on jaundice, hypothermia, infection prevention and integrated newborn care. Nuviatech has secured ₹47+ lakhs through non-dilutive grants and awards Yes We are applying to IITACB Incubator to access a strong ecosystem of IIT alumni, mentors, industry leaders, investors, corporate partners and commercialization networks. Nuviatech has already completed a rapid journey from idea to validation, POC, MVP, NABL safety testing, regulatory pathway and manufacturing licence progress within 16 months. We are now entering the GTM and commercialization stage, where IITACB’s mentoring, investor access, industry connects, workspace, strategic guidance and Bangalore ecosystem can help us scale faster and more effectively. During the programme, we aim to strengthen our GTM strategy, refine investor readiness, build hospital and distributor partnerships, access strategic mentors, improve commercialization planning, and accelerate fundraising for our first institutional round. We also want to leverage IITACB’s ecosystem to support early customer acquisition, manufacturing partnerships, regulatory and quality guidance, and expansion into Bangalore and South India healthcare markets. Yes. We are open to virtual participation and can actively engage in mentor sessions, investor connects, pitch reviews, workshops, and programme activities online. We are also willing to travel to Bangalore for important in-person meetings, demo days, investor sessions, strategic discussions and ecosystem networking whenever required. Bommasandra and Bangalore provide a strong advantage for Nuviatech because of the presence of healthcare institutions, medtech companies, electronics manufacturers, precision engineering vendors, quality-system experts, hospitals, investors and corporate innovation networks. We can leverage this ecosystem for manufacturing partnerships, vendor development, product refinement, pilot deployments, hospital connects, distributor partnerships and strategic collaborations. IITACB can help us by enabling mentor access, investor introductions, corporate and hospital connects, industry partnerships, workspace support, pitch refinement, fundraising guidance and connections with relevant medtech, electronics, healthcare and manufacturing stakeholders in Bangalore. Yes We would use IITACB infrastructure as a strategic base for investor meetings, mentor discussions, pitch preparation, product demonstrations, partner meetings, business development, GTM planning and networking with IIT alumni, corporates and industry stakeholders. The workspace would help us maintain a structured Bangalore presence while exploring hospital partnerships, manufacturing/vendor connects, distributor networks and fundraising opportunities. This support can help Nuviatech move faster from validated innovation to commercial deployment and scale-up. Yes Supporting feature Nuviatech’s product architecture combines a medical-grade applied pad, smart controller, embedded firmware, sensor feedback, safety monitoring and regulated power architecture. For NuviaGlow, the system includes a flexible phototherapy pad with 460–465 nm blue LEDs, smart controller, low/medium/high intensity modes, skin-temperature probe, OLED display, audio-visual alerts and fault-handling logic. The system is designed to deliver high-intensity phototherapy while monitoring safety parameters. For NuviaWarm, the architecture includes a flexible silicone heating pad, smart controller, auto/manual modes, closed-loop skin-temperature feedback, over-temperature protection, probe/pad disconnection detection and audio-visual safety alerts. Both devices are designed as Class B medical devices, with Type BF applied part, Class II electrical protection, USB-C PD power architecture, embedded firmware, safety cut-off logic and use of approved accessories / disposable protective sleeves. Nuviatech has built a strong proprietary knowledge base through 100+ interactions with neonatologists, pediatricians, hospitals, NICU/SNCU teams, biomedical engineers and healthcare stakeholders. This includes insights on clinical workflow, usability gaps, device adoption barriers, phototherapy treatment practices, neonatal warming needs, safety concerns, hospital procurement expectations and field deployment requirements. As we begin pilot deployments and clinical validation, we expect to generate proprietary real-world data on device usability, treatment workflow, temperature monitoring, usage patterns, consumable adoption, safety alerts, service needs and hospital ROI. This will help improve product design, clinical evidence, AI/analytics readiness and future connected neonatal-care solutions. Nuviatech is defensible because it combines clinical validation, regulatory readiness, cost advantage, product design, safety-first engineering, IP activity and platform expansion. Unlike conventional bulky neonatal equipment, Nuviatech is building portable, affordable and baby-friendly devices designed for Indian hospitals, small children’s hospitals, maternity centres, SNCUs and resource-constrained settings. Our flagship NuviaGlow has achieved high-intensity phototherapy performance up to 75 µW/cm²/nm, while also integrating skin-temperature monitoring and safety alerts. Our defensibility comes from: India-focused affordability and portability Strong clinical validation with 100+ stakeholders NABL-accredited safety and compliance testing passed in first attempt CDSCO regulatory pathway and manufacturing licence progress Patent activity and platform roadmap Device + consumables + service business model Early customer interest and hospital deployment readiness Multi-product neonatal care platform, not a single-device approach We evaluate performance and reliability using measurable medical-device parameters such as phototherapy irradiance, wavelength accuracy, treatment coverage, temperature monitoring, alarm response, fault handling, electrical safety, EMC performance, usability, durability, power stability and continuous operation. For NuviaGlow, the key benchmark is blue-light phototherapy performance at 460–465 nm, adjustable intensity modes and maximum irradiance up to 75 µW/cm²/nm, which positions it strongly against benchmark global phototherapy devices. For NuviaWarm, we evaluate controlled warming performance through set temperature range, closed-loop skin feedback, over-temperature protection, pad performance and safety alarm handling. Both products have undergone NABL-accredited safety and compliance testing against global-level equivalent medical electrical safety standards, including IEC 60601 series requirements, and passed in the first attempt. This validates product robustness, safety and reliability compared to existing conventional and imported systems. Current Nuviatech devices are primarily embedded medical devices and do not depend on cloud-based patient data storage for core functionality. Patient safety is handled locally through embedded firmware, sensor feedback, audio-visual alerts and safe-state shutdown logic. For data privacy and compliance, we follow a minimum-data approach. Any future connected features will be designed with consent-based data collection, anonymization, controlled access, secure storage, auditability and compliance with applicable Indian data protection and medical-device requirements. On the product compliance side, we follow medical-device quality and regulatory expectations, including design documentation, risk management, traceability, validation records, IEC 60601 safety standards, labeling / IFU control and CDSCO-aligned regulatory documentation. Yes. Nuviatech benefits from India’s growing policy focus on Make in India medical devices, affordable healthcare, neonatal and maternal-child health, reduction of import dependency, public-health innovation, startup grants, medtech incubation and government-supported healthcare procurement. Relevant policy tailwinds include CDSCO medical-device regulation, public-health focus on newborn survival, Ayushman Bharat / PM-JAY hospital reimbursement ecosystem, Make in India / Atmanirbhar Bharat, Startup India, DPIIT recognition, medtech incubation programs, grant schemes and CSR focus on neonatal and rural healthcare. These interventions support indigenous medical-device innovation, hospital adoption and scale-up. Yes, as with all medical devices, regulatory risk exists. Key risks include delays in CDSCO approval, changes in device classification, additional testing requirements, clinical validation requirements, labeling / IFU updates, quality-system documentation requirements, post-market surveillance expectations and manufacturing compliance requirements. However, Nuviatech has actively de-risked these areas by following the CDSCO regulatory pathway, working with a manufacturing ecosystem aligned with ISO 13485 quality systems, completing NABL-accredited safety and compliance testing, preparing technical documentation, and engaging with clinical and regulatory stakeholders. We treat regulatory compliance as a core part of product development, not as an afterthought. At 10x scale, the key pressure points will be manufacturing capacity, vendor reliability, component procurement, quality control, service infrastructure, installation support, distributor training, working capital, inventory planning, field maintenance and documentation control. To address this, we are building a scalable operating model with multi-vendor sourcing, manufacturing partner support, documented quality processes, service SOPs, training material, distributor onboarding, planned inventory buffers, AMC/service workflows and milestone-linked fundraising. Our immediate funding plan is designed specifically to strengthen working capital, manufacturing readiness, team expansion and deployment capability before large-scale rollout. Yes. Nuviatech has an in-house founding and technical team with expertise in medical-device development, electronics, embedded systems, firmware, mechanical design, thermal systems, optical phototherapy systems, product validation, prototyping, regulatory documentation and manufacturing coordination. The founders have experience from the BETIC IIT Bombay medtech ecosystem and have worked across product development, electronics, mechanics, clinical validation, firmware logic, safety architecture, medical-device testing and commercialization readiness. We are also supported by clinical mentors, manufacturing partners and medtech advisors to strengthen regulatory, quality, clinical and commercialization execution. Nuviatech’s products are primarily embedded medical-device systems and do not currently depend on third-party patient datasets or open-source AI models for core functionality. The product design, embedded control logic, safety workflow, system architecture, mechanical design, clinical workflow learnings and application-specific firmware are internally developed / owned by Nuviatech, subject to final IP filings and documentation. We use standard commercially available electronic components, sensors, LEDs, power components, displays, cables and medical-grade materials sourced through vendors. Any third-party components are used under standard commercial procurement terms. We have 1 patent submitted and 3 additional IP areas under development related to neonatal phototherapy, warming and integrated newborn-care technologies. We will continuously improve performance through hospital feedback, clinical validation, usability studies, service reports, safety-event analysis, manufacturing feedback, quality audits, component-level testing, software/firmware updates, design refinements and post-market surveillance. For NuviaGlow, improvement focus areas include treatment-area coverage, irradiance uniformity, LED thermal management, usability, alarm logic and workflow integration. For NuviaWarm, focus areas include thermal stability, closed-loop feedback, warming uniformity, patient comfort, safety alerts and reliability. We also plan to build future connected features, data-driven monitoring, improved accessories and next-generation integrated newborn-care products based on real-world deployment learnings. We are building for India first, with global readiness. Our first priority is to address India’s urgent neonatal care gap across government hospitals, SNCUs, NICUs, maternity hospitals, pediatric hospitals and smaller healthcare centres. At the same time, the problem is global across emerging markets where affordable neonatal jaundice and hypothermia care is needed. Our products are being developed with IEC 60601-aligned safety standards, CDSCO regulatory pathway, ISO 13485 manufacturing ecosystem and future CE / FDA readiness in mind. The long-term vision is to build an Indian neonatal medtech platform that can scale across India and later expand to global emerging healthcare markets. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/EtKjVe0GnhUH-NUVIATECH-DEVICES-PRIVATE-LIMITED_PITCH.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/EtKjVe0GnhUH-NUVIATECH-DEVICES-PRIVATE-LIMITED_PITCH.pdf Yes. Nuviatech Devices Pvt. Ltd. is a mission-driven medtech startup building India’s Essential Neonatal Care Platform to make critical newborn-care technologies accessible, affordable and portable. We are focused on solving urgent neonatal challenges such as jaundice, hypothermia, infection prevention and integrated newborn care. India has one of the world’s largest newborn populations, yet access to timely neonatal care is still limited outside advanced NICUs. Nuviatech aims to bridge this gap through India-made, regulatory-aligned devices such as NuviaGlow for neonatal jaundice, NuviaWarm for thermoregulation, and NuviaShield as a high-volume consumable for hygiene and infection prevention. In just 16 months, we have progressed from idea validation with 100+ stakeholders to POC, MVP, product development, patent activity, NABL safety testing, CDSCO regulatory pathway, manufacturing licence progress and commercialization readiness. Our goal is to improve access to essential neonatal care across hospitals, maternity centres, pediatric hospitals, SNCUs, smaller clinics and underserved regions. Nuviatech is a founder-led early-stage medtech startup working from the Indian healthcare innovation ecosystem. While we may not specifically claim underrepresented status, we are building for underserved newborns, smaller hospitals and resource-constrained healthcare settings where access to advanced neonatal care is limited. DR. RUPESH GHYAR Nuviatech has achieved a rapid and capital-efficient medtech execution journey. In just 16 months, we have moved from idea to validation, POC, MVP, product development, clinical feedback, patent activity, NABL-accredited safety testing, CDSCO regulatory pathway, manufacturing licence progress and commercialization readiness. Key highlights include: 2 market-ready products: NuviaGlow and NuviaWarm 1 high-volume consumable: NuviaShield 2 pipeline products: NuviaGlow Lite and Sparsh 360 100+ neonatologists, hospitals and healthcare stakeholders engaged ₹47+ lakhs grants and awards secured ₹45 lakhs founder capital invested ₹92+ lakhs total capital deployed / committed so far 1 patent submitted and 3 IP areas under development NABL safety and compliance testing passed in first attempt Commercialization planned in the coming months We are now looking for incubation support, investor access, strategic mentoring, GTM guidance, hospital / distributor connects, fundraising support and Bangalore ecosystem access to scale Nuviatech from validated innovation to commercial deployment. checked
Aug 13, 2026 @ 1:31 AM Shubham Sharma shubham.sharma@sunitechai.com http://www.linkedin.com/in/ssharma-ai https://sunitechai.com/ +919415410131 Founder | 10+ years data science expertise — IIT Dhanbad & SUNY Buffalo pedigree. NA 1 Shubham is from the very industry he aims to serve, fused with a profound expertise in building lasting customer relationships. His extensive 10+ year journey in data science and AI, from earning his Master's at SUNY Buffalo to solving complex data challenges at Baker Hughes and Quickbase, gives him a profound understanding of the skills the industry demands. With experience moderating sessions for MIT professors and mentoring countless professionals, he has a proven ability to make complex topics accessible and engaging. His IIT (ISM) Dhanbad roots ground him in India's top-tier engineering ecosystem. SunitechAI https://sunitechai.com/ Bengaluru SAGEMIND is an AI co-pilot for educators. It helps educators instantly build 1-on-1 interactive learning mapped to real-world employability. Passive learning fails students; interactive learning bankrupts creators. Faced with this friction, creators default to passive text and video, which actively harms learner outcomes and creator revenue: * Prohibitive Production Costs: Building just one hour of highly interactive, scenario-based eLearning takes between 80 and 400 hours of production time. * Unsustainable Financial Burden: Custom, highly interactive educational content currently costs well over $20,000 per finished hour of learner seat time. * Dismal Learner Retention: Because creators are forced to use passive text and video to save money, median online course completion rates sit at a catastrophic 12.6%. SAGEMIND is an AI powered platform that automatically architects deterministic, code-backed visuals, from dynamic flowcharts to parameter-driven simulators, based purely on instructor prompts. This reduces interactive course production time from weeks to seconds, scaling high-end pedagogy at 10x the speed. It shifts students from passive video consumers (15% average course completion) to active system debuggers by interactive evaluations. The focus is on one-to-one learning for the learner, increasing learner's engagement by offering adaptive activities for learners which can be designed easily by the instructor. It aims to be a career partner, showcasing what to focus on for immediate employability, durable competence * Research confirms that learners consuming passive instruction (video/text) forget up to 90% of the material within a single week. Transitioning to interactive, 3D visual environments significantly improves spatial understanding and long-term memory consolidation compared to traditional, passive instruction. Also, Industry benchmarks state that developing one hour of advanced, highly interactive eLearning traditionally requires between 184 and 267 hours of labor. SAGEMIND's automated AI architecture reduces this multi-week bottleneck to minutes and such a solution doesn’t exist in the market. SAGEMIND’s Advantage is that it merges instant AI generation with deep, interactive, zero-hallucination visual learning environments. MVP Users Data Science and AI upskilling content creators, STEM educators relying heavily on systems, architectures, and data flows. $ 236 B $10 B $ 36 M B2B2C SaaS with scalable, usage-based pricing across creator and enterprise tiers. No direct competitor exists Initial Customers will come from an exclusive invite strategy only for selected educators to try the platform Product-led growth through visual embed virality, Target tech bootcamps with pilot programs proving curriculum cost- savings. SunitechAI's vision is to empower every learner to master data and AI through immersive, affordable and visually engaging education built in India, for the world. The skills requirement is changing rapidly across all industries and there is a burning requirement for up-skilling and ed-tech industry to keep pace with it. SunitechAI envisions to lead the charge in the ed-tech industry by making AI powered education mainstream which has the potential of creating a deep impact on learner outcomes. Incorporated an LLP None Yes To get guidance, mentorship and the seed capital I wish to work together with IITACB to bring our platform to the leading institutes in our country. We wish to iterate fast as per the feedback received. We also wish to get guidance from professors to understand their point of view wrt to usage of AI in education and how can this be leveraged to improve learner outcomes. Yes We need to build a team and the IITACB centre is very well positioned as our first address. The best market for us in India would be Bangalore which is full of tech professionals looking to upskill. This would provide us massive data to understand the customer pain points and build SAGEMIND as a learner's go-to platform with time. Also, we wish to conduct workshops/ seminars on AI for which IITACB centre is very much suitable for us. We have already conducted 1 such workshop in collaboration with ACSEL. Yes This will be primarily used as our first address for our Team. Yes Core engine Langgraph, AWS, Javascript, ReactFlow, Excalidraw, Mermaid, Manim animations, d3.js I have been mentoring professionals since past 6 years and have deep insights in the upskilling industry. We also have current usage data for SAGEMIND. SAGEMIND has been live since 3 months in beta and has 50 active users. Early mover advantage, only focused on one-niche - Data Science, AI, STEM Our platform is as per industry standards, appropriate observability and governance is implemented We are fully compliant with respect to these aspects adhering to industry best practices. We use AWS which itself has appropriate guardrails and security perimeters. No None existing currently Our platform is designed to scale. Currently, I am the lead developer. 10+ years data science expertise — IIT Dhanbad & SUNY Buffalo pedigree. Built advanced AWS anomaly detection tools for Quickbase, Boston. Engineered complex data science & AI solutions for global O&G leader Baker Hughes. Moderates live technical sessions with MIT professors; mentors professionals. I have also been a Lead AI engineer at Toptal We use Langgraph which is an open source library We plan to onboard users and use live usage data as feedback to refine the platform Both 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/ruTY3h8BTZLY-Pitch-Deck-SAGEMIND.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/ruTY3h8BTZLY-Pitch-Deck-SAGEMIND.pdf SAGEMIND has a deep potential for massive impact in the education sector. Our primary focus is better learner outcomes & 1-to-1 mentoring and that is why we are different from any other AI platform. No NA SunitechAI is the umbrella company under which SAGEMIND is being developed. checked
Aug 12, 2026 @ 11:20 PM Vijay Anand vijayanand@regencyops.com https://www.linkedin.com/in/vijay-anand-917ba476/ http://www.regencyops.com 917760774411 Founder & CEO. 30-year IT career across India, the US, and the Netherlands. Former Group Project Manager at HCL Technologies — the exact enterprise IT-operations domain Stratos serves. Credentials: IIT Kanpur, ISB Hyderabad, University of Wales. Solo Founder 1 Deep domain expertise: ITIL V3 Expert with 30 years in enterprise IT operations management (ITOM) combined with hands-on execution speed — a solo founder who has independently designed, built, and shipped four production-grade products and filed two patents within months of starting, using AI-assisted development to move at a pace typically requiring a full engineering team RegencyOps https://regencyops.com Bengaluru, India A patented causal-correlation engine that reconciles conflicting signals from Datadog, PagerDuty, Grafana and 7+ tools into one consensus incident view — alert to root cause to action in under 2 minutes. Enterprise IT operations teams are drowning in disconnected alerts from multiple monitoring tools. When an incident hits, engineers waste critical time manually correlating signals across dashboards instead of fixing the actual problem — extending downtime and increasing business impact.Detection is solved; understanding is not. Datadog, Grafana, and PagerDuty raise alerts in seconds, but engineers still spend 30-90 minutes piecing together meaning across 7+ disconnected tools. No single pane of glass exists — signals, business impact, data flow, architecture, infra, and runbooks each live in a different tool. Downtime is expensive: ~$1,840/min lost in a real worked example, plus SLA breaches and thousands of blocked users. An 8-layer causally-linked incident glass pane (monitoring → business workflow → data flow → application → architecture → infrastructure → user/financial impact → action) that auto-assembles when an incident fires and lights the failing layer in red. Read-only, sits above the existing stack (no rip-and-replace), setup under 20 minutes. Plain-English business/financial layers mean L1/L2 engineers can act without waiting for an SRE. Stratos ingests and normalizes alerts from tools like Grafana and Jira, correlates related signals into a single incident view, and uses causal inference (Fault Tree/Bayesian DAG analysis) plus LLM-based synthesis to surface likely root causes — cutting the manual triage time that currently falls entirely on engineers. 30 years of hands-on enterprise ITOM experience (HCL, Infosys),ITIL V3 Expert means the founder has lived the exact problem Stratos solves, and has built a canonical cross-vendor correlation schema that compounds in value as it's exposed to messier real-world environments — something cloud-native-only competitors structurally avoid. Incumbent vendors (Datadog, PagerDuty) are also disincentivized from building neutral, cross-vendor correlation since it undermines their own platform lock-in.Filed patents (202641060485 — Multi-Layer Incident Intelligence) and published MVP Mid-to-large enterprise IT operations teams running multi-vendor monitoring stacks (Grafana, Datadog, PagerDuty, Jira, etc.) — particularly organizations with complex, messy hybrid/multi-cloud environments where alert noise across tools is a daily operational pain point. Global observability/incident-management market — $17B growing to $73B. Mid-market companies needing L1/L2 incident tooling. India + APAC — mid-market design partners in the first 3 years Pilot value of $299/month and with Tiered SaaS subscription: Starter ($3,000/month, up to 5 integrations, 500 incidents/month), Professional ($8,000/month, up to 15 integrations, 2,000 incidents/month), Enterprise ($20,000+/month, unlimited integrations/incidents + SLA). igPanda, Dynatrace Davis (correlation/AIOps layer); Rootly, incident.io, FireHydrant (coordination/postmortem); PagerDuty, Opsgenie, ilert (alerting/on-call); Datadog, Grafana, SigNoz (detection/observability) — all of these feed Stratos as read-only data sources rather than competing directly at the "understanding" layer. Low-friction self-serve onboarding (setup under 20 minutes, read-only, no rip-and-replace) keeps CAC low; sticky daily-use tooling drives high LTV-to-CAC. Land 2-3 mid-market design partners in India + APAC first, converting paid pilots to annual subscriptions, before broader expansion. A repeatable SaaS engine built on a patented, category-defining product, scaling from a regional India base to the UK and global mid-market — with the same orchestration IP already reused once (powering Intelligent Workspace) extending into this new category. 3-year indicative revenue: $30K → $108K → $290K. RegencyOps (OPC) Private Limited, 16 May 2026, Bengaluru. CIN: U85499KA2026OPC221057. DPIIT Startup recognised, Udyam MSME registered. 0 Yes As an IIT Kanpur alumnus, IITACB offers direct access to a curated investor network, structured pitch coaching, and peer accountability through the cohort structure — exactly what's needed to convert Stratos from a working MVP (TRL 5, patent published) into a funded, design-partner-validated product. The Bengaluru location also puts us physically close to the enterprise IT/ITOps customer base Stratos targets. Sharpen the investor pitch, get direct feedback from VCs/angels on the $250K raise, and ideally secure introductions to 2-3 mid-market enterprises who could become Stratos design partners — the single biggest unlock for the product right now. Yes Bengaluru's dense concentration of enterprise IT, ITOps, and SaaS companies is precisely the customer base Stratos is built for — being embedded in that ecosystem shortens the path to design partners and pilot customers. IITACB's alumni/mentor/investor network can provide warm introductions into that base far faster than cold outreach alone. Yes Primarily for structured mentor access, investor-facing meeting space for design-partner and pitch conversations, and proximity to the IIT alumni/industry network for warm customer and investor introductions — less for day-to-day building, since RegencyOps is currently a solo, remote-capable technical operation. Yes Core engine A five-stage pipeline: (1) ingest/normalize alerts from connected tools (Grafana, Jira, with Datadog/PagerDuty/ServiceNow/CloudWatch planned), (2) correlate related signals across sources, (3) causal inference using Fault Tree/Bayesian DAG analysis to identify the failing layer, (4) semantic retrieval against a knowledge-error-database (KEDB) using vector/embedding-based search, (5) synthesis and plain-English narration via the Claude (Anthropic) API. Backend currently on Firebase/Firestore; read-only integration model — no write access to customer production systems. None yet — pre-design-partner stage. The intended long-term moat is a canonical cross-vendor correlation corpus that compounds as it's exposed to real, messy multi-vendor environments — something incumbent single-vendor players are structurally unlikely to build. This advantage has to be earned through design-partner usage, not claimed in advance. 1) Filed IP — one patent already proven to ship commercially. (2) Read-only, above-the-stack architecture — low switching cost/risk for customers, unlike incumbents. (3) Incumbents' innovator's dilemma — Datadog/PagerDuty are commercially disincentivized from building neutral cross-vendor correlation since it undermines their own platform lock-in. (4) 30 years of founder domain experience in enterprise ITOM. Not yet benchmarked against competitors — honest current status. Target internal metric once live: alert-to-root-cause time under 5 minutes (vs. the 30-90 minutes typical of manual multi-tool triage today). Formal benchmarking is planned as part of the design-partner validation phase. Read-only architecture by design — Stratos never requires write access or production credentials, which meaningfully limits blast radius if compromised. No customer production data is currently processed since the product is pre-design-partner; formal compliance posture (SOC2, data residency, etc.) will be built out ahead of first paid design partner, not retrofitted after. DPIIT Startup recognition (tax benefits, IP fast-track — already used for Form 18A expedited patent examination) and Udyam MSME registration. Data privacy regulation (India's DPDP Act, and GDPR if/when expanding to the UK as planned) given the product touches enterprise operational and, indirectly, customer-impact data. Being read-only reduces but doesn't eliminate this exposure. Honestly — the current Firebase/Firestore backend isn't architected for high-throughput real-time correlation at enterprise alert volumes; it would need to move toward a proper event-streaming architecture (e.g. Kafka-style) well before 10x scale. The causal inference engine's latency under high concurrent alert volume is also unvalidated at scale — this is explicitly a "next to build," not a solved problem. No — solo founder currently. Planned hires (per the pitch deck's use-of-funds) are AI/full-stack engineers, to be brought on as the raise closes. Anthropic's Claude API (licensed, commercial API use), standard Fault Tree/Bayesian DAG causal-inference methodology (established open technique, not a licensed dataset), official Grafana and Jira APIs (licensed per their terms). No proprietary or third-party datasets currently in use — patent filings (202641060485) are the owned IP. Primarily through design-partner feedback loops once onboarded — refining causal models against real, messy multi-vendor environments, which is also the intended long-term data moat. Both — initial SOM is India + APAC for the first 3 years, per the current go-to-market plan. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/FFoNmlWccgyl-RegencyOps_Stratos_Pitch.pptx, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/FFoNmlWccgyl-RegencyOps_Stratos_Pitch.pptx https://youtu.be/csCYsyCTKbc Partially — while Stratos itself is enterprise-focused, RegencyOps as a company has a genuine impact angle through CampusHire and PlacePrep, which help colleges and students navigate placement readiness, addressing real employability gaps in India's education-to-employment pipeline. NA IIT Kanpur Alumni Association checked
Aug 12, 2026 @ 10:56 PM Utkarsh Gupta utkarsh@pi-dojo.com https://www.linkedin.com/in/utkarshiitr2020/ http://NA +919455569903 Vatsal(CEO):- 8+ years of experience in software, ML, and distributed systems. Built synthetic data generation systems for Alexa. Utkarsh(CTO): 6+ years of experience in EV and embedded systems and MBD.Built RTB robot for Bajaj. We have known each other for 2.5 months. We met on Reddit after Vatsal had spent two months exploring whether world models could be post-trained to generate robotics training data. Through that work, he realized video-only data was insufficient because it lacked the signals needed to capture real-world dynamics and physics. Then he started looking for someone who could help build RGB-D headgear, a hand-tracking and tactile-sensing glove, which is how he connected with me - Utkarsh. Since then, we have worked together to build PI Dojo. Apart from that we have met recently in gurugram. All The founders are alumni of IIT Roorkee and Arizona State University. I (Utkarsh) have experience in EV systems, embedded systems, and robotics from Ola Electric and Bajaj. While mt Co-Founder (Vatsal) has strong backend, distributed systems and ML experience from Google, Amazon, and Microsoft. Our skill sets are complementary across software, ML, robotics, and hardware. PI Dojo’s unfair advantage is an infrastructure-first approach to robotics data. We understand how to build scalable data systems, and we are applying that to a domain where the bottleneck is not just models, but high-fidelity grounded data. PI Dojo https://www.pi-dojo.com/ Gurugram Grounded robotics training data from dexterous human demonstrations LLMs had the internet scale data for training but Robots don’t have that much quantity of training data. The defining bottleneck in robotics today is the scarcity of high-quality training data. Teleoperation cannot scale due to its reliance on human operators, custom hardware, and controlled setups. Conversely, the internet is full of raw human videos but they are useless for robot policies without spatial and physical grounding (camera pose, hand-ob), PI Dojo solves this. Our end-to-end infrastructure processes raw human demonstrations, automatically extracting the missing physical context to generate grounded, humanoid-ready training datasets. PI Dojo collects in-the-wild human manipulation behavior using custom capture hardware, including RGB-D headgear and tactile gloves. We solve the scale problem through a distributed MSME partner network, allowing us to collect diverse task families, environments, tools, materials, and workflows. We solve the fidelity problem through our grounding pipeline, which converts raw demonstrations into robot-ready training data with modalities including - color, depth, camera pose, hand key-points, 3D hand pose, task labels and tactile signals (contact / pressure) . We are building a full capture-to-grounding data layer for robotics (Not a generic annotation service). Our edge is the combination of real-world data sourcing, custom capture hardware and robotics grounding. The output is not raw video or labels; it is high-modality humanoid training data. We believe our data will be best-in-class specifically because of the quality and density of the modalities we offer. The quality of robot learning depends on the quality of physical grounding. The more accurately the data captures real-world physics, contact, motion, camera pose, tactile signals, and task structure, the more useful it becomes for training reliable robot policies. Users Our target customers are Physical AI foundation model companies, humanoid robotics companies, warehouse/industrial automation companies, and manipulation-focused AI teams that need task-specific demonstration data. The global Embodied AI Data market is projected to grow from US$ 753 million in 2024 to US$ 6752 million (TAM)by 2031, at a CAGR of 36.8% (2025-2031), driven by critical product segments and diverse end‑use applications. We estimate RGBD + tactile datasets represent approximately 60 to 70% of the embodied AI data market, as perception (RGBD) and physical interaction (tactile/contact) constitute the core data modalities required for robot manipulation and foundation model training. SOM: US$50M to US$150M over five years, based on acquiring leading humanoid robotics companies, embodied AI developers, and research labs as enterprise customers. NA Our closest direct competitors are Human Archive and Intelligence Factory, which also collect high-modality human manipulation data, including RGB-D video and tactile signals. Other companies, such as Cortex AI, Shift, Asimov, Hub, and Claru AI, primarily focus on lower-modality data, including RGB or RGB-D video and phone-based human demonstrations. NA Our target customers are general-purpose robotics companies and Physical AI labs. Because this is currently a highly concentrated market, our Go-To-Market (GTM) strategy is highly targeted. We are primarily leveraging our existing network to secure warm introductions with key players. In parallel, we are building curated lists for strategic outbound campaigns to engage the remaining high-value accounts. Our long-term vision is for PI Dojo to become the data and training infrastructure layer for Physical AI. Over the next three, PI Dojo aims to become the data infrastructure layer for Physical AI, providing the grounded, multimodal datasets used to train and evaluate humanoids, robotics foundation models, and world models. Over time, we plan to expand this into a full Physical AI data factory that combines proprietary real-world data, simulation, training infrastructure, and evaluation. Once we have built a sufficiently large and diverse data corpus, we intend to use it to train and offer our own advanced Physical AI models. This is important to us because data is one of the largest bottlenecks preventing robots from becoming capable and reliable in the real world. Solving it could significantly accelerate the development of general-purpose robots that improve productivity, reduce dangerous or repetitive human work, and make advanced robotics accessible across industries. In progress We haven't raised any funding Yes We are applying to the IITACB Incubator because it gives PI dojo a unique advantage in building the industrial data infrastructure required for Physical AI. The Bommasandra industrial hub and the broader Bengaluru manufacturing ecosystem give us direct access to the diverse manipulation tasks that robotics companies need to train general-purpose robots. IITACB can help us bridge the gap between our technology and industrial deployment through its network, mentorship, technical ecosystem, and access to IIT-linked talent and infrastructure. This is particularly valuable as we scale from our initial data-collection pilots into a standardized, reliable platform for collecting and delivering robotics training data. Yes Bangalore, and particularly the Bommasandra industrial corridor, gives PI Dojo a unique advantage: access to a dense concentration of manufacturing activity where robots will ultimately need to operate. We see the ~$16B Bommasandra industrial ecosystem not just as a market, but as a large-scale real-world environment for generating robotics training data. We will work directly with manufacturers to capture high-quality multimodal data from real industrial workflows, starting with basic manipulation tasks such as picking, placing, sorting, assembly, and tool handling. These datasets can then be used by general-purpose robotics companies to train and evaluate robot policies across different environments, objects, and task variations. Bommasandra allows us to start locally and scale systematically. Instead of building artificial environments for data collection, we can deploy our hardware and data-collection systems directly inside factories, work with operators to identify repetitive manipulation tasks, and continuously expand the diversity of objects, environments, and workflows in our dataset. Bangalore's broader manufacturing and technology ecosystem also gives us access to potential customers, robotics companies, hardware suppliers, engineering talent, and early adopters. IITACB can significantly accelerate this process. Its physical presence within the Bommasandra industrial area, along with its industry and academic network, can help us establish introductions to manufacturing companies and identify suitable pilot sites. The incubator's maker spaces and infrastructure can support rapid iteration of our data-collection hardware, while its mentors, IIT alumni network, and industry connections can help us refine our go-to-market strategy and build relationships with robotics and AI companies. IITACB's focus on industry-academia collaboration and its emerging AI ecosystem is particularly relevant to our goal of building high-quality data infrastructure for Physical AI. Our vision is to make Bommasandra our initial data-generation ground, Bangalore our first robotics data ecosystem, and PI Dojo's infrastructure scalable across manufacturing hubs globally. No NA Yes Other: PI dojo is a deep-tech data infrastructure platform for Physical AI. We integrate RGB-D, tactile sensing, synchronization, calibration, and proprietary data pipelines to capture training-ready multimodal robotics data. We are developing proprietary hardware-software integration and data-processing methods. We currently do not hold a granted patent, with IP being developed around our system architecture, data pipelines, and datasets. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/E7nNNbMlqspA-PI-Dojo-Pitch-Deck.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/E7nNNbMlqspA-PI-Dojo-Pitch-Deck.pdf https://drive.google.com/drive/folders/1m_PiWJfH_679uKKdPKVBZiu-1gPyzlDC NA checked
Aug 12, 2026 @ 7:37 PM Abhishek Kumar abhi737shek@gmail.com https://www.linkedin.com/in/abhishek-kumar-%E0%A4%85%E0%A4%AD%E0%A4%BF%E0%A4%B7%E0%A5%87%E0%A4%95-%E0%A4%95%E0%A5%81%E0%A4%AE%E0%A4%BE%E0%A4%B0-2b0594b3/ +918017401560 I'm a multidisciplinarian. Alumnus of FTII, XLRI, etc. Have also worked at Bajaj Finserv as part of its Group Young Leaders Programme. Zerkalo Pune Film production Solving for art Great cinema is the solution Can't measure the immeasurable Expertise, money, network Yes 'll see Yes Other: Use AI as and when needed 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/Op3ousUe0l1s-Zerkalo.pages, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/Op3ousUe0l1s-Zerkalo.pages NA checked
Aug 12, 2026 @ 3:08 PM Testing dogove@mailinator.com https://www.woxatuvasuj.cm https://www.tucurixe.ws +1 (916) 647-9851 Culpa eius amet dis Et ut et accusantium 1 Autem velit amet do Cathleen Tate https://www.fohiwoxenyjaxi.tv Consequuntur est min Tempora magni animi Obcaecati perspiciat Porro aut adipisicin Quisquam reprehender Product-Market Fit Revenue, Signups, Testimonials Maiores similique pl Non Nam magni rerum Mollit lorem minus e Labore laudantium c Tempora ab similique Quia molestias quo v Et nobis dolore laud Odit consequatur exc Quis nostrud vero et Ad iure velit proide Dolor sint sequi eos No Autem sed soluta et Incidunt qui duis c Et excepteur quae ni Do eos id tempora r Yes Possimus qui mollit No Other: Judith Garner Laboris quam odit cu Incididunt magnam vo Amet quos dolor nec Voluptatibus et sunt Cum officia culpa a In est ratione et r A amet corporis qui Hic sapiente provide Similique provident Incididunt aliqua E Labore architecto ex Est anim enim corpo 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/Q55AJ9ZwuaOk-7mb.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/Q55AJ9ZwuaOk-7mb.pdf https://www.letizumu.org.uk Exercitation sed nih Recusandae Veniam Repellendus Similiq Fugit sint harum mo checked
Aug 12, 2026 @ 2:41 PM Cairo Taylor cypune@mailinator.com https://www.darebul.com https://www.zevyh.net +1 (196) 547-5048 Dolor consequatur r Reprehenderit volup 1 Ea ut ab impedit ac Hanae Frederick https://www.mivep.me Eum ipsum laudantium Quas voluptates ipsa Est vel sunt volupta Dolorum sunt et rer Doloribus exercitati Revenue Signups, Testimonials Dolor sit illum te Quae quia ut vitae q Perspiciatis omnis Delectus reprehende Voluptatem aliquip l Rerum dolor molestia Hic in vel fugiat d Ipsam dignissimos mi Dicta facilis corpor Mollit mollitia recu Veritatis non volupt No Qui officia nulla ea Architecto similique Consequatur et ut a Eum velit rerum qui No Ipsum in et est nece No Supporting feature Consectetur maiores Sunt omnis id duis Culpa cumque velit v Beatae quae consecte Quasi et cupidatat N Est fugiat tempor s Error adipisci vero Ad voluptas eveniet Nobis officiis rerum Neque ex architecto In quos nisi reprehe Soluta temporibus be 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/eY5IEPdgPE3h-7mb.jpg, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/eY5IEPdgPE3h-7mb.jpg https://www.xomuvijedej.us Doloribus voluptate Assumenda voluptatem Quis commodi est tem Consequatur Invento checked
Aug 12, 2026 @ 2:25 PM Haviva Norton liburyb@mailinator.com https://www.penobomyzy.co https://www.zyxubugygubekeh.info +1 (988) 302-9878 Iusto nobis sit aut Vitae voluptates lab 1 Animi eum tempore Demetrius Vincent https://www.xiraxic.me Dolor qui duis enim Fuga Qui nostrum ne Quo inventore et vol Assumenda dolores eu Molestiae et quae eo Product-Market Fit Revenue, Signups, Testimonials Nihil ipsum enim ev Illo blanditiis in i Yes Reprehenderit nemo Consequat Recusanda Magna incidunt cons In tenetur nulla pos Yes Animi quia aliquid No Not applicable Dolore excepteur in Corporis recusandae Nulla dolores qui op Sint cupidatat repre Porro ut et reprehen Dolor id aliqua Omn Accusamus eum et odi Qui earum aut expedi Vero et quis similiq Magna hic consequatu Dolorum culpa ipsa Excepteur tempor ill 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/DL4TtzAGac4n-banner.png, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/Givvia1gKcP0-Surf_2026-new-27-07-2.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/DL4TtzAGac4n-banner.png, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/Givvia1gKcP0-Surf_2026-new-27-07-2.pdf https://www.vymily.org Inventore eu distinc Ut omnis saepe nisi Veniam veritatis au Quibusdam amet qui checked
Aug 11, 2026 @ 10:26 PM Sahil Singh satvolume@gmail.com https://www.linkedin.com/in/n8singh/ https://github.com/romanticNomad +91 9531974505 Sahil Singh:: Role: Founder, Background: Student at IIT BHU Physics department, Built a transaction software for the Ethereum Virtual Machine (EVM) and scaled it up to 1000 transactions per second maintained at a p99 latency of 50ms, and wants to turn it into an infrastructure service for licensed institutional operators. I am presently a solo founder, but I am willing to partner with an eligible co-founder. All I am a solo founder. Sthiranet Settlement linkedin.com/company/sthirasettlemets NA Our goal is to provide network-based, privacy-first digital infrastructure to licensed supply-chain finance institutions seeking to digitise their receivables portfolio. Traditional systems employed for managing assets face 3 major problems, which are also identified by the IMF 2026 note on tokenised finance: 1) Delay in settlement of transactions. 2) Heavy logistic overhead of compliance and corporate operations. 3) Lack of continuous liquidity vehicles for illiquid assets. Tokenisation of these assets using the Distributed Ledger Technology (DLT) provides an ideal solution to the above-mentioned problems. Services provided by Sthiranet improve as the number of clients grows (network-as-a-service model). This provides clients with a real advantage in partnering with Sthiranet instead of building a settlement system in-house. We do this by providing 2 layers of services. 1. Individual Layer: This layer solves the time delay and logistics overhead problems by embedding the corporate logic into a smart contract and deploying it on the ledger (database) in an instant (atomic transaction). This way, the transactions occur at a T+0 time delay, and the corporate logic of the contract is automated. 2. Network Layer: Using a collection of cryptographically hashed data, Sthiranet will be able to provide network services like: a. Duplicate Financing Registry: A fraud detection system that identifies fraudulent buyers whose receivable invoices have already been financed by some other NBFC on the Sthiranet client network. b. Aggregate Risk Scoring: Based on the anonymised repayment performance data collected across the Sthiranet client network, Sthiranet will be able to provide a superior Risk Score that drastically reduces the cost of capital for Sthiranet clients. Our tech stack provides a native privacy enabled layer that prevents client's transaction information from being public which is not generally the case for traditional blockchain solutions. The network-as-a-service model combined with native privacy layer positions Sthiranet uniquely compared to other SaaS players in the market. Idea Signups Licensed supply-chain finance providers seeking to digitize their trade receivable portfolio. Global factoring market was valued at approximately $4.51 trillion in 2025 Mid-market segment in our target regions (India, Brazil, ASEAN) represents a $150B+ in SAM A 0.1% to 0.2% market capture in next 3-5 years equates to $150 million to $300 million in annual processed receivable volume. An upfront installation fees followed by a revenue share subscription model on the revenue generated by our clients using our service. At both regional and global level, Sthiranet has 4 major competitors: Spydra Technologies, Vayana Network, Incomlend and Centrifuge. Cold approach and networking through FinTech conferences and mutual connections. Document progress and create reach through Blogs on LinkedIn and X, get interested institutional signups before the actual pilot program is launched. I plan to develop an MVP in India and later expand to Singapore and Hong Kong to gain access to the greater ASEAN and East Asian market. Later, I plan to expand to Brazil, which has a large supply-chain receivables market, and, through Brazil, expand into the broader Latin American market. I plan to enter the European and American markets only after I have built a mature network in the other markets mentioned, because they are fast-growing, have less political friction, and are more willing to experiment in this field. NA NA Yes I am fascinated by the work of all my alums, that I have met through various events and connections, I want to earn my own set of achievements and be a part of this network, and I believe that collaborating with IITACB can help me achieve that. I want to make connections with people who may later become my clients or at least can get me connected, I also want to make connections with possible investors to my business. yes If Bommasandra or Banglore in general happen to have my ideal clients, instead of selling them my service as an established provider, I would start a pilot program in which my team would work closely with their team to set up a custom digitization infrastructure, without any up-front cost, to makeup for the risk they would be taking in collaborating with an early stage startup. This way both teams will be able to learn and we will be able to leverage the high-appetite for risk that is common in the Bangalore business ecosystem. IIT ACB can help by being a intermediary in the process, it may increase the trust factor with prospective clients which otherwise would have been low. Yes Apart from being a working space for Sthiranet, IITACB would a great gateway to the local Bangalore market, which would have been difficult to access if Sthiranet operates from outside of Bangalore. Also being in Bangalore and affiliated with an IIT tagged incubation cell, Sthiranet will appear to be a more trustable entity to the prospective clients not only in Bangalore but across the globe. Yes Core engine At the core of Sthiranet sits Lobby, a transaction software that I built and optimised to meet institutional high-throughput and low-latency requirements. Lobby is adapted to make transactions on the Canton network, which is the Distributed Ledger Technology (DLT) that Sthiranet leverages. Lobby is wrapped by a tokenisation system that builds the Daml contracts (native language used on the Canton network), the Daml contracts embedds the corporate and compliance logic, which are then deployed to the Canton network. This system is further wrapped by a client-facing layer that provides all the high-level APIs and records the hashed transaction data, which is then collected and normalised into forms that can be further used to provide the network-level service to clients, like duplicate financing detections and risk scoring. The majority of the codebase is written in Rust and Daml. Sthiranet does not have any proprietary data yet. 1. Niche specificity: Sthiranet operates in a very specific niche, i.e, the licensed supply-chain finance provider (mid-tier NBFCs) seeking to digitise their receivable portfolio; most of the competitors are in the larger market-making space. This gives Sthiranet a unique market position. 2. Canton-based infrastructure: Sthiranet is built on the Canton protocol, and that allows us to build custom privacy layers for our clients; this gives us an advantage over competitors who use Ethereum L2 protocols where the transaction data is stored on a public ledger, making it unattractive for institutional players. 3. Network-as-a-service model: Unlike most competitors, Sthiranet does not follow a single-tenant-based SaaS business model; instead, we provide network services like duplicate financing detection and risk scoring that become more beneficial as the network grows, which makes Sthiranet more valuable than most of the competition. I use the following metrics to judge Sthiranet's technological performance against the competition. 1. Client Privacy: Most tokenisation services are based on L2 Ethereum chains, which inherently store all transaction data on a public ledger. Sthiranet uses the Canton protocol that allows dynamic privacy control and has a mature usage for institutional asset tokenisation. 2. Network data management: Most competitors of Sthiranet provide single-tenant solutions. Sthiranet's network data management and the resulting services allow our individual clients to benefit from the larger network of Sthiranet's client portfolio, and the quality of those services will grow as the client network grows. 3. Specialised tech-stack and deep-tech leverage: Sthiranet is primarily written in Rust, which provides better memory management and an asynchronous runtime, both of which are important for systems that have high-throughput and low-latency requirements. Sthiranet has been focused on in-house automation architecture since day 1. The technical talent for building such systems is rare and is generally very difficult for companies that were not built on such an architecture from scratch. Sthiranet uses the Canton protocol through which data privacy of our client becomes native to the transaction system itself. The compliance and regulatory requirements are embedded into the Daml smart contracts deployed to the Canton network. Sthiranet is planned to run Canton nodes locally instead of hosting on foreign servers. There are 2 major Policy intervention helping Sthiranet in India. 1) RBI’s Expansion of the TReDS Ecosystem: RbI's Trade Receivables Discounting System (TReDS) mandates require large corporates (with turnovers above ₹500 crore) to settle MSME invoices via TReDS platforms, this create a mature pool of exact asset class that Sthiranet is targeting. 2) RBI Regulatory Sandbox (Safe Harbor for Innovation): RBI provides a safe-sandbox to allow fintechs like Sthiranet to test innovative-tech like our tokenisation of trade-receivable, this create a favorable safety net for Sthiranet and out prospective clients. No, Sthiranet is planned to only operate in jurisdictions that have well-laid-out trade receivable and tokenisation regulations, and Sthiranet will comply with those regulations. The processor threads will overload if Sthiranet scales 10x, even though the software itself is made for handling high throughputs (Lobby can handle up to 10K transactions per second), but Sthiranet will require better hardware for processing. No, I don't have a team yet, but I have over a year of experience in writing Rust software for blockchain applications, and I am willing to hire professional individuals with experience in trade receivable financing, tokenisation of digital assets using Canton, and building second-brain automation systems using open-source models. This will make up for an ideal 4-member team to build an MVP for Sthiranet. Sthiranet uses Lobby, an open-source transaction software that I wrote for processing EVM (Ethereum Virtual Machine) transactions at high throughput while maintaining low latency, and I plan to build an internal second brain system using open-source models to oversee the technical streamlining across all our code bases of Sthiranet. Apart from that, Sthiranet does not have any IP yet. Sthiranet uses TReDS (RBI's Trade Receivable Discounting System) API for Oracle data on trade receivables in India. Apart from regular upskilling of my teams in specialised aspects, I plan to integrate a central 'second brain' model, built in-house by fine-tuning open-source AI models; this would help in rapidly upgrading the Sthiranet code base and document faults and solutions to reinforce the learning and upgrading process while keeping highly skilled human beings in the loop. I am building for both Indian and global markets. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/ARBMz8NNDcrT-Sthiranet_Settlement_pitch_deck.pptx, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/ARBMz8NNDcrT-Sthiranet_Settlement_pitch_deck.pptx http://NA I aim to build an impact-focused startup. Since Sthiranet is at the intersection of finance and technology, I want to build a lean team of cross-functional experts skilled in both finance and cryptography and leverage large-scale automation to delegate manual work, allowing my team to focus on high-leverage intellectual tasks. This would also allow my team to be more flexible and pivot instantly to meet changing market demands and performance requirements. NA Ravi Teja, Founder and CEO Vishvena Techno Solutions NA checked
Aug 11, 2026 @ 9:28 PM Yuvansh Sagar yuvansh@nileai.in https://www.linkedin.com/in/yuvansh-41ba2b35b/ http://NA +91 7760441501 Yuvansh Sagar — Founder, Director & CEO Leads company vision, strategy, product direction, fundraising and overall business development. Anand — Co-founder & CIO Leads innovation, technology strategy and development of NILE's core AI execution architecture. Bhagya — Director & COO Leads operations, execution, partnerships, hiring and cross-functional coordination. Subhash — CTO Leads technical development, engineering and product implementation. Yuvansh and Anand are biological brothers. And Bhagya, Subhash and Yuvansh met through academic and professional network and began working together on QuasysAI while developing NILE. We have worked together closely through the product-building and validation stages, building strong technical and operational alignment as a founding team. 2 Our biggest strength is complementary expertise across technology, innovation, product execution and operations. We combine technical depth with strong execution, allowing us to move quickly from identifying problems to building, testing and improving NILE while staying aligned on our long-term vision. QUASYSAI PRIVATE LIMITED https://nileai.in Bengaluru, Karnataka QuasysAI is building NILE, an AI execution intelligence platform that transforms user intent into real-world outcomes through context-aware decision-making, coordination and execution across fragmented services. QuasysAI is building NILE, an AI execution intelligence platform that transforms user intent into real-world outcomes through context-aware decision-making, coordination and execution across fragmented services. AI can understand and recommend, but it still struggles to reliably execute real-world outcomes. Users must coordinate multiple fragmented services, make decisions and handle failures themselves. NILE addresses this gap between AI intelligence and real-world execution. NILE understands user intent and context, makes decisions, coordinates connected services, executes tasks and adapts when execution fails. Starting with mobility and travel, it transforms AI from an answer engine into an outcome engine. Revenue Users, Revenue Initially, urban consumers, commuters, travelers, students and young professionals who frequently make and execute real-world decisions. Long term, NILE will serve enterprises, service providers, developers and institutions through its execution infrastructure. $500B+ global opportunity ~$50B across our initial markets ~$2B within our initial customer segments NILE will use a multi-layered model: consumer subscriptions and execution fees initially, followed by enterprise SaaS, API licensing, SDKs and usage-based pricing for businesses using NILE's execution infrastructure. NILE will use a multi-layered model: consumer subscriptions and execution fees initially, followed by enterprise SaaS, API licensing, SDKs and usage-based pricing for businesses using NILE's execution infrastructure. Through product-led growth, targeted seeding of high-density user networks, referrals, creators, community leaders, social sharing and strategic partnerships with mobility, travel and service providers. We seed NILE in decision-dense networks such as campuses, communities and travel clusters, create product-led referral loops, then expand through creators, merchants, mobility partners and institutions. Density and network effects precede geographic expansion. Our vision is to make NILE the default execution layer between human intent and the real world—where people simply “Ask NILE,” and it understands, decides, coordinates and executes across services. Over time, NILE will expand from mobility and travel into consumer, enterprise and institutional workflows, becoming infrastructure for AI-driven real-world execution. Private Limited Company — QuasysAI Private Limited ₹0 — Bootstrapped Yes We are applying to IITACB to access technical mentorship, industry connections, incubation support and investor networks that can accelerate NILE from early revenue to scalable AI execution infrastructure. IITACB's ecosystem can help us validate enterprise use cases and build strategic partnerships. We aim to strengthen NILE's technology, validate additional real-world use cases, secure strategic pilots and partnerships, improve our go-to-market execution, and prepare the company for the next stage of fundraising and commercial scale. Yes Bangalore provides a dense ecosystem of technology companies, mobility providers and enterprises where NILE can validate real-world execution workflows. We can leverage the Bommasandra industry hub for industry connections and pilots, while IITACB can support us through technical mentorship, industry introductions, infrastructure and investor access. Yes We would use the incubation space for core-team operations, NILE development and testing, technical collaboration, customer and partner meetings, and pilot execution. We also want to leverage IITACB's infrastructure and ecosystem for mentorship, industry engagement, networking and investor interactions. Yes Core engine NILE is an AI execution-intelligence layer between user intent and real-world services. Its architecture combines intent understanding, context and constraint processing, decision intelligence, execution orchestration, service/API integrations, failure detection, fallback handling, outcome verification and learning from execution results. NILE is building an execution-outcome dataset capturing the relationship between intent, decisions, actions, failures, recoveries and outcomes. This differs from datasets based primarily on prompts and responses, enabling NILE to improve its real-world execution intelligence as usage grows. NILE's defensibility comes from its execution architecture, accumulated real-world execution history, service integrations and outcome-based learning. As usage scales, these create increasingly valuable execution and outcome graphs that are difficult for competitors to replicate quickly. We evaluate NILE using execution-focused metrics including Decision Compression Ratio, Time-to-Outcome, Recovery Success Rate, execution success rate, successful decisions per user, delegation depth, outcome quality and retention. These measure whether NILE reliably completes and recovers real-world tasks. NILE follows a privacy-by-design approach with user control over retained context. As we scale, we will implement data minimization, encryption, access controls, secure API integrations, auditability and market-specific privacy and data-protection controls. We have already filed provisional patent and logo trademark. AI adoption, digital infrastructure, API-based services and increasing digitization of mobility and commerce create a favorable environment for NILE. However, our business does not currently depend on a specific government policy, subsidy or intervention. Potential risks include data privacy and cross-border data requirements, third-party platform/API restrictions, consumer protection, payments and sector-specific regulations as NILE expands across mobility, travel, commerce and enterprise workflows. The main risks are API reliability, integration complexity, execution latency, vendor failures, observability and infrastructure capacity. We are addressing these through modular integrations, vendor redundancy, monitoring, fallback strategies and scalable execution infrastructure. Yes. NILE's core technology is being developed in-house. The CEO leads innovation and NILE's AI execution architecture, while the CTO leads engineering and technical implementation, supported by the founding leadership team and technical interns. NILE uses commercially available AI/LLM capabilities, APIs and standard software components where appropriate. Third-party components remain subject to their respective licenses. Our proprietary layer consists of NILE's execution architecture, orchestration logic, integrations and outcome data generated through product usage. NILE continuously learns from the execution loop: Intent → Decision → Execution → Outcome. We use success, failure and recovery data to improve decision quality, service selection, routing and fallback strategies, while continuously monitoring execution and outcome metrics. Both. India is our initial validation market, particularly Bengaluru, where dense digital ecosystems and fragmented services provide a strong environment for testing NILE. We plan to expand globally into markets with high decision density, digital readiness and strong service ecosystems. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/E2VaeH1dxooO-QuasysAi_PD.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/E2VaeH1dxooO-QuasysAi_PD.pdf https://drive.google.com/file/d/1xIxbuQYx7epc2ghfNnmryE-BbTRAuROf/view?usp=sharing Yes. NILE's mission is to make AI capable of reliably executing real-world outcomes, reducing the complexity and friction people face when navigating fragmented services. Starting with mobility, we aim to improve access, reliability and efficiency while building technology that can eventually support broader societal and infrastructure workflows. NA NA NILE is being built as an India-first, globally scalable AI execution platform. We are currently at the early-revenue stage with 400+ active users, ₹2.5L+ reported revenue and 85%+ 30-day retention, and are focused on expanding real-world validation, strategic partnerships and execution reliability. checked
Aug 11, 2026 @ 6:52 PM Vijendra Goyal vgoyal.iitbhu@gmail.com https://www.linkedin.com/in/vgoyal29/ http://swiftontime.com +91 9538356544 Product Business Strategy Quit my job in Feb 2026 to work on this problem of solving daily office commute by providing pre booked shared commute service. 1 Building Team, Hiring Right set of people , Solving problem , Making business strategy , Building product. SwiftOnTime swiftontime.com Bangalore Asset light shared commute platform solving daily office commute and reducing traffic by providing pre booked shared commute service. Building a asset light shared commute platform which allow user to coordinate with person going in the same route and almost same time to travel together using cab or auto and split the fare in order to increase the occupancy rate of each cab or auto on the road. Asset light commute discovery platform build for our country where people wants to save money and nation wants to use fuel in efficient way Product-Market Fit Users, Revenue, Pilots, Signups, Testimonials 20 to 35 aged group collage goer, early stage of career, daily office goer, people coming from railway, airport, malls where demand is high but supply is less. 30000 Crore 8000 Crore 1000 Crore Platoform fee, Booking Commission both from users and cab company, Self fleet margin, Corporate/B2B setup, Bike taxi (due to price war) Hyperlocal marketing and word of mouths - residential societies, Office-Tech parks, WhatsApp groups and existing 500+ SwiftOnTime users. Referral-led growth and targeted digital/social campaigns to build density on specific routes and time slots. As matching liquidity grows, successful shared rides and repeat usage will drive organic network effects. We will start hyperlocal, building density route-by-route rather than launching city-wide. We will pilot with existing SwiftOnTime users and residential communities, acquire commuters through WhatsApp/community groups and office networks, match users travelling on similar routes and timings, and use successful shared rides, referrals and repeat usage to build network effects. Once validated in Bengaluru, we will expand to other high-density office corridors and Tier-1 cities. Our long-term vision is to build India’s leading Social Commute Platform - a discovery layer that connects people travelling on the same route and time, enables them to share cabs/autos, split fares, and eventually book rides seamlessly through mobility partners. We aim to make everyday urban commuting more affordable, reliable, social and sustainable, starting with Bengaluru and expanding across Tier-1 cities. Done NA Yes To get access to experienced mentorship, industry networks, and guidance on validating and scaling SCP (Social Commute Platform). We want to use the incubation ecosystem to strengthen our product, business model, technology, and go-to-market strategy, while leveraging our existing SwiftOnTime platform and mobility experience to build a scalable Social Commute Platform. To validate SCP(Social Commute Platform) through real-world pilots, achieve strong product-market fit, refine the revenue and operating model, and build a scalable technology and go-to-market strategy. We also aim to leverage IITACB’s mentorship and network to prepare SCP for expansion from Bengaluru to other Tier-1 cities and become investment-ready. yes We aim to use Bengaluru as our launch and validation market, leveraging its dense technology, manufacturing and corporate ecosystem to build strong commuter networks and validate SCP at scale Yes To build the network, find a right set of people. Also we want to use IITACB as our working base for building and validating SCP, while leveraging its collaborative workspace, meeting rooms and professional environment for product development, user research and partner meetings. Yes Supporting feature Technology Stack: Mobile-first PWA built using React + TypeScript, with Vite as the build tool and Tailwind CSS for responsive UI. Supabase (PostgreSQL, Authentication and backend services) is used for data and user management. Google Maps APIs are used for location, route and pickup-point functionality. Cashfree Payments is used for payment processing in the existing SwiftOnTime platform. The application is developed using Lovable with a modular architecture so SCP can be developed without impacting the existing SwiftOnTime shuttle-booking system. Future integrations: Uber, Ola and Namma Yatri APIs for ride-hailing/booking orchestration, subject to API availability and partnership access. Yes. Our initial data advantage comes from SwiftOnTime’s existing commuter ecosystem and operating experience in Bengaluru. We have access to first-party commute signals such as routes, pickup/drop locations, travel timings, recurring commute patterns and user ride behaviour. As SCP pilots grow, we will build a proprietary dataset of route-time demand, commuter matching, shared-ride conversion, fare ranges and repeat behaviour. This data can improve matching accuracy, route density and pricing over time, creating a compounding network-effect advantage. Our defensibility will come from a dense, hyperlocal network of commuters, proprietary commute and matching data, and a trusted social layer around everyday travel. As more users participate, SCP can improve route-time matching, fare estimation and reliability, creating stronger network effects within specific communities and corridors. Our existing SwiftOnTime platform, commuter base and mobility operating experience provide an initial advantage to build this network. Over time, the combination of network density, trust, repeat behaviour and matching intelligence can create meaningful barriers to replication. SCP is currently in prototype/pilot stage, so we are evaluating technology primarily through functional reliability, responsiveness and real-world pilot performance rather than benchmarking against competitors. We follow a privacy-by-design approach, collecting only data required for commute matching and service delivery. User data is protected through authenticated access, role-based permissions, secure database policies, and controlled sharing of profile/ride information. We plan to implement appropriate consent, privacy notices, data retention/deletion controls and breach-response processes aligned with India’s applicable data-protection and cybersecurity requirements, including the DPDP framework and CERT-In requirements. Yes. Government policy increasingly supports shared and sustainable mobility to reduce urban congestion, emissions and inefficient vehicle utilisation. The Government of India has recognised shared mobility and ride-pooling as part of the broader mobility ecosystem, while the 2025 Motor Vehicle Aggregator Guidelines provide a framework for commercial ride-sharing. SCP can contribute to these objectives by increasing vehicle occupancy and reducing the number of individual trips. We also expect future policy support for organised carpooling, EV adoption and sustainable urban mobility to benefit the platform. Motor vehicle / aggregator regulations around ride-sharing and passenger transport. Licensing and permit requirements depending on whether rides use private or commercial vehicles. Liability, insurance and passenger safety in shared rides. Third-party platform policies if integrating Uber/Ola/Namma Yatri. At 10x scale, the main challenges would be matching speed and accuracy, database/query performance, real-time notifications/location updates, and payment/transaction reliability. We would address these through scalable backend infrastructure, indexed matching queries, caching, asynchronous processing and stronger monitoring. The key metric we would watch is successful match-to-ride completion rate without increasing latency or failures. No. We currently do not have an in-house deep-tech/AI team. Our product is being developed with a lean product and technology setup, using modern cloud and software technologies. We plan to build an AI/ML capability as SCP scales, particularly for intelligent commute matching, demand prediction and route optimisation, with support from technical mentors and the IITACB ecosystem. We currently use standard open-source software frameworks and libraries, along with third-party APIs/services such as Supabase and Google Maps APIs. These components are used under their respective open-source or commercial licenses. SCP does not currently use proprietary external datasets or licensed AI datasets. Our key proprietary data will be generated from first-party commuter activity on SwiftOnTime/SCP, including route, timing, matching and ride behaviour. We currently have no registered IP/patent reference; our proprietary IP will primarily be the product architecture, matching logic, workflows and accumulated first-party data. We will continuously improve technology through real-world pilot feedback and data-driven monitoring. We will track key metrics such as app performance, uptime, error rates, matching accuracy, successful ride completion, cancellations and repeat usage. Insights from users and ride data will guide iterative improvements to matching algorithms, scalability, security, reliability and overall user experience. We are initially building for India, starting with Bengaluru as our primary validation market. We plan to expand SCP to other Tier-1 Indian cities once the model is validated and achieves sufficient commuter density. International expansion may be considered later, but our immediate focus is India. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/Sv5guvrGzuQV-SCP_IITACB_PitchDeck.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/Sv5guvrGzuQV-SCP_IITACB_PitchDeck.pdf Yes. SCP is mission-driven around making urban commuting more affordable, reliable and sustainable. By helping people travelling on the same route and at similar times discover each other, share cabs/autos and split fares, we aim to reduce the cost of commuting, improve vehicle utilisation and reduce unnecessary solo trips, congestion and emissions. We plan to start in Bengaluru and scale the impact across India’s Tier-1 cities. NA Kamlesh from IITACB checked
Aug 11, 2026 @ 3:13 PM Ayush Bhardwaj founders@chronis.in https://www.linkedin.com/in/ayush-bhardwaj-b76414203?utm_source=share_via&utm_content=profile&utm_medium=member_android http://NA +919899497406 Aniket Mandal CTO (been a remote strategist at Frost & Sullivan), Ayush Bhardwaj CEO (worked as a founder in multiple startups, ex student flying pilot ranked 4132 AIR) , Nikunj Mathur COO (based in IIT BHU with experience in multiple startups doing seed A currently) met 2 yrs ago have built multiple projects and done research together. 1 our biggest strength is that we keep each other accountable, we work together so it's a tussle between each of us on who works more. Chronis https://chronis.in New Delhi First AI with human intelligence, building for something which never lets you forget anything in life. We are solving for the problem that humans have a very short spanned memory what we remember is fragmented and chronis is a way to make memory continuous and searchable. an AI pendant which understands you learn from you, speaks like you and becomes your AI persona. Telling you what you miss, your flaws your issues your personalized solutions, making you remember things which you could never recall. one can't answer what they did 37 days ago, but chronis can. wearables usage is steadily increasing, people are actively looking to understand themselves better, also to save what they would forget, chronis fits right in that frame. MVP Signups, Testimonials currently we are going for HNIs and startup founders then scaling towards consumers at mass. na na na na Omi, Neosapian we acquire customers by creating hype around the product then dropping only handful of units and market it vehemently and then drop the second batch, we being a hardware startup need to have excessive marketing in the beginning but it goes a long way after done once and we don't have to keep repeating it. firstly we sell to HNIs and startup founders for better decision making and having a way to look back in past, then when we scale we switch to consumers at mass our long term vision is to make Chronis the go to device for making memory continuous and then in next 10 yrs we would also offer our users options which transfer the device data into movable robots. still based in IIT BHU, incorporating soon. NA Yes not yet. to get to connect with like minded people and potential investors yes IIT ACB can help us by providing a stage which helps us get pre seed funded so that we can launch production and work on the tech with utmost focus. Yes we would love to work hands on on the device and the framework we are curating with help of IITACB infra Yes Core engine confidential, as we haven't filled the patent yet. includes HSSM, NSSM and sum of advanced AI ML frameworks. the data we store of users is private and confidential but the insights are system generated which are the property of chronis, and cannot be transferred so our users can't switch to our competitors after using chronis for 1 month. our performance and reliability is continuously increasing which can be proved through: we started 6 months ago and now today we have a working MVP 900+ waitlist and are in programs like Sarvam AI, currently speaking with station F and cisco for pilot program. we have dedicated privacy control wing in the team we are complaint with the new privacy guidelines of India and the US. Our soon to be patented framework helps us steer away from privacy concerns while also helping users get detailed analysis about themselves. Yes, the data we store of users is private and confidential but the insights are system generated which are the property of chronis, and cannot be transferred so our users can't switch to our competitors after using chronis for 1 month. NA we currently have the infra to work upto 1k users and above that we will need a framework which can implement logics faster and also for a lot of users simultaneously. yes, in our team we have multiple profs. based in IIT BHU seasoned in ECE, AI ML and cloud computing. We also have 35+ interns from tier 1 colleges working with us, with diverse knowledge essential for chronis. we are using our own behavioural recognition system which is still not patented but is in under progress. we plan to iterate fast and learn through our mistakes and our technology patented and designed by us, making it essential for us to fix bugs and bring in new technological advancements as the market develops. both 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/asUrqtd1SZfu-chronisxallin.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/asUrqtd1SZfu-chronisxallin.pdf http://NA NA NA NA NA checked
Aug 10, 2026 @ 10:52 AM Ramunivagaira Gnanaprakash gnanaprakash@iittp.ac.in https://www.linkedin.com/in/gnana-r-310644261/ https://www.algorithec.com/ +91 7396144250 I am the Founder and CEO of Algorithec Private Limited, working at the intersection of AI, intelligent decision systems, and technology-driven entrepreneurship. I hold a B.Tech in Mechanical Engineering and currently work as a Project Scientist at IIT Tirupati, where I have gained experience in robotics, AI-enabled systems, research, prototyping, and technology development. I lead the startup's overall product vision, business strategy, technology direction, customer validation, partnerships, fundraising, and execution. Our core product is an AI-powered decision and execution engine designed to understand user intent, compare options across multiple commerce and service domains, identify relevant offers and savings opportunities, and assist users in making better purchasing and service decisions. I have experience taking the venture from ideation and prototyping through market validation, startup recognition, incubation activities, investor outreach, and MVP development. I am responsible for coordinating the technical and business aspects of the venture and translating the technology into a commercially viable product. The founding team was formed through our academic and professional ecosystem, where we connected through research, and entrepreneurship. We have worked together through the development and validation of the startup, collaborating on product development, technical implementation, market research, and execution. 2 Our biggest strength is the ability to combine technical problem-solving with strong entrepreneurial execution. We are focused on moving beyond research and prototypes toward real-world validation and commercialization. We continuously iterate based on user feedback, take ownership of execution, and are comfortable working across technology, product, business development, partnerships, and fundraising. As a team operating within the IIT ecosystem, we also have access to technical expertise, research capabilities, and a strong network that can help us solve complex problems and accelerate product development. Algorithec Private Limited https://www.algorithec.com/ Bengaluru, Karnataka, India Algorithec is building an AI-powered decision and execution platform that helps users make smarter decisions across commerce and everyday services. Our platform understands natural-language intent, searches and evaluates options across multiple platforms, identifies relevant offers and savings opportunities, and guides users toward the most suitable option and transaction path Consumers currently need to search across multiple platforms to find the best option for a single purchase or service. Prices, discounts, coupons, payment offers, reviews, delivery times, and other factors are fragmented across different platforms, making comparison time-consuming and often leading users to make decisions without complete information. Existing platforms are primarily designed to maximize transactions within their own ecosystem rather than determine the best option for the user across ecosystems. We are solving this fragmentation and decision-complexity problem. We are developing an AI decision engine that understands a user's natural-language request and converts it into actionable intent. The system can search across relevant commerce and service platforms, compare available options based on factors such as price, offers, reviews, convenience, and user preferences, and generate an AI-assisted recommendation. It can also identify applicable coupons, promotions, and payment-related savings and guide the user toward the appropriate platform or checkout flow. Our longer-term vision is to create a unified AI execution layer across domains such as shopping, food, mobility, travel, and hospitality. Our uniqueness lies in building an AI decision and execution layer, rather than another marketplace or comparison platform. It understands user intent, evaluates options across platforms, personalizes recommendations, and optimizes overall transaction value. Our integration with India’s government-backed Open Network for Digital Commerce (ONDC) further enables access to an open, multi-domain commerce ecosystem. Our defensibility comes from AI-driven decision workflows, cross-platform integrations, user learning, and a scalable multi-domain architecture. MVP Pilots, Signups, Testimonials Our primary customers are digitally active consumers in India, particularly smartphone users who regularly use e-commerce, food delivery, mobility, travel, and hospitality platforms and want better prices, offers, recommendations, and convenience. Our secondary customers include merchants, brands, and service providers that can benefit from AI-driven customer discovery and transaction opportunities. ₹5 lakh crore ₹1 lakh crore ₹200+ crore Our primary revenue model is transaction-based, earning commissions/margins from completed transactions through partner platforms and open-commerce networks such as ONDC. Additional revenue opportunities include sponsored placements, merchant/brand partnerships, and AI-powered services. Our competitive landscape includes Google Shopping, PriceRunner, Buyhatke, and individual commerce/service platforms such as Amazon, Flipkart, Swiggy, Zomato, and others. However, these platforms primarily focus on search, comparison, or transactions within their respective ecosystems. Algorithec aims to provide a cross-platform, AI-driven decision and execution layer across multiple domains. We plan to acquire users through digital marketing, social media, referral programs, partnerships, campus and community networks, content-led growth, and strategic collaborations with merchants and ecosystem partners. We will initially focus on digitally active users who frequently compare prices, offers, and services. We will initially launch with high-frequency consumer use cases where price discovery and decision complexity are significant, acquire early users through targeted digital and community channels, and use product-led growth and referrals to scale. We will progressively expand across commerce domains and integrate with open networks such as ONDC, while building partnerships with merchants, brands, and service providers. User behavior and transaction feedback will continuously improve our AI recommendation and decision engine. Our long-term vision is to build a universal AI decision and execution layer for everyday commerce and services—where users simply express what they want in natural language and our AI determines the best option across platforms, optimizes value, and helps execute the transaction. We aim to become the intelligent layer connecting consumers, merchants, platforms, and open commerce networks across multiple domains globally. Incorporated — Algorithec Private Limited NA Yes We are applying to IITACB to access a strong combination of mentorship, industry connections, investor networks, workspace, and the Bengaluru startup ecosystem. Algorithec is moving from MVP and user validation toward commercialization, and IITACB can help us strengthen our business model, partnerships, technology, and go-to-market strategy. The proximity to Bengaluru's technology and industry ecosystem is particularly valuable for building partnerships and accelerating adoption. What do Strengthen and commercially deploy our MVP. Expand real-world user validation and achieve stronger product-market signals. Establish strategic partnerships with commerce, service, and open-commerce ecosystems including ONDC. Develop a scalable technology and business model. Build relationships with mentors, industry partners, and investors. Prepare for our next stage of fundraising and commercial expansion. Yes Bengaluru provides a strong concentration of technology companies, startups, consumers, investors, enterprises, and industry partners, making it an ideal market for validating and scaling Algorithec. We can use the Bommasandra industrial ecosystem and Bengaluru market to identify early adopters, conduct real-world product validation, develop industry partnerships, and understand consumer and business requirements. IITACB can help us through mentor access, investor introductions, industry and academic collaborations, technology ecosystem connections, workshops, and physical infrastructure. These connections can help us move from MVP validation to commercial deployment faster. Yes We would also leverage the meeting and conference facilities, maker spaces, networking ecosystem, workshops, mentor interactions, and investor-connect opportunities to accelerate product development and commercialization. The physical presence in the IITACB ecosystem would help us collaborate with mentors, researchers, industry partners, and other startups while building Algorithec's Bengaluru presence. Yes Core engine Our architecture consists of a modular AI decision layer built around: User Interface → Intent Understanding → Decision/Task Orchestration → Multi-platform Data & API Integration → Ranking & Recommendation Engine → Offer/Savings Optimization → Execution/Redirect Layer → Feedback & Learning The system converts natural-language requests into structured intents, gathers relevant information from integrated platforms and open-commerce networks such as ONDC, evaluates alternatives using multiple decision factors, and produces an optimized recommendation and execution path. At the current stage, we do not claim a large proprietary dataset. Our data advantage is being developed through user preferences, interaction patterns, recommendation outcomes, transaction outcomes, and feedback generated through the platform. Over time, this feedback loop can help improve personalization, ranking, intent understanding, and decision quality. We also design the system to combine platform/API data with user-specific context rather than relying only on static datasets. Our defensibility comes from the combination of AI-driven intent understanding, decision orchestration, cross-platform integrations, personalization, ranking and recommendation workflows, and transaction feedback loops. The architecture is designed as a multi-domain decision layer rather than a single-category marketplace or comparison engine. Integrations with open-commerce networks such as ONDC can further expand the range of sources available to the decision engine We evaluate the system using measurable technical and product metrics including: Intent recognition accuracy Recommendation relevance / ranking accuracy Price and offer accuracy Savings generated for users Response latency API/integration success rate System uptime and reliability Recommendation acceptance / click-through rate User feedback and repeat usage AI response quality and hallucination/error rate As we scale, we will benchmark these metrics against conventional search, comparison, and recommendation workflows to quantify improvements in decision quality, time saved, and transaction value We follow a privacy-by-design approach by collecting only data required for the intended functionality. User data should be handled with appropriate consent, access controls, encryption, secure API communication, and controlled data retention. We plan to maintain separation between personally identifiable information and analytical/behavioral data wherever practical, restrict internal access based on roles, and ensure that third-party integrations follow their respective API terms and data policies. As the platform scales, we will strengthen our controls to align with applicable Indian data-protection, cybersecurity, and platform-specific requirements. Yes. India's growing Digital Public Infrastructure and open-commerce ecosystem, particularly ONDC under the Department for Promotion of Industry and Internal Trade (DPIIT), supports our model by enabling interoperable digital commerce across participating network participants. Policies supporting digital payments, open networks, startup innovation, and AI adoption can also reduce barriers to building and scaling our platform. Potential risks include changes in data-protection and AI regulations, platform/API access policies, consumer-protection requirements, digital advertising and recommendation rules, and terms imposed by third-party platforms. Our approach is to maintain transparent recommendations, respect platform/API terms, minimize unnecessary personal-data collection, and design the architecture so that individual integrations can be modified or replaced without disrupting the entire system. At 10x scale, the primary challenges would likely be API rate limits, integration reliability, data freshness, AI inference latency, infrastructure costs, and recommendation quality under higher traffic. We are designing a modular architecture with caching, asynchronous processing, scalable infrastructure, monitoring, fallback mechanisms, and independently scalable integration services to address these bottlenecks. Yes. Our technical team has expertise spanning AI/ML, software engineering, backend systems, API integration, data processing, and product development. The team is supported by the IIT ecosystem and has experience developing technology prototypes and translating research-oriented concepts into working systems. The team is currently focused on AI decision systems, multi-platform integration, recommendation/ranking, backend infrastructure, and scalable product development. Open-source components are used in accordance with their respective licenses. Platform data is accessed only through permitted interfaces and integrations. Our application architecture, decision workflows, orchestration logic, product implementation, and internally developed components are developed by our team. We have also initiated IP protection for the product and can provide the relevant IP reference/documentation where required. We plan to continuously improve the system through user feedback, outcome-based evaluation, A/B testing, model evaluation, integration monitoring, and continuous optimization of ranking and decision workflows. We will track recommendation accuracy, user satisfaction, savings, latency, conversion/acceptance, and system reliability. As transaction and interaction data grows, these signals will be used to improve personalization and decision quality while maintaining appropriate privacy controls. Both, with India as the initial market. India is our first target market because of its rapidly growing digital commerce ecosystem, diverse consumer base, digital public infrastructure, and open-commerce initiatives such as ONDC. Our underlying AI decision architecture is designed to be market-agnostic and multi-domain, allowing us to expand internationally after establishing product-market fit and the required platform integrations in India. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/ilBBaRRUz3m5-Algorithec-Pitch-main.pptx, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/ilBBaRRUz3m5-Algorithec-Pitch-main.pptx https://drive.google.com/file/d/1ZwUdA3bs_-ti6HxvBGCNRMqMZ2qGzLzr/view?usp=drive_link Yes. Our mission is to make digital commerce and everyday services more transparent, efficient, and user-centric. Consumers currently spend significant time navigating multiple platforms to identify the best option, price, offer, and service. Algorithec aims to give users an intelligent decision layer that helps them make better-informed choices and maximize the value of their transactions. By leveraging AI and open-commerce infrastructure such as ONDC, we aim to contribute to a more interoperable and consumer-centric digital commerce ecosystem in India. NA IITACB member Algorithec is currently progressing from MVP and user validation toward commercial deployment. We are particularly interested in leveraging IITACB's mentorship, industry connections, investor network, and Bengaluru ecosystem to accelerate product development, partnerships, and market entry. We believe IITACB can provide the right environment to convert our technology into a scalable, commercially sustainable venture with potential for expansion across multiple consumer-service domains and, eventually, international markets. checked
Aug 10, 2026 @ 1:45 AM Chandravijay Rai foundercareplus@gmail.com https://www.linkedin.com/in/cvrai/ +91 7066117218 Chandravijay Rai — Founder & CEO: Computer Science graduate and AI/full-stack engineer with experience building scalable AI, cloud, and software products. Leads Care+ across product strategy, AI/ML, engineering, technology, and overall company execution. Sanjeev Tiwari — Co-founder & CMO: Leads marketing, brand, customer acquisition, growth, partnerships, and go-to-market strategy for Care+. We have known each other since 10th grade and have been close friends for over 9 years. We previously built a laptop repair business, Reboot, together in 2022, giving us our first experience working as a team and running a business. Care+ is our second venture, where we combine our technical, product, marketing, and business strengths. 1 Our biggest strength is our long-standing trust and complementary skill sets. We’ve known each other for over 9 years and have already built a business together. Chandravijay leads AI, product, and technology, while Sanjeev drives marketing, growth, and business. This allows us to execute quickly and stay aligned. Care+ https://play.google.com/store/apps/details?id=app.dermco.ai_dermatologist_skincare Mumbai Care+ is an AI-powered skin health platform that uses computer vision to analyze skin from images and deliver personalized skincare insights and routines. We are building an accessible digital skin health platform that can combine AI-driven analysis with dermatologists to deliver personalized care at scale. Access to personalized dermatology is limited by cost, availability, and geography, while consumers often rely on generic online advice and trial-and-error skincare. Care+ addresses this gap by making personalized skin analysis and guidance more accessible, affordable, and available on demand. Care+ uses computer vision and AI to analyze a user's skin image and generate personalized skin insights, recommendations, and skincare routines. Our roadmap extends this into an AI-assisted dermatology platform where users can combine instant AI insights with consultations from certified dermatologists. Our advantage comes from combining computer vision-based skin analysis, personalized recommendations, and a continuously improving user feedback loop into one platform. We are building proprietary skin-analysis capabilities, product and user data, and an AI-plus-dermatologist workflow that can become increasingly difficult to replicate as usage and clinical expertise grow. Users Users, Signups, Testimonials Our initial customers are smartphone users aged 18–40, particularly people dealing with acne, pigmentation, Blackheads, uneven texture, oiliness, dryness and other common skin concerns who want convenient and personalized skincare guidance. We initially focus on India, with a roadmap to expand globally. $155.8B global skincare products market (2025). $9.06B India skincare market (2025). Initial 3–5 year goal: capture a small, measurable portion of the India digital-skincare opportunity through paid subscriptions, premium AI features and dermatologist consultations. We will validate SOM through user acquisition, conversion and retention data rather than assuming a fixed market percentage. Care+ uses a freemium model: users receive limited free AI skin analyses and can subscribe for premium analyses, personalized routines, advanced insights and additional features. Over time, we plan to expand revenue through dermatologist consultations, skincare/product partnerships and B2B/API solutions for dermatologists, clinics and beauty brands. Perfect Corp / YouCam, L'Oréal Skin Genius / SkinConsult AI, and Miiskin are key competitors. Care+ differentiates by combining AI-based skin analysis, personalized skincare routines, and an accessible consumer experience, with a roadmap toward AI-assisted dermatologist care. We use a product-led, digital-first acquisition strategy focused on organic social content, skincare education, creator/influencer partnerships, app-store discovery, referrals and targeted paid acquisition. Our initial focus is building trust through educational content and free AI skin analysis, then converting engaged users to premium subscriptions. We are taking an India-first, mobile-first approach. We will acquire users through short-form skincare education, creator partnerships, communities and app-store discovery, using free AI skin analysis as the entry point. We will optimize activation, retention and paid conversion through personalized routines and premium features, then expand into dermatologist partnerships, clinics and international markets. Our vision is to build a globally accessible AI-powered skin health platform where AI provides instant, personalized skin insights and certified dermatologists provide expert care when needed. We aim to make personalized skin health more accessible across underserved markets, starting with India and expanding globally. NA – Care+ is currently pre-incorporation. ₹0 – Bootstrapped to date. Yes We are applying to IITACB to accelerate Care+ from an early-stage live product into a scalable AI-powered skin health company. We are looking for mentorship in product-market fit, healthcare and AI validation, go-to-market, business strategy, and access to investors, industry partners, and the Bengaluru startup ecosystem. Our goals are to validate product-market fit, grow our user base, strengthen our AI and product roadmap, establish healthcare and dermatologist partnerships, develop a scalable go-to-market strategy, and prepare Care+ for our next stage of fundraising and expansion. Yes Bengaluru gives Care+ access to a strong technology, healthcare, startup, and investor ecosystem. We want to use the region to build partnerships with dermatologists, hospitals, clinics, technology companies, and potential distribution partners, while testing Care+ with a diverse Indian user base. IITACB can help us access industry connections, domain experts, mentors, investors, and the infrastructure needed to validate and scale the product. Yes We would use the incubation space as a base for Care+'s product development and growth activities, including team collaboration, product demonstrations, meetings with mentors and investors, and discussions with healthcare and industry partners. We would also leverage IITACB's technology infrastructure, networking opportunities, meeting facilities, and ecosystem to accelerate product validation, partnerships, and fundraising. Yes Core engine Care+ uses a mobile client connected to a Node.js/Express backend and a dedicated Python AI service. User images are securely transmitted to the backend, which handles authentication, API orchestration, image processing, and user workflows before communicating with the Python AI service. The Python service runs our fine-tuned ResNet-50 computer-vision model, exported to ONNX and served through ONNX Runtime for skin analysis. Firebase is used for application services. The architecture separates the mobile, API, AI inference, and application-service layers, allowing individual components to scale independently. We currently use established dermatology datasets for model development and validation and do not claim exclusive ownership of those datasets. Our emerging data advantage will come from consented, real-world user interactions, skin images, analysis outcomes, routine adherence and user feedback generated through Care+. Over time, this feedback loop can help us improve personalization and model performance across diverse skin types and real-world conditions. The underlying AI models are not our only source of defensibility. We aim to build an integrated advantage across computer-vision skin analysis, personalized recommendations, longitudinal user data, product feedback loops, and eventually dermatologist workflows. As usage grows, consented real-world data and outcome feedback can improve personalization and model performance, while our product, distribution and dermatologist network can create additional barriers to replication. We evaluate the ML pipeline using classification accuracy, precision, recall, F1-score and per-class performance on held-out validation data. For production performance, we monitor inference latency, API response time, throughput, error rates and availability. We also evaluate model performance across different image conditions and skin characteristics to identify failure modes. Our engineering background includes production systems with high-throughput and low-latency requirements, which informs our approach to Care+'s scalability and reliability. We treat user skin images and associated account information as sensitive user data. Our approach includes collecting only data required for the product experience, obtaining appropriate user consent, restricting access to production data, securing API communication, separating application and inference services, and minimizing unnecessary retention. We are also designing our data practices around India's evolving Digital Personal Data Protection framework and will adapt our controls as Care+ scales internationally. India's growing digital-health infrastructure, AI ecosystem and startup-support programs create a favorable environment for Care+. Government initiatives supporting digital health, AI innovation and startup incubation can help accelerate adoption and technology development. We do not currently depend on a specific policy intervention for our business model. Yes. Because Care+ analyzes skin and provides health-related guidance, its regulatory classification may depend on the product's intended use and the claims we make. In India, software can fall within the medical-device framework when intended for purposes such as diagnosis, prevention, monitoring or treatment. We therefore need to carefully manage product claims, clinical validation, user disclosures and the regulatory pathway as Care+ evolves toward AI-assisted dermatology. We will seek appropriate regulatory and clinical guidance before making diagnostic or treatment claims. At 10x scale, the main pressure points would be ML inference capacity, image-processing workloads, API/database throughput, storage and monitoring costs. We designed the architecture with separated API and inference layers so these components can scale independently. Our next scaling priorities are horizontal inference scaling, asynchronous processing where appropriate, caching, database optimization, observability and automated infrastructure scaling. Yes. The core AI and deep-tech development is currently led entirely by Chandravijay Rai, the technical founder. I handle the end-to-end AI/ML stack, including computer vision, PyTorch, TensorFlow, ResNet architectures, model training and fine-tuning, ONNX/ONNX Runtime optimization, Python AI services, LLM/RAG systems, and AI deployment. I also lead the backend, mobile, cloud infrastructure, Docker, Kubernetes, and overall technical architecture of Care+. For model development, we use publicly available dermatology and facial-image datasets, including DermNet and acne04, subject to their respective dataset licenses and terms of use. We use open-source ML frameworks and runtimes including PyTorch and ONNX Runtime, together with standard backend and mobile-development components. Our trained model weights, inference pipeline, application code and integration layer are developed by us. We are reviewing dataset and component licenses as part of our commercialization and compliance process. We plan to continuously improve the models through a feedback-driven development cycle: monitor production performance and failure cases, collect appropriately consented real-world data, improve dataset diversity and quality, retrain and validate models, and benchmark new versions before deployment. We will track accuracy, precision, recall, F1-score, per-class performance, latency and reliability while specifically monitoring performance across diverse skin tones and image conditions. We are India-first and globally oriented. India is our initial market because of its large smartphone population, growing beauty and digital-health adoption, and significant access gap in personalized dermatology. We plan to expand internationally once the product, clinical validation, regulatory requirements and go-to-market model are established for each target market. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/xOBL9gpkOQxn-PitchDeckCare.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/xOBL9gpkOQxn-PitchDeckCare.pdf https://drive.google.com/file/d/1MRLcPIZ4y2IUPOdEdMdR0RKLJsAd1xqh/view?usp=sharing Yes. Care+ aims to make personalized skin health guidance more accessible and affordable, particularly for people who face barriers to timely dermatology care. We are using AI to provide instant skin insights and personalized guidance, with a long-term vision of combining AI with certified dermatologists to expand access to quality skin health services. NA NA Care+ is our second venture as a founding team. We have known each other for over 9 years and previously built Reboot, a laptop repair business, together in 2022. With Care+, we have combined our technical, product, marketing, and business strengths to build and launch the product end-to-end. We are currently focused on user growth, product-market fit, and preparing Care+ for scale. checked
Aug 9, 2026 @ 11:05 PM Swetal Dindod swetal@neevnaav.com https://www.linkedin.com/in/swetal-dindod-937971153/ +917042592169 Technical and QMS Lead We are working on this idea since last 25 months. We started a shared and collective goal of improving the wellness and nutrition for the athletes and working professionals. We have been collaborating directly on lipid-protein encapsulation, HPLC retention validation, and bench-to-pilot scale-up of our functional nutrition matrix. 2 Our biggest strength is our unique intersection of advanced food/biotech formulation science and rapid commercial execution. While standard market players lose 85–90% of their actives to first-pass metabolism, our proprietary lipid-protein encapsulation architecture achieves 67% bioactive retention after n-hexane treatment (validated via HPLC)—delivering a 4x higher bioavailability multiplier. We possess the rare internal capability to move from molecular stability testing to clean-label, high-caloric functional matrices (e.g., date/monk-fruit sweetened, zero-refined-sugar) entirely in-house, completely bypassing traditional nutraceutical formulation bottlenecks. Neevnaav Pvt Ltd https://www.climbeat.com Vadodara A biotech-led functional nutrition platform engineered to eliminate the systemic absorption failure of conventional nutraceuticals, Ayurveda, and sports supplements. We develop clean-label, high-performance matrices utilizing advanced lipid-protein encapsulation to bypass first-pass metabolism, delivering targeted metabolic, cognitive, and stress-mitigation outcomes for high-performers and endurance athletes. Standard nutraceuticals, traditional pills, and Ayurvedic solutions suffer from a catastrophic bioavailability bottleneck—losing 85% to 90% of their active ingredients to first-pass hepatic metabolism and gastric degradation. Simultaneously, working professionals and athletes facing chronic lifestyle stress, sleep disruption (quantified by PSQI), and cognitive fatigue are forced to rely on unverified supplements, sugary bars, or synthetic nootropics that fail to cross physiological barriers efficiently or cause severe gastrointestinal distress. We have engineered a proprietary lipid-protein encapsulation delivery system integrated into a clean-label functional matrix (e.g., a high-density, 438 kcal per 50g format sweetened exclusively with dates and monk fruit, completely free of refined sugars and synthetic preservatives). Targeted Health Outcomes: Formulated with clinical adaptogens and nootropics to drive measurable stress reduction (marked by PSS), optimize sleep architecture (PSQI), and enhance working memory. Biotech Delivery: The matrix protects active botanicals through the harsh gastric environment, ensuring systemic absorption and maximizing cellular uptake. The Absorption Moat: While standard market alternatives max out at 10–15% bioactive retention, our encapsulation technology achieves 67% bioactive retention after rigorous $n$-hexane treatment, fully validated via HPLC analytics (delivering a validated 4x multiplier in systemic bioavailability).Clean-Label Structural Synergy: We achieve superior pharmacokinetic delivery without chemical surfactants, synthetic preservatives, or artificial masking agents—utilizing a food-grade lipid-protein scaffold that scales seamlessly in commercial manufacturing. Users Revenue, Pilots Endurance Athletes & Triathletes: High-performance individuals requiring rapid, high-rate caloric replenishment and stress mitigation without gastrointestinal distress or systemic crash. High-Stress Corporate Professionals & Founders: Performance-driven individuals suffering from lifestyle-induced sleep degradation, cognitive fatigue, and chronic cortisol elevation who demand clinical-grade nootropics and adaptogens without synthetic fillers or refined sugars. $180+ Billion (Global Functional Food and Nutraceuticals Market). $15+ Billion (Global Sports Nutrition, Bioavailable Supplements, and Nootropic Functional Foods Market). $45 Million (Initial capture of high-intent endurance athletes, triathletes, and premium biohacking professionals across Tier-1 Indian metropolitan hubs and direct-to-consumer digital channels over 3 years). Direct-to-Consumer (D2C) E-Commerce & Subscription: High-margin recurring subscription model for monthly functional nutrition and bioactive fuel boxes. B2B / B2B2C Partnerships: Direct integration into elite endurance coaching academies, triathlon training camps, marathon ecosystems, and corporate wellness programs. Traditional Supplement & Gel Brands: (e.g., Maurten, GU Energy, Fast & Up) — Limitation: High sugar, zero advanced bioavailability protection, standard first-pass metabolism loss. Functional Food & Energy Bar Brands: (e.g., RXBAR, RiteBite/Max Protein) — Limitation: Lack clinical adaptogenic nootropic profiling, low bioactive retention, often rely on dates/syrups without targeted cellular delivery systems. Performance Authority Marketing: Deep integration with elite endurance coaches, marathoners, and triathletes who validate the 4x bioavailability and HPLC-backed retention metrics. Data-Driven Digital Acquisition (Performance Funnels): Targeted community building in high-performance, biohacking, and endurance sports networks highlighting our science-first formulation over standard marketing fluff. Phase 1 (Niche Domination): Launch directly to endurance athletes and triathletes through targeted beta-testing, grit-testing in high-intensity racing environments, and strategic partnerships with elite endurance coaching camps. Phase 2 (Horizontal Expansion): Scale via D2C e-commerce into the broader high-stress corporate professional and longevity/biohacking community using clinical validation data (PSQI sleep tracking, PSS stress scores) as the primary conversion hook. To build the category-defining biotech-led functional nutrition standard, replacing unverified traditional supplements and low-absorption nutraceuticals globally with scientifically engineered, hyper-bioavailable delivery systems that measurably optimize human cognitive and physical endurance. Yes 300000 Yes To leverage institutional validation, regulatory and scientific mentorship, and specialized deep-tech infrastructure to scale our lipid-protein encapsulation platform from pilot batch validation to commercial market entry. IITACB’s strategic location provides the ideal launchpad to commercialize our HPLC-validated, high-bioavailability functional nutrition matrix for endurance athletes and high-stress professionals. Complete pilot-to-commercial scale-up optimization for our clean-label, high-density functional nutrition matrix. Establish formal clinical or field-testing partnerships with elite endurance training academies to track physiological metrics (PSS, PSQI). Secure institutional angel/seed investor connections to accelerate our go-to-market distribution across Tier-1 metropolitan hubs. Yes (or hybrid, depending on your physical location and ability to utilize physical presence). The Bommasandra industrial belt offers immediate proximity to advanced contract manufacturing, chemical/pharmaceutical ingredient suppliers, and food-processing packaging houses. We will leverage this ecosystem to transition our bench-scale HPLC-validated formulations into industrial-scale production. IITACB will help bridge the gap by providing localized regulatory guidance, expert chemical engineering mentorship, and direct access to Bangalore’s vast network of high-performance athletes, corporate wellness channels, and deep-tech investors. Yes We will utilize the physical incubation and co-working space to house our core founding and formulation team, run collaborative R&D alignment sessions, and conduct face-to-face mentorship and investor pitch meetings. Having a permanent physical anchor within the Bommasandra industrial ecosystem allows us to seamlessly coordinate between laboratory formulation trials, supply chain partners, and commercial pilot rollouts. Yes Core engine Our technical architecture centers on a proprietary lipid-protein encapsulation matrix rather than traditional software stacks. It utilizes food-grade biopolymer scaffold assembly, controlled-shear phase dispersion, and targeted thermal-emulsion processing. Formulation stability, active botanical dispersion, and molecular binding kinetics are modeled and optimized using analytical chromatography (HPLC) and physicochemical stress-testing frameworks (thermal, moisture activity, and $n$-hexane resistance degradation assays). We possess proprietary formulation datasets linking specific lipid-protein ratios to active botanical stabilization and systemic absorption rates. Specifically, our empirical data maps how our encapsulation matrix achieves 67% bioactive retention after rigorous $n$-hexane treatment (a 4x multiplier compared to standard 10–15% market baselines), giving us a locked blueprint for high-bioavailability functional delivery. Our defensibility lies in our trade-secret encapsulation mechanics and analytical validation. While competitors rely on surface-level marketing and standard bulk-ingredient blending that suffers from 85–90% first-pass hepatic degradation, our matrix is empirically proven via HPLC to protect active nootropics and adaptogens through gastric transit, creating a high barrier to entry for imitation products. We evaluate our technology via quantitative biochemical and physiological metrics:Bioactive Retention Rate: Measured via HPLC analysis before and after simulated gastric stress and n-hexane treatment (targeting our baseline > 67% retention vs. standard 10–15%).Efficacy & Stress Modulation: Tracked via validated human biometric markers including Perceived Stress Scale (PSS), Pittsburgh Sleep Quality Index (PSQI) scores, and working memory performance benchmarks during high-exertion/high-stress beta trials. For consumer data (such as beta-tester physiological tracking metrics like PSQI and PSS scores), we comply strictly with digital privacy frameworks and data protection standards. For product safety, we adhere to stringent food-grade manufacturing compliance, rigorous heavy-metal and microbial testing protocols, and complete transparency of clean-label ingredient sourcing. Government initiatives promoting domestic functional food manufacturing, nutraceutical R&D subsidies, and the 'Make in India' ecosystem support our localized sourcing, formulation scaling, and export capabilities. Regulatory risks are minimal and standard to the health-food and nutraceutical sector, primarily involving FSSAI compliance for functional ingredients and health claims substantiation. We mitigate this proactively by maintaining rigorous analytical HPLC data logs and adhering strictly to established food-safety and labeling standards. At 10x scale, our manual bench-scale high-shear mixing and lipid-protein emulsion processing would face throughput bottlenecks, risking batch-to-batch micro-viscosity variation. Scaling requires transitioning from pilot batching to automated, continuous-flow industrial homogenization equipment to maintain our exact structural matrix and HPLC retention integrity. Yes. Our core in-house team combines specialized expertise in food science, analytical chemistry, pharmacokinetics, and formulation engineering, holding direct technical capabilities in chromatography (HPLC), emulsion stabilization, and functional nutrition scaling. We utilize proprietary, in-house generated formulation datasets, chemical stability logs, and HPLC chromatography profiling data (fully owned IP). We reference open-access peer-reviewed pharmacological literature regarding SGLT1/GLUT5 transport kinetics and adaptogenic bioavailability pathways to guide structural design. By continuously iterating our lipid-protein ratios based on longitudinal HPLC stability testing and real-world biometric feedback loops from elite endurance athletes and high-stress professionals. We systematically optimize shelf-life, taste profile (using clean-source dates and monk fruit), and cellular absorption pathways. Both. (Initial market entry focused on Tier-1 Indian metropolitan hubs and endurance circuits, scaling rapidly into global export markets across North America and Europe where premium functional nutrition and biohacking demand is surging) 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/JxfBm7klthHn-Climbeat-Biotech-Nutrition-Pitch-Deck-July-2026.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/JxfBm7klthHn-Climbeat-Biotech-Nutrition-Pitch-Deck-July-2026.pdf Yes. We are fundamentally addressing the lifestyle-health epidemic caused by chronic stress, sleep degradation, and cognitive fatigue. By replacing low-absorption, synthetic, and high-sugar supplements with a scientifically validated, high-bioavailability functional nutrition platform, we enable high-performers, professionals, and endurance athletes to achieve peak physical and mental longevity sustainably. Yes, ST women entrepreneur NA Our platform successfully bridges the gap between traditional food matrices and advanced biotech delivery. With our core retention metrics already validated via HPLC, we are positioned to scale rapidly out of the Bommasandra industrial corridor into national and global markets. checked
Aug 9, 2026 @ 8:06 PM Dr. Kailash Chandra Panda kcpanda@rediffmail.com https://www.linkedin.com/in/kailash-chandra-panda-50719719/ http://NA +91-9900934499 Dr. Kailash Chandra Panda - CEO, Dr. Subhash Deorao Hiwase - CTO We were doing Ph.D. at IIT Kharagpur . After that we were having short interaction about our organisation, our roles and responsibilities etc.. For this project we were working since 2 to 2.5 years to identify, define and develop the concept All It is a team of like-minded and self-motivated people with rich experience in executing advanced aerospace and high-tech projects. Each team member has expertise in dealing with various multinational and Indian OEMs. Most of the team members have also contributed significantly towards research and development related projects for different Aerospace organizations. Reeyam Engineering and Technology Pvt. Ltd. https://www.reeyam.com/about Bangalore We are developing high altitude and long endurance(HALE) UAV which will be used as high altitude pseudo satellite (HAPS) for Indian ISR and communication requirement At present not a single company in India has made a HAPS system which can carry a payload of 25KG and fly for more than 5 days at an altitude of 20KMs. Reeyam’s High-Altitude Platform System (HAPS) can act like a “stationary satellite” flying very high in the sky for long periods, helping both defense and civilian agencies. From this height, it can continuously watch large areas to support border security, coastal monitoring, disaster response, and emergency management by providing clear images and real-time information. At the same time, it can serve as a powerful communication tower in the sky, delivering internet and secure connectivity to remote villages, mountains, offshore areas, or regions affected by natural disasters where ground networks may fail. Because it can stay in one place for weeks or months and be brought back for upgrades and reuse, Reeyam’s HAPS offers a cost-effective and reliable way to strengthen surveillance and communication across the country. Reeyam Engineering and Technology’s Tri-Hybrid HALE UAV-HAPS can deliver persistent, wide-area Intelligence, Surveillance, and Reconnaissance (ISR) and resilient communication by operating in the stratosphere (18–22 km), bridging the gap between satellites and terrestrial networks. As a quasi-stationary platform, Reeyam’s HAPS can host multi-sensor ISR payloads such as EO/IR cameras, SAR, AIS/ADS-B receivers, and lightweight ESM suites to provide continuous border monitoring, maritime domain awareness, disaster assessment, and tactical battlefield intelligence with higher revisit rates and lower latency than LEO satellites MVP Testimonials Telecommunication service providers, Indian Airforce, Army and Navy, Oil PSUS, NDMA and SDMA etc.. 5.7 Billion USD (Globally) 0.35 Billion USD ( For India ) 0.2 Billion USD ( For India ) Mission as a Service and Data as a Service Satellite service providers B2B direct sales, Partnerships & ecosystem, Technical-led marketing Direct Enterprise Sales, Partner Eco system, Direct Lease To emerge as a market leader in the HALE UAV and HAPS domain in India, we believe success will be defined by a combination of technological maturity, operational reliability, scalable business models, and strong ecosystem partnerships REEYAM ENGINEERING AND TECHNOLOGY PRIVATE LIMITED is incorporated on this SIXTEENTH day of JULY TWO THOUSAND TWENTY FIVE under the Companies Act, 2013 NA Yes For raising fund through equity Fund for making our next version of the prototype Yes Bommasandra in Bangalore can be a very strong manufacturing and customer-acquisition, collaboration base for Reeyam, particularly because Reeyam is working across BLDC motors, aerospace/HALE UAVs, HAPS and advanced engineering. Reeyam–IITACB Aerospace & Electric Propulsion Program Expectations: 1. Incubation/workspace 2. Access to maker/prototyping facilities 3. 5–10 IIT alumni mentors 4. Introductions to 20 potential industrial customers 5. Introductions to 5 aerospace/defence companies 6. Technical collaboration with IIT faculty 7. Investor introductions 8. Manufacturing-partner introductions 9. Joint technical workshops 10. Support for government/defence/aerospace funding applications No NA Yes Core engine Will be explained in detail after NDA is signed NA At Reeyam Engineering & Technology, we are not just building another solar HALE UAV.” We are planning to develop an integrated technology stack + mission architecture + manufacturing capability that is difficult to replicate. Reeyam HAPS USP 1. Ultra-high aerodynamic efficiency 2. Indigenous high-efficiency propulsion 3. Integrated solar–fuelcell-battery–propulsion energy management 4. Modular HAPS architecture 5. Stratospheric-specific structural technology 6. Autonomous station-keeping Right now not a single company in India has commercially manufactured HALE UAV HAPS. There are few companies trying this but all are in technology development stage. Reeyam Engineering & Technology Pvt. Ltd. will follow a privacy-by-design and security-by-design approach across its products and services. Customer, operational and system data will be collected only when required, with appropriate access controls, encryption, secure authentication, role-based permissions and regular security reviews. Sensitive data will be stored securely and access will be restricted to authorized personnel on a need-to-know basis. Reeyam will comply with applicable Indian data-protection, cybersecurity, aviation/UAV and industry-specific regulations, including the Digital Personal Data Protection framework and other applicable statutory requirements. Wherever required, appropriate customer consent, data-retention policies, audit trails, contractual confidentiality provisions and data-processing agreements will be implemented. For UAV/HAPS and engineering products, Reeyam will additionally protect telemetry, navigation, flight, payload and engineering data through secure communication protocols, controlled interfaces, authentication, encrypted storage/transmission and controlled software/firmware access. Third-party components and cloud services will be evaluated for security and compliance before integration. Yes. For Reeyam Engineering & Technology, several Indian government policy interventions can directly support the business, particularly because of its focus on BLDC motors, aerospace/HALE UAVs, HAPS, and advanced engineering products. • Make in India / Atmanirbhar Bharat: Supports domestic manufacturing of motors, UAV subsystems and aerospace components and can create procurement opportunities. • Startup India & DPIIT benefits: Tax, IP, procurement and compliance support for eligible startups. • Defence & aerospace policies: iDEX, Defence Production Policy and positive indigenisation lists can create opportunities for indigenous UAV and propulsion technologies. • IN-SPACe policies: Relevant to Reeyam's HAPS/HALE technologies where they can complement satellite and space-based communication/remote-sensing systems. • Government R&D grants: Programs through DST, MeitY, DRDO, Technology Development Board and state startup agencies can support technology development and prototyping. • PLI / manufacturing incentives: Depending on the specific product and eligibility, manufacturing-oriented schemes can reduce the cost disadvantage of domestic production. Yes. For Reeyam Engineering & Technology, particularly its HALE UAV/HAPS, autonomous aircraft, BLDC motors and associated aerospace systems, the main regulatory risks are: 1. DGCA / MoCA certification – UAV type certification, UIN, flight permissions and operational restrictions could delay commercial deployment in India. 2. Autonomous-flight restrictions – Regulations governing BVLOS and autonomous operations could limit the business model until approvals and operational frameworks mature. 3. Cybersecurity & data regulations – Autonomous UAVs collecting imagery or other data can create obligations concerning cybersecurity, data protection and potentially sensitive geospatial information. If Reeyam Engineering & Technology scales 10×, the biggest risk is not engineering—it is that the organization, manufacturing, cash flow, and quality systems need to be addressed to scale at the same rate as sales. Relevant Team Member Expertise and Collaboration Srn Team Member Expertise & Collaboration Remarks 1 Our Team has got Profound Experience on Mission Critical Projects while working with Prestigious Organizations such as - (a) ISRO, SAC, ADA,HAL, NAL, GTRE, ADE, BDL, DLRL, DRDL, RCI, CFEES, ADRDE, ARDE, R&DE, etc. (b) Airbus, Boeing, GE, Rolls Royce, EADS, Thales, Embraer, TAS, etc. (c) Jio Connects, Reliance, Airtel, etc. (d) ONGC, IOCL, BPCL, MGL, RIL, L&T, Lamprell, Reliance, Oil India, etc. Exposure to Vision, Mission and Work Culture of Premier Organizations on their Innovative and Visionary Projects 2 The Team has got Proven Track Record of Delivering Products to their Clients while working with Past Organizations in – (a) HALE UAV Platform and Electric Propulsion System Design (b) Carbon Fiber Composite Wing, Solar HALE UAV Platform with wingspan of 15m for European market (c) Control System Design And, team has got extensive hands-on expertise on the following technologies: (a) Solar UAV Design along with Fuel Cell System Design (b) Phased Array Antenna Design along with Communication Payload Design (c) Earth Observation Payload (EO, IR & SAR) Design (d) Fusion of EO+IR Payloads, Fusion of IR+SAR Payloads The team has already executed a project on HALE UAV Platform while working in their previous organization, and delivered the product as per customer requirement 3 Partnership with leading Institutions like: (a) IITs, IISc, NITs and leading engineering colleges in Bangalore (b) Major aerospace component manufacturers across Pan-India. (c) It will help in designing high aspect ratio flexible composite wings and advanced guidance and navigation requirement For Incubation, Consultancy Support, Research & Development 4 Collaboration with IN-Space, 3GPP, HAPS Alliance, Near Space Labs, Sceye, etc. For Technology knowhow, Technology Transfer Reeyam uses a combination of open-source software, commercially licensed engineering tools, third-party hardware components and internally developed proprietary datasets, algorithms, engineering models and system designs. The company's core aircraft, propulsion, motor-design and system-integration is developed and owned by Reeyam, while third-party open-source and commercial components are used under their respective licenses. Reeyam will continuously improve technology performance through a structured cycle of design–test–measure–learn–redesign. We will use flight and field-test data, simulation/CFD, digital engineering, and customer feedback to identify performance gaps and optimize aerodynamics, propulsion, energy efficiency, reliability, and system-level performance. We will also continuously benchmark our technology against global solutions, adopt advanced materials, electronics, AI-based analytics and manufacturing methods, and maintain rigorous validation and qualification processes to progressively improve efficiency, endurance, payload capability, reliability, and cost. We are building the HALE UAV based HAPS for both Indian as well as global market. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/e0rNy9dqhtIk-12-1-9-Reeyam_Sharable_V1.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/e0rNy9dqhtIk-12-1-9-Reeyam_Sharable_V1.pdf http://NA Reeyam Engineering & Technology is a mission-driven deep-tech startup focused on developing indigenous, energy-efficient aerospace and engineering technologies. Our mission is to enable sustainable aerial connectivity and advanced mobility through HALE UAVs, HAPS platforms, high-efficiency propulsion systems, and other precision-engineered technologies, with a strong emphasis on reducing energy consumption, increasing endurance, and lowering the cost of deployment. NO NA NA checked
Aug 9, 2026 @ 6:23 PM Dibyalochan Sahoo dibyalochan.sahoo@aninone.com https://www.linkedin.com/in/dibyalochan-sahoo-0616a2177/ http://aninone.com +917683934947 Solo Founder: Dibyalochan Sahoo — IIT Madras, Batch of 2023, prior 4 year work exp in AI I am the solo founder. We are a 3-member team. We began the work officially from Oct -2025 and the company got incorporated in Nov-2025. Currently, it is bootstrapped and we are in a full product development cycle. 1 Our biggest strength is the exceptional blend of deep technical expertise and unstoppable execution. We have a highly qualified team of IIT graduates and experienced computer scientists capable of building a complex engineering design and simulation platform and service. The founder brings strong product development experience, business insight, relentless focus—and the kind of driven, almost unreasonable determination needed to take this product all the way. Together, we combine technical excellence, industry knowledge, and a shared passion to build India’s first homegrown engineering design and simulation suite. Anin Technologies Private Limited aninone.com Bangalore An AI-Native Full-Stack Hardware Engineering OS for Product Development Teams Most businesses—especially MSMEs—cannot afford the high-cost, outsourced engineering design and simulation software currently dominating the market. There is no Indian homegrown engineering design and simulation company, creating a major gap in accessibility, innovation, and affordability. Both MSMEs and large industries across construction and manufacturing struggle due to dependence on outsourced product and design teams—resulting in delays, high costs, security concerns, and lack of control over the development process. An AI-native digital engineering platform that unifies CAD, CAE, CAM, and manufacturing into a single workflow. Built for MSMEs and large industries, the platform is providing a globally benchmarked alternative to expensive and fragmented legacy solutions. It reduces design-to-manufacturing back-and-forth, repetitive work, and information loss across disconnected tools. AI assists with design decisions, automates repetitive tasks, and identifies issues earlier—helping engineers reach validated, manufacturable designs faster. The long-term vision is to build a homegrown Indian engineering technology platform with global capabilities and global ambitions, serving customers across manufacturing, construction, and other engineering-intensive industries Our differentiation comes from combining CAD, CAE, CAM, manufacturing, and AI into a unified engineering workflow, rather than offering disconnected tools. AI is built into the engineering process to reduce repetitive work, design iterations, and back-and-forth between teams. Over time, the platform will build a proprietary layer of engineering workflows, design data, manufacturing insights, and AI models, creating a growing technical and data advantage. Our focus on MSMEs and underserved engineering markets, combined with a modern, accessible user experience and globally scalable architecture, provides a strong entry point against expensive legacy solutions. MVP MSMEs , Large industries, manufacturing, aerospace,defense, semiconductor, training center, educational institution $200Bn $30-50B $150-300Mn Subscriptions, usage based, outcome based, design services Autodesk, Dassault systems, Ansys Our customer acquisition will combine direct sales and digital channels: Direct outreach to MSMEs and engineering companies. Product-led acquisition through our online platform and website. Technical content, YouTube design tutorials, blogs, and social media. Free training and subscriptions for students and institutes to build early adoption and future customer pipelines. Seminars and workshops for direct engagement and lead generation. Complete full product development and launch the first product in October 2027, initially targeting MSMEs and engineering teams in mechanical design and manufacturing. We will begin with early users and pilots, then expand through direct sales, partnerships, educational adoption, and product-led growth. What’s your long-term vision? Build a global Engineering Operating System, starting with a Mechanical Design OS and gradually expanding across CAD, CAE, CAM, and manufacturing. Over time, we aim to build greater control over the underlying kernels, algorithms, and engineering infrastructure, reducing dependence on third-party technologies. The platform will eventually expand beyond mechanical engineering into AEC, semiconductors, chemicals, and other engineering-intensive industries, creating a unified digital foundation for engineering design, simulation, and manufacturing. Nov-2025 NA Yes Networking with the investors and mentorship Networking with the investors and mentorship preference-Online Bommasandra and the broader Bengaluru industrial ecosystem provide access to a large concentration of manufacturing, engineering, automotive, and MSME companies, making it an ideal market for early customer discovery, pilots, and product validation. We plan to leverage this ecosystem to: Engage directly with manufacturing and engineering companies. Identify real-world CAD/CAE and manufacturing workflow challenges. Run early pilots and gather feedback before the full product launch. Build relationships with potential customers, partners, and engineering talent. IIT ACB can help by providing industry connections, mentorship, access to its network, and introductions to potential pilot customers and partners. This would help us validate the product with real industrial users and accelerate our transition from product development to commercial adoption. Yes We would use the incubator as our product development base, leveraging office, meeting, internet and computing facilities for building and testing our CAD/CAE platform. We would also leverage IITACB's network, mentorship, and industry connections for customer validation, partnerships, hiring, and investor outreach as we move toward product launch. Yes Core engine Hybrid architecture combining C++/native engineering kernels, WebAssembly, cloud/backend services, and a modern web frontend, designed to support CAD, CAE, AI, and collaboration. We are currently building our proprietary engineering workflows and datasets. Two CAD-related patent filings are in progress, with one already filed. Our differentiation is the unified CAD–CAE workflow with AI-assisted engineering, reducing the fragmentation and repetitive work between design and simulation. We evaluate modeling accuracy, operation success rate, regeneration time, simulation performance, stability, and resource usage, benchmarked against existing engineering workflows and tools. We follow secure-by-design principles, with controlled data access, encrypted data transmission, authentication, and secure storage. As the platform scales, we will align with applicable data protection and industry standards. Government initiatives supporting deep-tech, R&D, indigenous engineering software, manufacturing digitization, and startup innovation can significantly support our development and adoption. There are currently no major regulatory barriers to the core software product. We will comply with applicable data protection, cybersecurity, export-control, and industry-specific requirements as we expand. The primary scaling challenges will be compute-intensive CAD/CAE workloads, cloud infrastructure, storage, and concurrent users. Our architecture is being designed to scale these components independently. Yes. We have an in-house team working across CAD geometry, C++, WebAssembly, web technologies, engineering workflows, and AI/CAE, supported by domain expertise. We use a combination of open-source engineering libraries and internally developed code. Key components include Open CASCADE, C++, WebAssembly/Emscripten, and Three.js, used in accordance with their respective licenses. Our proprietary application logic, workflows, and IP are developed in-house. Through benchmarking, automated testing, real-world user feedback, performance profiling, and continuous improvement of algorithms and engineering workflows. Both. We plan to use India as an initial market for validation and adoption while building the platform from the beginning for global engineering and manufacturing markets. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/A65cAN2Equ2e-pitch-deck-Anin.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/A65cAN2Equ2e-pitch-deck-Anin.pdf https://drive.google.com/drive/folders/19Ek6UglbxtggYvcSS0gF1QAGgqLRKSZf?usp=drive_link Yes, we are building a mission-driven startup. Our goal is to capture the multi-billion-dollar global digital engineering market, serving construction, manufacturing, and heavy industries through innovative software products and services. We aim to elevate India’s engineering and design capabilities to a global level, creating homegrown solutions that compete internationally and drive industry-wide innovation. NA NA NA checked
Aug 6, 2026 @ 11:49 PM Shivam Panwar rajputshivam2800@gmail.com https://www.linkedin.com/in/shivam-panwar-151195266/ 8755681776 BlueForge is led by five full-time co-founders. Shivam Panwar (Co-Founder & CEO) is an IIT Kharagpur graduate and former TATA Boeing engineer, where his work on the paint booth and industrial management led directly to the idea; he brings an AI/ML background and drives the company's strategy and overall vision. Sangam Sahu (Co-Founder & CTO) comes from a robotics and product-R&D background and has already built magnetic painting rovers for gas and oil tankers, which de-risks the hardest part of the technology. Avinash Mishra (Co-Founder & COO) is from IIT Gandhinagar with experience in UAV field operations, and leads on-ground operations and deployment. Rahul Giri (Co-Founder & CIO) is an IIT Bombay graduate with a background in CFD and HPC, and is responsible for software development. Mukesh Jaiswal (Co-Founder & Business Lead) holds an MBA from IIM Mumbai leading go-to-market and partnerships The founding team has known each other since 2019. All of us except Sangam are from the same graduating batch, and Sangam, our CTO, is our college senior — so we've shared a campus and a network for years. That long association means we already understood each other's strengths, working styles, and how each of us holds up under pressure well before we started building together. It's a big part of why we've been able to move fast and trust each other's judgment at BlueForge. All Our biggest strength is that we've already built the hardest part. Our CTO, Sangam, has designed and built magnetic rovers that paint gas and oil-tanker hulls — so the core technical risk isn't a hypothesis we hope to solve, it's something a founder on this team has done before. Around that, the five of us cover the entire stack full-time: robotics hardware, software and controls, field operations and deployment, AI & ML, and go-to-market — which is exactly what a prep-plus-coat-plus-inspect-plus-data platform needs. Add a CEO who lived this problem first-hand running the paint booth at Tata Boeing, and a team that has known and trusted each other since 2019, and you get a group that can build the rover, put it to work in a real yard, and sell it — without depending on anyone outside the founding team for the things that matter most BlueForge NA Lucknow BlueForge (SkyOps Technologies LLP) is building India's first autonomous ship-hull robotics and predictive-maintenance platform for shipbuilding and ship repair. Our magnetic-crawler rovers surface-prep, coat and inspect ship hulls, and record every job as a verifiable data file — the Digital Hull Passport. We offer it as a service (robots-as-a-service, priced per square metre) rather than selling machines, with recurring annual maintenance and a data subscription on top Ship-hull surface preparation, coating and inspection is still done almost entirely by hand — workers hanging off scaffolding in clouds of grit and toxic overspray. It's slow, hazardous and inconsistent: up to 30% of the coating gets reworked, and every extra day a ship sits in dry dock costs the yard lakhs in lost revenue. Yards also face a shrinking pool of skilled labour willing to do this dirty, dangerous work. Globally, this prep-coat-inspect activity is a ~$48 billion-a-year market that remains largely manual. BlueForge's autonomous rovers climb the hull and take on the three hardest, most hazardous steps — grit-blasting to standard (SA 2.5), coating application, and inspection — holding constant, controlled parameters no human can sustain across a full shift. Every pass is logged into a Digital Hull Passport: surface-prep standard, dry-film thickness, coverage and ambient conditions, all time-stamped. The yard gets faster, first-pass-right, safer work; the shipowner gets a verifiable maintenance record; and each job converts into recurring revenue through annual maintenance contracts and the data subscription No one — Indian or global — delivers surface prep + coating + inspection + data on a single autonomous platform, as a service. Existing players do only one slice: blasting-tool crawlers (VertiDrive, Chinese makers), in-water cleaning robots, or inspection alone (Gecko Robotics built a $1.25B company on inspection data). Our defensibility rests on three things: four rover designs with patents in progress; a CTO who has already built magnetic painting rovers for gas and oil tankers, so the hardest technical risk is proven rather than theoretical; and a compounding data moat — the Digital Hull Passport becomes more valuable with every hull we service MVP Our primary customers are ship-repair and shipbuilding yards with dry docks — both commercial and naval/PSU yards (Cochin Shipyard, Mazagon Dock, Hindustan Shipyard, and private repair yards such as Vadinar), expanding later to Gulf and Singapore repair hubs. Shipowners and ship-management companies are secondary customers for the Digital Hull Passport and annual maintenance contracts, and marine-coating manufacturers are channel partners we co-sell with 75000 cr 13000 cr 1260 cr Three recurring streams. (1) Robotics-as-a-Service (RaaS) — priced per square metre of hull prepped, coated and inspected, so the yard pays with zero capex. (2) Annual Maintenance Contracts (AMC) — tiered plans for ongoing hull maintenance across a fleet. (3) SaaS — a subscription to the Digital Hull Passport data platform. We land with RaaS pilots and expand each account into recurring AMC + SaaS revenue No one offers prep + coating + inspection + data on a single autonomous platform as a service — competitors each do one slice. Surface-prep/blasting crawlers are sold as tools, not a service (VertiDrive in the Netherlands, Chinese crawler makers). In-water robots only clean the hull. Inspection-only players capture data alone — Gecko Robotics ($1.25 bn) globally, and Planys Technologies and EyeROV in India (underwater inspection). Our integrated, service-plus-data model is the whitespace between them and-and-expand from a beachhead yard: we start with a zero-capex RaaS pilot at an Indian yard (Cochin / SDHI), prove the dock-time and rework savings, then convert that account into AMC + Passport SaaS and grow yard by yard. We reach yards through coating manufacturers (co-sell), ship-management companies (fleet-wide AMC), class societies and incubators (trust and introductions), and direct business development, with naval/PSU yards as a later expansion Land → Expand → Scale. Land: a zero-capex RaaS pilot at a beachhead yard. Expand: convert to AMC + Passport SaaS and win 3–5 yard accounts across India. Scale: Gujarat, Goa and Kerala yard clusters, then Singapore and the Gulf. Partnerships with coating majors (e.g. Shalimar), ship managers and certifiers accelerate reach, and the whole strategy rides the tailwind of Maritime India Vision 2030 To become the global operating layer for hull maintenance — every ship's hull prepared, coated, inspected and monitored autonomously, with a living Digital Hull Passport that turns maintenance from reactive to predictive. Starting India-first, we aim to define and lead the category of autonomous surface operations and predictive maintenance for the maritime industry worldwide Incorporated. The company is registered as SkyOps Technologies LLP, a Limited Liability Partnership in India (BlueForge is our operating brand) NA Yes As a founding team of IIT alumni (IIT Kharagpur, IIT Gandhinagar, IIT Bombay) building deep-tech hardware, IITACB is a natural home for us — it combines the IIT alumni network with Bengaluru's position as India's deep-tech and robotics capital. We're applying for three things specifically: hands-on mentorship from operators and technologists who have scaled hardware ventures; investor connections to close our current round; and access to Bengaluru's manufacturing and engineering ecosystem to build and scale our rovers. The alumni-led, deep-tech-friendly nature of IITACB fits a venture like ours better than a generic accelerator Concretely: (1) advance our rovers from TRL-4 to a pilot-ready system; (2) secure our first paid yard pilot; (3) close our ₹1.56 Cr round through the programme's investor connects; (4) establish manufacturing and component-sourcing partnerships in the Bengaluru ecosystem to bring down rover build cost and lead time; and (5) sharpen our GTM and unit economics with mentor guidance. We'd also value support on our IP/patent filings, which are currently in progress YES Our rovers are hardware — mechanical assemblies, motors, electronics, sensors and controls — so Bommasandra's dense precision-manufacturing, electronics and engineering base is directly useful for rapid prototyping, component sourcing, and eventually contract manufacturing to scale rover production cost-effectively. Bengaluru also gives us access to robotics and embedded-systems talent, a deep investor pool, and proximity to defence and aerospace institutions (HAL, BEL, DRDO labs) that matter for our naval/defence-yard expansion. IITACB can help us convert this proximity into real partnerships — introductions to manufacturers and suppliers in Bommasandra, to mentors who've built hardware here, and to investors — turning a location advantage into build speed and lower cost. Yes We'd use the workspace as a Bengaluru base for our core hardware and business team, and the prototyping/workshop facilities for rover assembly, iteration and testing. Beyond desks, the real value is on-site access to mentors and the alumni network, meeting rooms for investor and shipyard conversations, and the incubator's demo-day and investor-connect events — plus introductions into the Bommasandra manufacturing ecosystem for our supply chain Yes Core engine BlueForge has four layers. (1) Robotic layer: magnetic-crawler rovers that adhere to and traverse a steel hull, carrying tooling for grit-blasting, coating application and inspection. (2) Perception & autonomy: onboard sensors and edge compute for hull navigation, path-planning and surface mapping, so the rover covers the hull with controlled, repeatable parameters. (3) Process control: closed-loop control of blast standard, coating film thickness and application speed, with live sensing (DFT, environmental conditions). (4) Data layer — the Digital Hull Passport: every pass is logged and synced to a cloud platform that stores a time-stamped record of prep standard, film thickness, coverage and condition, and feeds predictive-maintenance analytics Today, honestly, limited — we are pre-deployment. Our advantage is a compounding one: every hull we service generates a proprietary dataset — blast profiles, dry-film-thickness maps, coating type and condition over time — through the Digital Hull Passport. Over many hulls this becomes a hull-condition dataset no competitor holds, which sharpens our predictive-maintenance models and creates a widening moat as we scale Four things: (1) integration — no one else does surface prep + coating + inspection + data on one autonomous platform as a service; competitors each do a single slice; (2) IP — four rover designs with patents in progress; (3) proven capability — our CTO has already built magnetic painting rovers for gas and oil tankers, so the hardest tech risk is de-risked; (4) a compounding data moat and the switching costs of an embedded, recurring service relationship with each yard Coating quality: dry-film-thickness uniformity (variance vs spec), adhesion (pull-off, ASTM D4541), surface-prep standard achieved (SA 2.5), and first-pass-right rate / rework % (baseline: up to 30% manual rework). Productivity: m² prepared/coated per hour vs manual. Safety: hazardous man-hours removed. Commercial: dock-time reduction per vessel. Reliability: rover uptime, coverage %, and mean time between failures. We benchmark against both the manual baseline and single-function robots Our data is industrial and operational (hull condition, yard activity), not consumer personal data, so PII exposure is minimal. Hull and fleet data can be commercially sensitive — and, for naval vessels, security-sensitive — so we treat customer data as owned by the yard/shipowner, with role-based access, encryption in transit and at rest, and strict confidentiality. For defence/naval work we will comply with data-localisation and security-clearance requirements, keeping such data segregated and, where required, on-premise Strong tailwinds: Maritime India Vision 2030 and the Maritime Amrit Kaal Vision 2047 (top-5 shipbuilding, 5% global share); the Shipbuilding Financial Assistance Policy and the ₹25,000 cr Maritime Development Fund; Make-in-India and manufacturing incentives; iDEX / defence-indigenisation routes for naval yards; and green-shipping/emissions norms that raise the value of well-applied, well-documented coatings. We were also selected in Round 1 of the Adani Vande Bharatam mission Class-society approval and certification for robotic coating application on classed vessels; slow naval/defence procurement and security-clearance cycles; hazardous-area and worker-safety/environmental regulations around blasting dust and solvent coatings (largely a tailwind, but a compliance burden); and yard safety certification for autonomous equipment. None are blockers, but each affects timelines. The software/data platform scales fine; the strains are physical and operational: (1) rover manufacturing and component supply chain; (2) hiring and training enough field operators/service engineers; (3) simultaneous support across many yards and geographies; (4) consumables logistics (grit, coatings); (5) quality consistency across a larger rover fleet; and (6) working capital, since a RaaS model is capex-heavy to deploy fleet ahead of revenue. Our plan addresses these through contract manufacturing (e.g. via the Bengaluru/Bommasandra ecosystem), a trained-operator pipeline, and staged geographic rollout Yes. Our CTO leads robotics and has built ship-hull rovers before; our CIO (IIT Bombay, CFD/HPC) leads software and controls; our COO brings UAV field-operations experience for real-world deployment; and our CEO brings an AI/ML and manufacturing background (ex-Tata Boeing). All five founders are full-time, covering hardware, software, field ops and GTM in-house Owned/proprietary: our rover mechanical and system designs (four patents in progress), our process-control software, and the Digital Hull Passport platform. Standard, permissively-licensed open-source is used in the stack where sensible; hardware components (motors, sensors, edge compute) are sourced off-the-shelf and integrated. We do not use any GPL-encumbered or restrictively-licensed code in our proprietary modules A data flywheel: every hull serviced feeds blast, coating and inspection data back into our models to improve navigation, path-planning, defect detection and predictive maintenance. We push over-the-air software updates across the fleet, iterate rover hardware on a regular revision cycle, and capture real coating-performance outcomes over time to refine our recommendations and tighten quality Both — India-first. We start with Indian yards as our beachhead (aligned with Maritime India Vision 2030), then expand to Singapore and the Gulf and, over time, to global repair and newbuild hubs. The problem is universal; India is where we prove and scale it first 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/QwvOG6pyeJ11-IIT.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/QwvOG6pyeJ11-IIT.pdf Yes — impact is built into what we do, not bolted on. The most direct impact is human: hull surface prep and painting is one of the most dangerous, toxic jobs in any shipyard — workers spend hours grit-blasting and spraying solvent coatings off scaffolding, exposed to airborne grit, fumes and fall risk, and the long-term respiratory toll is real. Our rovers exist to take people out of that work. Much like robots have been used to end manual scavenging, we want the most hazardous parts of hull maintenance done by machines, so the humans move to safer, higher-skilled roles operating and supervising them. This isn't abstract for us — our CEO saw this problem first-hand running the paint booth at Tata Boeing. There's an environmental dimension too. Manual application wastes up to a third of the coating in rework, with the paint, solvent and grit waste that implies; doing it right the first time cuts that waste and the associated VOC emissions. And a properly prepared, well-coated hull fouls less and burns less fuel at sea — so better hull maintenance is quietly a lever on shipping's carbon footprint. Finally, it's a mission of national capability. This is India-built maritime deep-tech, aligned with Maritime India Vision 2030 and Atmanirbhar Bharat — helping Indian shipyards become globally competitive and reducing dependence on imported technology in a strategically important, defence-adjacent sector. Safer workers, less waste, and a stronger Indian maritime industry — that's the impact we're building toward. NA NA checked
Aug 6, 2026 @ 11:48 PM Abhishek Sohanlal Paliwal abhishekpaliwal473@gmail.com https://www.linkedin.com/in/abhishek-paliwal-42b6b0286?utm_source=share_via&utm_content=profile&utm_medium=member_android http://NA 7572990350 Abhishek Paliwal – Founder & CEO of ILAAV, responsible for overall strategy, business development, partnerships, fundraising, and driving the organization's vision to create sustainable solutions for rural communities. Komal Chaudhari – Co-founder & Chief Marketing Officer (CMO), leading marketing strategy, brand development, community engagement, outreach campaigns, and communication with stakeholders. Dharya Patwa – Co-founder & Chief Financial Officer (CFO), responsible for financial planning, budgeting, business compliance, resource management, and ensuring the financial sustainability of the venture. We first met as classmates while pursuing our BBA. During one of our academic activities, we were given the opportunity to present an innovative business idea. Driven by our shared interest in solving real-world problems, we developed and presented the concept that eventually became ILAAV. What started as a classroom project soon evolved into a mission to empower farmers and strengthen rural communities through technology and innovation. Since then, we have continued refining the idea, validating it with stakeholders, and building the venture together. We have been working as a team since 1 October 2024, combining our complementary skills in strategy, marketing, finance, and operations to transform ILAAV into a scalable social enterprise. All Our greatest strength as a team is our resilience, shared vision, and unwavering commitment to our mission. Since we started working together in October 2024, we have experienced both acceptance and rejection. Some opportunities opened doors for us, while others challenged us to improve. However, one thing has never changed—our belief that rural India has the potential to become a driving force of the nation's economy, and our commitment to making that vision a reality through ILAAV. We complement each other's strengths and maintain complete trust in one another. Whenever one team member faces setbacks or feels discouraged, the others step forward to provide support and keep the momentum going. We never allow individual challenges to affect the progress of the venture. Every decision is guided by our common purpose rather than personal recognition. Our ability to adapt, learn quickly, and stay united through every challenge has enabled us to build partnerships, engage with farmers, and continuously refine our solution. More than just co-founders, we are a team that shares responsibility, celebrates every milestone together, and remains committed to creating lasting social impact. We believe that this unity, resilience, and mission-first mindset are our greatest strengths and the foundation on which ILAAV will continue to grow. ILAAV (Innovative Land and Agricultural Advancement Venture) https://kronickeys.link/ilaav-portal/ (Underdevelopment) Mehsana ILAAV (Innovative Land and Agricultural Advancement Venture) is a rural development startup dedicated to improving the quality of life in rural India through innovation, technology, and community-driven solutions. We are building an integrated ecosystem through five focused verticals: KRUSTI, which empowers farmers with market access, government schemes, agricultural advisory, and digital services; ILAAV Shakti, which strengthens women through Self-Help Groups (SHGs), entrepreneurship, skill development, and financial inclusion; ILAAV Jal, which promotes access to clean drinking water and sustainable water management solutions; ILAAV Bhumi, which helps farmers efficiently manage fragmented agricultural land and improve land utilization; and ILAAV Arogya, which aims to improve access to affordable healthcare and health awareness in underserved rural communities. Together, these initiatives work towards one vision—to create self-reliant villages where every individual has access to opportunities, essential services, and a better quality of life Rural India faces interconnected challenges that cannot be solved by addressing agriculture alone. Farmers struggle to access fair markets, reliable agricultural guidance, government schemes, and modern technology, resulting in low incomes and dependence on intermediaries. Women in rural areas often have limited opportunities for entrepreneurship, skill development, and financial independence. Many villages continue to face inadequate access to clean drinking water, leading to health and livelihood challenges. Fragmented landholdings reduce agricultural productivity and make efficient land management difficult. Additionally, rural communities often lack affordable and accessible healthcare services, forcing people to travel long distances for even basic medical care. These issues together contribute to poverty, unemployment, migration to cities, and slow rural development. We believe that rural communities do not lack potential—they lack equal access to opportunities, resources, and integrated support systems. ILAAV exists to bridge these gaps and enable villages to become self-reliant, economically stronger, and better connected to the opportunities of the modern world. ILAAV is building an integrated rural development ecosystem that addresses the interconnected challenges of agriculture, livelihoods, healthcare, water, and land management through five dedicated initiatives. KRUSTI, our flagship agritech platform, is designed as a one-stop digital companion for farmers. It provides AI-powered crop advisory, weather forecasts and real-time weather alerts, pest and disease alerts, government scheme discovery and application support, AI chatbot assistance, multilingual support with audio and video guidance, expert consultancy, market price insights, and an integrated marketplace where farmers can directly connect with verified buyers and sellers, reducing dependence on intermediaries. For farmers who are not comfortable using technology, our trained field agents provide on-ground assistance, ensuring that no farmer is left behind in the digital transformation. As the platform evolves, KRUSTI will continue to integrate additional services that simplify every stage of a farmer's journey—from planning and cultivation to selling and accessing government benefits. ILAAV Shakti empowers rural women by strengthening Self-Help Groups (SHGs), promoting entrepreneurship, providing skill development, improving financial literacy, and creating sustainable livelihood opportunities that increase household income and community leadership. ILAAV Jal focuses on improving access to clean drinking water and promoting sustainable water management through innovative, community-led solutions that improve public health while conserving water resources. ILAAV Bhumi addresses the challenges of fragmented agricultural land by enabling better land management, resource optimization, and efficient utilization of farmland, helping farmers improve productivity and maximize the value of their land. ILAAV Arogya aims to bridge the rural healthcare gap by promoting preventive healthcare, health awareness, digital health services, and affordable access to medical consultations and essential healthcare support. Rather than addressing these issues in isolation, ILAAV brings them together into one connected ecosystem. Our vision is to build self-reliant villages where farmers have access to technology, women have opportunities to lead, families have clean water and healthcare, land is utilized efficiently, and every rural citizen can access the resources they need to improve their quality of life. We believe that empowering rural communities in a holistic way is the key to building a stronger and more inclusive India. What makes ILAAV unique is that we do not see agriculture as the only challenge facing rural India—we see it as one part of a much larger ecosystem. Most existing solutions focus on a single problem, such as farming, market linkage, or advisory services. We believe that a farmer's well-being is directly connected to the availability of clean water, quality healthcare, women's empowerment, efficient land management, education, and access to opportunities. That is why ILAAV is being built as a holistic rural development ecosystem rather than a single-purpose platform. Our mission is not simply to increase farmers' income; it is to build villages where people can live with dignity, access essential services, and create opportunities without feeling compelled to migrate to cities. We envision rural communities where a young person chooses to stay not because they have no alternative, but because their village offers the opportunities, support systems, and quality of life needed to build a meaningful future. Our strength also lies in the way we build. We work closely with farmers and rural communities, understand their real challenges, and design solutions around their needs instead of assumptions. By combining technology with on-ground support through our agent network, strategic partnerships, and community engagement, we ensure that innovation reaches even those who are not digitally connected. We are not just building a startup—we are building a long-term movement for rural transformation. Our vision is to create villages that are economically self-reliant, socially empowered, and equipped with the essential services needed for a better future. We believe that when rural India thrives, India as a whole becomes stronger. MVP Pilots Our primary customers are small and marginal farmers, who constitute over 85% of India's farming population. We also serve Farmer Producer Organizations (FPOs), Self-Help Groups (SHGs), rural women entrepreneurs, agri-input suppliers, buyers, agribusinesses, and rural households seeking access to clean water, healthcare, and digital rural services. Our initial focus is on underserved rural communities where access to technology, markets, and essential services remains limited. TAM (Total Addressable Market) ₹8,400 Crore Represents India's digital agriculture, agri-advisory, rural marketplace, and rural digital services opportunity, with long-term expansion into integrated rural development solutions. SAM (Serviceable Addressable Market) ₹1,500–2,000 Crore Focused on small and marginal farmers, FPOs, SHGs, and rural communities across states where ILAAV will initially operate through KRUSTI and other ILAAV verticals. SOM (Serviceable Obtainable Market) ₹50–100 Crore Our achievable market over the next 3–5 years through phased expansion, strategic partnerships, agent networks, marketplace transactions, premium advisory services, and rural development initiatives. ILAAV follows a multi-revenue, freemium business model to ensure affordability for rural users while maintaining long-term sustainability. Basic services on KRUSTI will remain free for farmers, while premium features such as AI-powered advisory, expert consultancy, and assisted services will be offered through subscription plans. We will generate revenue through marketplace transaction commissions, subscription plans for FPOs and premium users, agent-assisted service fees, and advertising and promotional partnerships with agri-input companies. Additional revenue will come from collaborations with banks, NBFCs, insurance providers, CSR initiatives, government and development organizations, and institutional projects. As our ecosystem grows, we will also expand into enterprise analytics and other value-added rural digital services Our primary competitors include AgroStar, AgriApp, DeHaat, Gramophone, and other agritech platforms that provide advisory, input commerce, or marketplace services. We also compete with the traditional ecosystem of local agents, commission agents, middlemen, and fragmented service providers, on whom many farmers still depend for market access, government schemes, and agricultural guidance. Unlike these solutions, ILAAV offers an integrated rural development ecosystem that combines AI-powered advisory, weather and pest alerts, government scheme support, multilingual assistance, local agent support, direct marketplace access, and community partnerships on a single platform. Beyond agriculture, our initiatives in women empowerment (ILAAV Shakti), water (ILAAV Jal), land management (ILAAV Bhumi), and rural healthcare (ILAAV Arogya) make our approach holistic and difficult to replicate. We acquire customers through a combination of grassroots community engagement and strategic partnerships. We conduct farmer awareness programs, village meetings, training sessions, and demonstrations to build trust within rural communities. We collaborate with Farmer Producer Organizations (FPOs), Self-Help Groups (SHGs), NGOs, agricultural institutions, and agribusiness partners to reach farmers at scale. Our trained local agents onboard and assist farmers who are less familiar with digital technology, while referrals and word-of-mouth within villages drive organic growth. As we scale, we will complement these efforts with digital marketing, social media outreach, and partnerships with government and CSR initiatives to expand our reach across rural India. ILAAV follows a community-first, phygital (physical + digital) go-to-market strategy. We begin by partnering with Farmer Producer Organizations (FPOs), Self-Help Groups (SHGs), NGOs, agricultural universities, and local institutions to build credibility and reach farmers efficiently. We conduct village awareness programs, training workshops, and on-ground demonstrations to educate farmers about our platform. Our trained field agents help farmers with onboarding, government schemes, and digital adoption, ensuring accessibility even for those with limited digital literacy. We then strengthen engagement through our multilingual KRUSTI platform with AI advisory, weather and pest alerts, marketplace services, and expert consultancy. As we scale, we will expand through strategic partnerships, referral programs, digital marketing, and CSR/government collaborations to reach rural communities across India. Our long-term vision is to transform ILAAV into one of India's leading rural development ecosystems, demonstrating that technology can solve interconnected rural challenges—not just agricultural ones. Our first milestone is to successfully implement a large-scale pilot or CSR-backed rural development project that showcases the integrated impact of ILAAV across agriculture, women empowerment, water, healthcare, and land management. Our second milestone is to establish KRUSTI as one of the leading agritech platforms in India, recognized for its AI-driven, farmer-centric approach. As we mature, we aim to expand internationally, particularly into the Gulf region. With increasing investments in food security, controlled-environment farming, and sustainable agriculture across Gulf countries, we see a significant opportunity for KRUSTI's technology, advisory, and digital agriculture solutions to support this growing transformation. Ultimately, our vision is to build self-reliant rural communities where people have access to opportunities, essential services, and sustainable livelihoods, making migration to cities a choice rather than a necessity. Limited Liability Partnership (LLP), incorporated on 27 March 2026. ₹2.5 Lakhs non-dilutive grant received under the SSIP (Student Startup and Innovation Policy) program. No We are applying to IITACB Incubator because we believe that solving rural India's challenges requires not only passion but also the right ecosystem. We are looking for mentorship from experienced entrepreneurs and domain experts, technical guidance to strengthen our platform, strategic industry connections, and support in validating and scaling our business model. IITACB's incubation ecosystem will help us transform ILAAV from a promising startup into a scalable, technology-driven rural development enterprise capable of creating measurable impact across India. During the incubation programme, we aim to strengthen KRUSTI into a scalable and market-ready agritech platform while building the foundation for the complete ILAAV rural development ecosystem. We want to secure our first large-scale CSR or institutional pilot project to demonstrate the real-world impact of our integrated model. We also seek mentorship to refine our technology, validate our business model, build strategic partnerships, strengthen our go-to-market strategy, and become investment-ready. By the end of the programme, we aspire to create a replicable model for rural transformation that can be scaled across India and, in the future, expanded to international markets such as the Gulf region. Yes. We are open to virtual participation and believe it will allow us to effectively engage with mentors, experts, and the IITACB ecosystem while continuing our on-ground work with rural communities. The Bommasandra industrial ecosystem and Bangalore's innovation network provide access to leading technology companies, CSR partners, investors, research institutions, and industry experts. We aim to leverage this ecosystem to build strategic partnerships, secure pilot and CSR projects, strengthen our technology, and connect with organizations that share our vision for rural development. IITACB's mentorship, industry network, investor connects, and business guidance will help us validate, scale, and accelerate ILAAV into a nationally impactful rural development platform. No At our current stage, our operations are primarily field-based and focused on rural communities rather than office-based. Therefore, we intend to leverage IITACB's incubation ecosystem through mentorship, networking opportunities, technical guidance, investor interactions, workshops, and access to domain experts. These resources will help us strengthen our product, refine our business strategy, and build meaningful partnerships while continuing our work on the ground. Yes Supporting feature KRUSTI is being developed as a scalable cloud-based web and mobile platform with a modular architecture. The platform integrates AI-powered advisory, multilingual support, marketplace services, and farmer assistance into a single ecosystem. We leverage APIs such as the IMD Weather API for weather forecasts and alerts, DigiLocker API for secure document verification, and Shiprocket API for logistics support. The platform is designed to support AI chat assistance, multilingual text, audio and video guidance, government scheme integration, and secure data management. Our architecture follows an API-first approach, enabling seamless integration with additional government, fintech, logistics, and agricultural services as the platform scales. While we are still in the early stages, our primary advantage comes from the real-world insights and feedback we continuously collect through direct engagement with farmers, FPOs, and rural communities. These interactions help us build a unique dataset of farmer needs, local agricultural challenges, government scheme awareness, and user behaviour. As KRUSTI grows, this proprietary data will enable us to deliver more accurate AI recommendations, personalized advisory services, and region-specific solutions that become increasingly valuable over time. Our competitive advantage lies in our integrated rural development approach rather than solving a single agricultural problem. While most agritech platforms focus on advisory, inputs, or marketplaces, KRUSTI combines AI-powered advisory, weather and pest alerts, government scheme assistance, multilingual support, AI chatbot, expert consultancy, marketplace access, and local agent-assisted services within one platform. Beyond agriculture, ILAAV extends its impact through ILAAV Shakti (women empowerment), ILAAV Jal (water management), ILAAV Bhumi (land management), and ILAAV Arogya (rural healthcare), creating a holistic ecosystem for rural transformation. Our strong community engagement, farmer trust, strategic partnerships, and growing proprietary rural data create long-term network effects that are difficult for competitors to replicate. We are not just building an application—we are building an ecosystem for self-reliant rural communities. As an MVP-stage startup, our primary focus is on validating real-world usability, reliability, and farmer adoption rather than benchmarking against enterprise-scale metrics. We evaluate our platform using API response time, application uptime, successful completion of user workflows, onboarding success rate, feature adoption, user retention, and farmer feedback. We also measure the accuracy and timeliness of weather alerts, AI recommendations, marketplace transactions, and government scheme assistance. Continuous field feedback enables us to improve reliability and user experience with every iteration. We follow a privacy-by-design approach. Personal information is collected only with user consent and only for services that require it. Data is encrypted during transmission and securely stored with role-based access controls. We use trusted APIs for integrations and follow applicable Government of India regulations, including the Digital Personal Data Protection (DPDP) Act, 2023. We are committed to maintaining transparency, protecting farmer data, and continuously strengthening our security practices as the platform scales. Yes. Our solution aligns with several Government of India initiatives, including the Digital India Mission, Digital Agriculture Mission, Farmer Producer Organization (FPO) promotion initiatives, PM-KISAN, Agristack, and various state and central agricultural schemes. These initiatives encourage digital adoption, improve farmer access to government services, and support innovation in the agriculture sector, creating a favourable environment for ILAAV's growth. As a technology platform, we monitor changes in data privacy regulations, API access policies, digital identity integrations, marketplace regulations, and agricultural compliance requirements. We mitigate these risks by using only authorized integrations, maintaining regulatory compliance, obtaining user consent, and designing our platform to adapt quickly to changes in government policies and regulatory frameworks. Our technology is designed to scale through a modular and cloud-based architecture. However, at 10× growth, the primary challenges will be infrastructure scaling, customer support capacity, API usage limits, field agent expansion, and maintaining consistent service quality across diverse regions. We plan to address these through cloud auto-scaling, optimized infrastructure, stronger AI automation, expanded regional partnerships, and a structured field-agent network to ensure that growth does not compromise user experience. NO As our platform is currently under development, we are integrating a combination of government-authorized APIs, licensed third-party services, and open-source technologies. These include the IMD Weather API for weather data, DigiLocker API for secure document verification, and Shiprocket API for logistics support. We also use standard open-source frameworks and libraries for application development. We currently hold two registered trademarks protecting our brand identity and are building our own proprietary platform architecture, workflows, and AI-enabled rural service ecosystem. As the product matures, we plan to further strengthen our intellectual property portfolio through additional IP protection where applicable We follow an iterative, user-centric development approach. Continuous feedback from farmers, FPOs, field agents, and partner organizations guides our product improvements. We regularly monitor application performance, optimize APIs, strengthen security, improve AI recommendations, and enhance user experience through multilingual and accessible interfaces. As the platform scales, we will leverage cloud infrastructure, automation, analytics, and emerging AI technologies to ensure high performance, reliability, and scalability. We are initially building for India, with a primary focus on solving the challenges faced by rural communities and small and marginal farmers. However, our technology is designed to be scalable and adaptable for global markets. In the long term, we plan to expand into regions such as the Gulf countries, where increasing investments in food security, smart farming, and sustainable agriculture create strong opportunities for KRUSTI's digital agriculture solutions. Therefore, our long-term vision is to build for both India and global markets. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/h1PJVNPfiEiX-iitacb.pptx, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/h1PJVNPfiEiX-iitacb.pptx https://drive.google.com/file/d/1cIKKPbopD6jTaIAQikLhYxRtcKQCtT4S/view?usp=drivesdk%20 Yes. ILAAV is a mission-driven and impact-focused startup committed to transforming rural India through technology and innovation. Our vision extends beyond agriculture—we aim to build self-reliant villages where farmers have better incomes, women are economically empowered, every family has access to clean water and quality healthcare, and rural communities can thrive without being forced to migrate to cities. Through our initiatives—KRUSTI, ILAAV Shakti, ILAAV Jal, ILAAV Bhumi, and ILAAV Arogya—we are creating an integrated rural development ecosystem that addresses interconnected challenges rather than isolated problems. Our success will be measured not only by business growth but by the positive and sustainable impact we create in rural communities. Yes. Our founding team includes a woman co-founder in a leadership role, bringing diverse perspectives to product development, community engagement, and strategic decision-making. We strongly believe that inclusive leadership drives better innovation and aligns with our mission of empowering rural communities, particularly through ILAAV Shakti, which focuses on women entrepreneurship and Self-Help Groups (SHGs). NA ILAAV LLP is an SSIP-supported startup that has received a ₹2.5 lakh non-dilutive grant from the Government of Gujarat and currently holds two registered trademarks. We are actively developing our MVP and engaging with farmers through awareness and capacity-building initiatives. We have also entered into a strategic collaboration with Newway Biotech to promote mushroom cultivation, provide technical training, and create sustainable livelihood opportunities for farmers. Through this partnership, we aim to combine ILAAV's rural outreach and digital ecosystem with Newway Biotech's agricultural expertise to deliver greater value to farming communities. Our long-term vision is to build a globally recognized rural development ecosystem that creates sustainable social and economic impact. checked
Aug 5, 2026 @ 8:07 PM George Johnson george.johnson@datamatrixai.co.in http://www.linkedin.com/in/georgejohnsonin https://www.datamatrixai.co.in 7829440444 Co - Founders We were both in the cohort of IISc GenAI and Prompt Engineering certification in July 2024. We officially formed the company in April 2025. We have developed AI based solutions specifically for the Energy sector and now focussing on Fintech space. 2 I(George Johnson) have been in Firm Management, Business Management and Sales and Marketing for over 2 decades having worked with JLL Property Consultants as Managing Director, with the mortgages business while in ABN AMRO Bank and ICICI Bank. I drive the customer acquisition part in DatamatrixAI. Radha Baran Mohanty handles the Tech development part. An IIT Kharagpur Alumni, he was with Infosys for 28 years in a leadership role responsible for CME(Communications, Media and Entertainment) vertical. We have a team of 12 full time employees, 11 of them are AI Engineers from Infosys and from Institute of Mathematics and Applications and have developed solutions solving real industry use cases and also deployed them proving that we can not only develop a Pilot but also deploy at scale. Datamatrix.AI Pvt Ltd https://datamatrixai.co.in Benagaluru and Bhubaneshwar At DatamatrixAI, we're building next-generation AI infrastructure to help businesses unlock the full potential of AI/ML and GenAI. Our platform leverages cutting-edge technologies to automate complex workflows, enhance decision-making, and reduce operational overhead. We design and develop scalable, and production-ready GenAI solutions with a big eye on security and privacy. We are solving the problem of executives grappling to elicit intelligence from fragmented and siloed structured and unstructured data through a natural language query. The platform we developed is now applied in two sectors. 1. Energy Sector: A. Identifying consumers stealing power and plugging revenue leakage. B. Load Prediction C. Rectifying meter connection mismatch with correct transformer or feeder known as GIS Index Problem. 2. Fintech Sector: A. NRI's faces KYC validation and AML scrutiny. B. Banks have to comply with regulatory reports and need to fill them from a plethora of documents of structured and unstructured data. Organizations today are drowning in documents and dashboards. Key business insights are locked inside fragmented reports, presentations, and siloed data platforms. CXOs and senior leaders face delays, blind spots, and inefficiencies due to: We transform enterprise data overload into instant, actionable intelligence enabling decision-makers to query complex information in natural language and receive accurate, contextual answers in under 5 seconds. Our long-term defensibility is built on a combination of proprietary technology, domain-adapted models, and continuously improving enterprise data context. As organizations use the platform, it learns from multiple structured and unstructured data sources, building a unique knowledge layer that becomes increasingly valuable and difficult to replicate. The platform’s architecture integrates multimodal data understanding, contextual reasoning, and conversational analytics in a single system. Over time, this creates strong switching costs as the system becomes deeply embedded in enterprise workflows and knowledge ecosystems. In addition, our focus on solving complex enterprise insight generation, rather than generic analytics, positions the platform as a specialized decision intelligence layer. Continuous model refinement, domain customization, and integration into enterprise systems will further strengthen our competitive moat over time. Revenue Revenue Energy Sector especially DISCOM's. Banks and Financial institutions USD 15 Billion USD 6 Billion USD 1.2 Billion Licence mode, User Mode and Subscription Mode HILA, Bloomberg, Alpha Sense, Seeking Alpha, Factset Focused event based engagement like CXO conferences, LinkedIn outreach, References, Social media Vlogs Our go-to-market strategy focuses on a targeted B2B approach through strategic partnerships and industry-specific deployments. We plan to collaborate with consulting firms, system integrators, and data platform providers that already serve enterprise clients and can embed our solution as an insight generation layer within their offerings. Initial focus will be on sectors such as financial services, consulting, and enterprise technology where organizations manage large volumes of structured and unstructured data and require faster decision intelligence. We will complement partnerships with direct outreach to data and strategy leaders, pilot deployments with early adopters, and participation in European AI and data innovation ecosystems. This partner-led and use-case-driven strategy enables faster market entry, lower customer acquisition costs, and scalable growth. To be a frontier intelligence generation firm with AI framework across industries. Pvt Ltd 0 Yes For business connect, data, mentoring and funding support to scale. Take the product to market. Yes With IIT ACB located in Bommasandra and having its connect with the industry, we want to leverage the influence the platform has over the region within the business fraternity. Yes Cloud Credits and Alumni connect. Yes Core engine We finetune open source Small Language models like Llama 4, Phi 3, Qwen 3.5 and deploy both on cloud and on premises. The entire data(of different formats, modes, legacy) which is proprietary and the platform builds a semantic layer over it for contextual understanding for generating intelligence. This method obliviates the need to create data pipeline every time a query is to be generated for extracting intelligence. The business logic from the data is extracted by our tool basis the semantic layer we build over it, and to replace our tool with competition, requires the customer to start from scratch which is annoying and time consuming and do not make sense. Fraction of a cost compared to Tier 1 or 2 AI firms offer as we run the tool over an SLM and build our own API's. The tool is run on premises. If its on cloud, then private cloud helps to some extent however the data leaves the premises. None to our understanding. But we may be uninformed. RBI's kill switch policy. Data protection and Data privacy policy. We haven't reached that stage to explain this. Yes. AI Engineers were with Infosys and worked on AI projects. Real world proprietary data sets from customers. Continuously improve to handle edge cases. Reduce latency making the tool lite. Add more use cases. Primarily for India. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/Ps6A0vBS2Y9D-DatamatrixAI-Company-Profile-Aug26.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/Ps6A0vBS2Y9D-DatamatrixAI-Company-Profile-Aug26.pdf https://drive.google.com/file/d/1G4CM4VAt3J78PHW7extdFRJe4ny8PaA4/view?usp=sharing Mission driven as we are solving India's energy sector problem which is critical for the nation given that the demand for energy is growing by leaps and bounds and the source is limited. So, reducing wastage is key to manage India's energy demands. Yes NA NA checked
Aug 4, 2026 @ 4:12 PM Eshwar Boini eshwarb@xequalto.com https://www.linkedin.com/in/eshwar-boini-8340008b/ http://quper.co +919002495989 Eshwar Boini (IIT KGP) & Ayan Chakraborty, Co-Founders of XEqualto and Quper. Both bring deep expertise in Data Engineering, AI/ML, and consulting, having worked across enterprise and startup environments. Eshwar leads product and technical architecture while part of it is shared; Ayan drives strategy, client engagement, and operations. We met at EPAM in 2023, where Ayan was my (Eshwar's) senior. We quickly discovered a shared outlook on work, problem-solving, and life, which led to a deeper professional and personal connection. That alignment gave us the confidence to co-found together. We've been working closely for more than two years now. 2 Our biggest strength is complementarity - we each bring deep, independent expertise across product, engineering, finance, operations, sales, and go-to-market. While either of us could handle most functions alone, we've chosen to let each person own their domain so we move faster and with less friction. Beyond skills, we operate like family. We're a remote-first team that deeply respects each other's individual values and ways of working. Both of us have navigated similar struggles in life, and that shared experience gives us a grounded, empathy-driven approach to strategy rather than a purely theoretical one. We don't just plan from frameworks; we plan from lived understanding. Importantly, what also holds us together is radical openness, we celebrate wins together and are equally comfortable calling out what's not working. That psychological safety is important in an early-stage founding team, and we believe it's what makes us resilient when things get hard. XEqualto Analytics xequalto.com; quper.co Kolkata At Xequalto, we are building Quper is a FinOps intelligence platform that helps engineering, platform, and finance teams optimize cloud and data platform costs. It connects cost, performance, ownership, and actionable recommendations in one place, giving organizations the visibility and accountability they need to continuously reduce waste and track realized savings. Cloud platform costs keep growing, but enterprises lack one or more areas of visibility, ownership, and actionable insights to do anything about it with proper recommendations and directions.. Quper connects cost, performance, ownership, and recommendations in a single intelligence layer. It helps platform, data, and finance teams identify what's driving cloud and data spend, assign ownership to the right teams, surface prioritised optimisation opportunities, and track realised savings over time - all powered by AI. Unlike generic cost tools, Quper is purpose-built for modern data platforms and grounded in real enterprise operating patterns discovered through personal and XEqualto's consulting engagements. Unlike tools that just show the bill, Quper explains the why, assigns ownership, delivers engineer-grade recommendations, and tracks realized savings over time, built from live enterprise environments and validated through active POCs, giving us depth no outside tool can replicate. MVP Revenue, Pilots, Testimonials Mid-sized and enterprise organizations with significant cloud spend, primarily FinOps, platform engineering, and cloud infrastructure teams, with budget ownership sitting with CTOs, VPs of Engineering, and CFOs. $15B+ (Global cloud FinOps and cost management market) $3B (Enterprises actively investing in FinOps practices across target industries) $50M (Near-term reachable via consulting-led and direct enterprise sales) SaaS and BYOC (Bring Your Own Cloud) subscription, tiered by cloud spend under management, plus a success fee as a percentage of realized savings. Customers only pay more when Quper delivers measurable value. Apptio Cloudability, CloudHealth (VMware), Harness Cloud Cost Management, Vantage, Spot.io. Most offer cost visibility but lack ownership assignment, engineering-grade recommendations, and realized savings tracking which is core to Quper. Through direct outreach and founder-led sales via XEqualto's existing enterprise network and connections. Warm relationships from consulting engagements convert naturally into Quper pilots. We use a consulting-led land-and-expand motion — XEqualto engagements open the door, Quper pilots prove value, and the success-fee model removes procurement friction. From there we expand within accounts and grow outbound through FinOps practitioner communities, cloud cost events, and referrals from early enterprise customers. BYOC support allows larger enterprises to adopt Quper within their own infrastructure, reducing security and compliance barriers to conversion. To become the default intelligence layer for cloud cost governance in every cloud-native enterprise. We believe the logical flow Quper is built on from cost visibility, to ownership assignment, to actionable recommendations, to tracking realized savings - is the right and complete way to solve FinOps. Our long-term vision is to make this flow the industry standard, evolving Quper into a proactive governance platform that predicts cost impact before infrastructure decisions are made, making FinOps a first-class engineering discipline rather than a reactive finance exercise. Quper is part of XEqualto, XEqualTo is incorporated Bootstrapped Yes I'm an IIT KGP alumnus, so the IIT network is something we naturally trust and feel connected to. Beyond that, we're at a stage where the right mentorship and market access matter more than capital, and IITACB feels like the right room to be in. Three things in specific - get mentorship from people who've built enterprise products before, land our first few marquee customers in Bangalore, and start meaningful conversations with investors who get B2B SaaS. Yes, absolutely. Bangalore is home to the exact teams we're building for - platform engineers, FinOps leads, and CTOs managing serious cloud spend. The Bommasandra hub adds manufacturing and industrial enterprises who are increasingly dealing with the same cloud cost problems. What we need most is warm introductions into these organizations, and that's where IIT ACB's network can make a real difference for us. Yes We'd use it as our Bangalore home base for customer meetings, pilot discussions, and investor conversations. More than the physical space though, being inside the incubator keeps us close to mentors and fellow founders, and that kind of proximity is something you can't replicate remotely. Yes Supporting feature Quper is built on AWS with a Node.js backend and React frontend. Cloud billing data is ingested via AWS Cost Explorer APIs and FOCUS-generated S3 files, orchestrated through Temporal workflows. Data pipelines run on AWS Glue with RDS as the primary data store. AI-powered recommendations and insights are driven by transformer models with attention-based agents that analyze cost patterns, ownership signals, and optimization opportunities. BYOC deployments are delivered via a licensed Docker image with customer-side cloud resource provisioning. Our core advantage is the combination of XEqualto's enterprise consulting data and Quper's own ingestion layer. We've seen how real organizations structure their cloud environments, tag resources, and attribute costs, patterns that are hard to learn from outside. This gives our AI models richer, more grounded training signal than from synthetic or public datasets. Three things. First, our logical flow cost visibility to ownership to recommendations to realized savings tracking is purpose-built and complete, unlike point tools that stop at dashboards. Second, our AI models are trained on real enterprise patterns, not assumptions. Third, BYOC support removes the biggest adoption barrier for security-conscious enterprises, giving us access to customers that SaaS-only competitors can't reach. We track API response latency, pipeline processing time, and recommendation accuracy as primary metrics. Data ingestion reliability is monitored through Temporal's workflow observability. AI model quality is evaluated on recommendation relevance and savings realization rate meaning we measure not just what we suggest, but what actually gets acted on and saved. We benchmark against cost attribution accuracy and ownership resolution rates across customer environments. Quper handles a mix of raw billing data and aggregated cost metadata. For SaaS, data is encrypted in transit and at rest on AWS. For BYOC, all data stays within the customer's own cloud environment nothing leaves their infrastructure. Access is scoped to read-only billing and usage APIs. We're building toward SOC2 compliance as we move into enterprise deployments, and follow least-privilege access principles across all integrations. Growing regulatory focus on cloud cost accountability and IT governance in enterprises — particularly in financial services and healthcare works in our favour. Organizations are increasingly required to report and justify cloud spend, which creates a natural tailwind for a product like Quper. The primary risk is around data residency and cross-border data transfer regulations, particularly for enterprise customers in the EU and regulated industries. Our BYOC model largely mitigates this since data never leaves the customer's environment. We'll need to ensure SOC2 and relevant compliance certifications are in place before enterprise deals close in regulated sectors. Two things we're already aware of. First, API call latency as the number of concurrent users and data queries grows, response times on our Node.js backend will need optimization and likely a caching layer. Second, AI model compute costs we haven't yet put hard limits on model inference credits per customer, which could become expensive at scale. Data ingestion pipelines via Glue and Temporal are well-architected and horizontally scalable, so that's not a concern. Yes. We have an in-house team with expertise spanning data engineering, cloud architecture, AI/ML, and full-stack development. The founding team brings deep hands-on experience building enterprise-grade data and cloud platforms, complemented by engineers who've worked across modern cloud-native stacks. Our AI capability is built around transformer models with attention-based agents, developed and iterated in-house. All proprietary logic cost attribution, ownership mapping, recommendation engines, and savings tracking is built and owned in-house. No third-party licensed datasets are used; our data advantage comes from real enterprise environments as part of our previous clients and new pilots. We track latency, recommendation accuracy, and realized savings rate as our core performance metrics and iterate against them. On the AI side, every new enterprise deployment feeds better signal into our models making recommendations sharper over time. We're also planning to introduce inference cost controls and a caching layer to address known latency and compute scaling concerns. Pipeline performance is monitored through Temporal's observability tooling, with Glue jobs optimized per customer data volume. India first. The Indian market gives us the right density of cloud-native enterprises, fast feedback cycles, and the ability to build deep customer relationships early. Once we've established strong product-market fit and a repeatable go-to-market motion here, we'll expand globally, particularly into the US and European markets where FinOps maturity and willingness to pay are high. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/hkVTBMPNHYMJ-The-Quper-Deck-1_compressed.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/hkVTBMPNHYMJ-The-Quper-Deck-1_compressed.pdf We genuinely believe cloud waste is one of the most overlooked inefficiency problems in modern organizations billions of dollars spent every year with no real accountability. Our mission with Quper is to change that not just by saving money, but by making engineering teams more intentional and responsible about the infrastructure they build and run. We want to make cost-aware engineering a default culture, not an afterthought. That's the impact we're working towards. NA Dipten Chatterjee, IIT KGP batch of '85 checked
Aug 4, 2026 @ 9:40 AM Sachin Anand sachin@coinslive.in http://linkedin.com/in/sachin-anand-mbb http://coinslive.in +919354580732 Founder, CEO, CTO All Philosophical alignment and alignment in working styles Coinslive coinslive.in Vrindavan The platform helps 3rd and 4th-year students from Tier 2 and 3 colleges achieve career clarity. It builds custom roadmaps, hosts live sessions with professionals, and reviews student projects so they are ready for any employer Problem of career confusion and lack of clarity in college students and early professionals We are helping the students by: - building a roadmap based on the market requirements, students potential/talent, interest and their family background - providing live mentor sessions with reputed professionals - helping in implementing the roadmap, verifying the proof of their practice which can be presented to the employer. Holistic roadmaps and universal verification system MVP Users College students and early professionals 5 crore 1.6 crore 1 lakh Platform fees, premium services, B2B charges Partial Competitors: Marketplaces like Udemy, Cohorts platform like scaler, Networking platforms like LInkedin By providing free content to increase engagement, then providing free roadmaps, then low cost webinars, then cohorts, then precise roadmaps, then implementing them Onboard highly qualified professional mentors, conduct regular session and attract audience To work closely with schools and students' families to create a holistic environment that inspires students to pursue a career aligned with their Ikigai and dedication to serving society. NA NA Yes To get guidance, funds and a network to approach mentors, recruiters and colleges To increase the mentors and recruiters on the platform. Precisely design the platform. Get Funding. Yes CoinsLive can leverage the Bommasandra industrial hub and Bengaluru market by partnering with companies to understand skill gaps, create industry-aligned career programmes, and build internship and hiring pipelines for students and early professionals. IIT ACB can support us through introductions to industry leaders, mentors, employers, investors and colleges, while also providing credibility, strategic guidance, pilot opportunities and access to its wider alumni and startup ecosystem. No NA Yes Core engine - Frontend: Web and mobile interfaces for learners, mentors and employers. - Backend: Secure APIs managing users, courses, diagnostics, mentorship and payments. - AI Layer: Powers career diagnostics, personalised learning paths, skill-gap analysis, mentor matching, doubt resolution and progress tracking. - Blockchain Layer: Enables tamper-proof verification of certificates, skills, mentor contributions and rewards. - Data Privacy: Personal and learning data remains securely stored off-chain; only verification hashes are recorded on the blockchain. Outcome: A scalable platform combining personalised career guidance with trusted and portable proof of skills. - CoinsLive is building proprietary data on learners from Tier 2 and Tier 3 colleges, including career goals, skill gaps, learning behaviour, constraints and mentor interactions. - We connect this data with programme completion, interview readiness, job applications and employment outcomes. - These feedback loops can continuously improve our AI-based diagnostics, recommendations and mentor matching. - Employer inputs on role requirements and recurring skill gaps further strengthen our industry-aligned intelligence. - Our data advantage is currently at an early stage, but it can become difficult to replicate as the number of learners, mentors and verified outcomes grows. - Proprietary outcome data: Every diagnostic, learning activity, mentorship interaction and hiring result improves our AI recommendations over time. - AI + human mentorship: CoinsLive combines personalised AI guidance with verified mentors, making the experience more practical and trustworthy than AI-only platforms. - Employer-linked learning: Programmes are designed around real skill gaps, roles and hiring requirements rather than generic course completion. - Verified skill records: Blockchain-backed credentials can provide tamper-proof and portable proof of skills, projects and mentor validation. - Network effects: More learners attract mentors and employers; more mentors and employers improve opportunities and outcomes for learners. - Focused distribution: Our organic content, community and strong understanding of Tier 2 and Tier 3 learners create a difficult-to-replicate acquisition and trust advantage. - Performance: API response time, page-load speed, AI recommendation latency and concurrent-user capacity. - Reliability: Platform uptime, error rate, failed transactions, recovery time and backup success rate. - AI quality: Diagnostic accuracy, recommendation relevance, mentor-match success and improvement in learner outcomes. - User experience: Registration completion, diagnostic completion, session attendance, retention and user satisfaction scores. - Security: Authentication failures, vulnerability findings, data-access incidents and audit-log coverage. - Blockchain efficiency: Credential verification time, transaction cost and successful on-chain verification rate. - Competitive comparison: We benchmark these metrics against leading learning and mentorship platforms, while differentiating through the combined use of AI personalisation, human mentorship and verifiable skill credentials. * **Continuous improvement:** Monitoring, user feedback and outcome data are used to identify bottlenecks and improve the platform after every release. - Privacy by design: We collect only necessary user data with clear consent and defined purposes. - User control: Users can access, update, delete or withdraw consent for their personal data. - Secure infrastructure: We use encrypted communication, secure authentication, role-based access, audit logs, backups and continuous monitoring. - AI safety: Personally identifiable data is minimised before AI processing, and sensitive decisions retain human oversight. User data is not used to train external models without permission. - Blockchain privacy: No personal or sensitive information is stored publicly on-chain; only hashes or verification references are recorded. - Compliance: We are building CoinsLive in alignment with India’s Digital Personal Data Protection Act, 2023 and the phased DPDP Rules, 2025, including consent, security, grievance and data-erasure requirements. - Ongoing protection: We plan regular vulnerability testing, vendor reviews, incident-response procedures and independent security audits as the platform scales. - Infrastructure bottlenecks: Higher traffic could increase API latency, database load and video-session failures; we will address this through autoscaling, caching, database optimisation and load testing. - AI cost and response time: Ten times more diagnostics and recommendations could increase inference costs and latency; we will use model routing, caching, smaller specialised models and usage limits. - Operational quality: Mentor availability, support response times and content moderation may become inconsistent; we will introduce structured onboarding, automated matching, quality scoring and stronger operational processes. - Datasets: We currently rely mainly on first-party learner data, including profiles, goals, assessments, skill gaps, participation and feedback. We do not use any restricted proprietary training dataset at present. - Open-source and third-party components: CoinsLive uses standard open-source web, backend and AI libraries under their respective licences, along with authorised third-party cloud and AI services. These components are not claimed as our IP. - Owned IP: Our proprietary assets include the CoinsLive source code, platform workflows, career-diagnostic logic, learning content, brand, domain and the learner–mentor–outcome data generated on the platform. We do not currently hold a registered patent; formal trademark registration and contributor IP-assignment documentation are being strengthened. - Measure continuously: Track uptime, API latency, error rates, AI response quality, infrastructure cost and user drop-offs through real-time monitoring and regular performance reviews. - Optimise systematically: Use load testing, caching, database tuning, autoscaling, model routing and smaller specialised AI models to improve speed, reliability and cost efficiency. - Improve through feedback: Analyse learner outcomes, mentor feedback, support issues and failed journeys to prioritise product improvements, followed by staged releases and regression testing. Primarily for India, but same could be implemented in other developing nations as well. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/dYicP7viSow9-CoinsLive-Pitch-Deck-Angels.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/dYicP7viSow9-CoinsLive-Pitch-Deck-Angels.pdf CoinsLive is a mission-driven startup focused on reducing unemployment and the career opportunity gap faced by students and early professionals from Tier 2 and Tier 3 colleges. NA checked
Aug 4, 2026 @ 6:54 AM Siddarth Baliga siddarth1981@gmail.com http://www.linkedin.com/in/sidbaliga http://www.sidbaliga.in 919900092156 1 I have worked in Sales, created e-learning courses on Sales, authored bylines/books on Sales Skillfyd www.skillfyd.com Bangalore Most sales hiring decisions are made on instinct. Skillfyd was built to change that — replacing gut feel with a structured, data-backed signal. We hire salespeople on gut feel — then wonder why half of them don't perform. Gut feel rewards confidence in a room. It doesn't reveal whether someone has the discipline to follow up, the resilience to handle rejection, or the focus to prioritise the right opportunities. Traditional sales interviews rarely reveal who will actually succeed. Skillfyd combines resume evidence, LinkedIn behavioural signals, and a live behavioural assessment to produce clear signals—in under 15 minutes, before you invest an hour interviewing the candidate. Skillfyd's defensibility comes from domain expertise, proprietary methodology, and accumulating data. The platform codifies nearly two decades of hands-on sales hiring and leadership experience into a structured evaluation model. Instead of relying on a single assessment, it triangulates resume evidence, LinkedIn behavioural signals, and a live adaptive behavioural assessment to generate a calibrated hiring recommendation. As more candidates are assessed and hiring outcomes are captured, the benchmarking engine continuously improves, creating a data advantage that becomes increasingly difficult to replicate. Users Users Mid-sized and large enterprises hiring sales professionals at scale. Our ideal customers are organizations recruiting 50+ sales candidates annually across inside sales, field sales, business development, and account management roles. Primary buyers are Heads of Talent Acquisition, HR Directors, Sales Enablement leaders, and Business Heads responsible for hiring quality and reducing sales attrition. INR 30,000 Crores INR 4,000 Crores INR5–10 Crore over the next 3–5 years Annual subscription for employers based on hiring volume, with usage-based pricing for assessments beyond the subscription limit. Additional revenue streams include campus licensing, institutional subscriptions, benchmarking reports, and premium interview intelligence. Thomas, Hogan, HireVue Outbound sales to HR and Sales leaders, founder-led enterprise sales, LinkedIn thought leadership. Business schools act as a talent pipeline and validation channel, introducing employers to pre-assessed candidates. We start with mid-sized enterprises hiring sales talent at scale, offering low-friction pilots to demonstrate reduced hiring risk and improved candidate quality. Successful pilots convert into annual subscriptions, supported by founder-led sales, customer referrals, and channel partnerships. As our benchmarking dataset grows, we expand into recruitment firms and larger enterprise accounts. Our vision is to become the operating system for sales hiring. Just as coding interviews transformed engineering recruitment, we aim to make sales hiring measurable, data-driven, and predictive. Over time, Skillfyd will build the world's largest benchmark of sales talent, enabling organizations to identify, compare, hire, and develop high-performing sales professionals with confidence. LLP 0 Yes Skillfyd has validated the problem and built a working platform. Our biggest challenge is accelerating enterprise adoption. IIT ACB can help us refine our product-market fit, access enterprise networks, strengthen our GTM strategy, and connect with mentors experienced in scaling B2B SaaS businesses. We also believe the IIT ecosystem will enhance our credibility with early enterprise customers. Our goals are to secure 10–20 enterprise pilot customers, validate repeatable product-market fit, refine our pricing and GTM strategy, strengthen the product based on customer feedback, and prepare the company for institutional fundraising. Yes. We are open to virtual participation and can also attend in-person sessions whenever required. Bengaluru provides access to a diverse mix of technology, SaaS, manufacturing, healthcare, and services companies. We intend to validate Skillfyd with organizations that hire sales talent at scale, while leveraging IIT ACB's industry network for pilot deployments, customer discovery, and strategic partnerships. No We prefer need-based use of the incubator facilities, as our current focus is on meeting enterprise customers, running pilot engagements, and building a repeatable sales process. Yes Supporting feature Skillfyd is built on a Next.js application with Supabase as the backend for authentication, data storage, and assessment orchestration. The platform combines deterministic scoring logic with AI-assisted services for question generation, report generation, and candidate insights. Resume parsing, LinkedIn signal extraction, and behavioral assessment results are consolidated into a calibrated hiring score. The architecture is API-driven, cloud-native, and designed for scalable enterprise deployment. Our proprietary advantage comes from combining three independent sources of hiring intelligence—resume evidence, LinkedIn behavioural signals, and live behavioral assessment outcomes—into a unified sales hiring dataset. As enterprise customers use the platform, this dataset grows with hiring outcomes and benchmarking information, continuously improving our prediction models. We are building one of the few datasets focused specifically on sales hiring rather than general personality or aptitude assessment. Our defensibility lies in three areas: (1) nearly two decades of sales hiring and leadership experience embedded into a proprietary evaluation methodology, (2) the integration of multiple independent hiring signals into a calibrated assessment framework, and (3) an expanding benchmark dataset focused exclusively on sales talent. Together, these create domain expertise and data assets that become increasingly difficult to replicate over time. The platform uses deterministic scoring for assessment reliability, cloud-native infrastructure for scalability, and modular AI services that can be replaced or upgraded independently. Assessment workflows are designed for consistent execution, while enterprise architecture supports secure data handling, auditability, and future model improvements without disrupting core functionality. Skillfyd follows a privacy-by-design approach. Candidate data is collected only with consent and stored securely using role-based access controls and encrypted cloud infrastructure. We follow data minimization principles, maintain audit logs, and ensure employers access only authorized assessment data. As the platform scales, we plan to align with applicable privacy regulations, including India's Digital Personal Data Protection (DPDP) Act and enterprise security requirements. Government initiatives promoting digital transformation, AI adoption, skill development, and startup innovation create a favorable environment for Skillfyd. The implementation of India's Digital Personal Data Protection (DPDP) Act also encourages standardized and responsible handling of recruitment data, benefiting trusted platforms. The primary regulatory considerations relate to candidate privacy, responsible use of AI in recruitment, and evolving data protection regulations. We mitigate these risks through transparent candidate consent, explainable assessment methodology, secure data handling, and compliance with applicable privacy laws. At 10× scale, the primary challenges will be enterprise onboarding, AI inference costs, assessment throughput, customer support, and maintaining consistent assessment quality across large hiring volumes. Our modular architecture allows independent scaling of application, database, and AI services, while benchmarking and scoring models can be continuously optimized as usage grows. Skillfyd is currently a solo founder venture. Product development is led by the founder and supported by specialized external engineering resources as required. The technical focus is on building a scalable SaaS platform with AI-assisted capabilities for enterprise sales hiring. The platform is built using licensed and open-source technologies, including Next.js, React, TypeScript, Supabase, PostgreSQL, and Vercel. We use commercially licensed AI APIs for specific workflows such as question generation and report generation. Our proprietary assets include the sales hiring methodology, assessment framework, scoring logic, question bank, prompt engineering, and application code. We currently do not hold any registered patents or IP filings. Technology improvements are driven by customer feedback, assessment analytics, hiring outcomes, and continuous benchmarking. We will optimize assessment quality, platform performance, AI-assisted workflows, and enterprise integrations through iterative releases while monitoring scalability, reliability, and security. We are building for both. India is our initial focus for product validation and enterprise adoption. The underlying methodology is industry-agnostic and geographically scalable, enabling future expansion into global markets where organizations face similar challenges in sales hiring. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/7oybubvwmwlm-Skillfyd.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/7oybubvwmwlm-Skillfyd.pdf Yes. Skillfyd aims to make sales hiring fairer, faster, and more objective. Sales remains one of the largest employment categories, yet hiring decisions are often driven by subjective interviews rather than evidence. By helping organizations identify genuine sales potential, Skillfyd reduces hiring bias, improves employment outcomes for candidates, lowers costly hiring failures for employers, and enables organizations to build stronger sales teams through data-driven decisions. NA checked
Aug 2, 2026 @ 11:55 PM Bryan Rodrigues bryan@singleaxis.ai https://www.linkedin.com/in/bryanrodrigues123 http://www.singleaxis.ai +917975563057 Ai engineer I’m a solo founder. 1 We are building agents for deployment in production environments. SingleAxis www.singleaxis.ai Bangalore We evaluate agentic ai deployments Ai evaluations We sandbox your ai deployment and perform recon and red teaming to ensure the agent is robustly build. 3 parts. 1. Datasets for evaluations 2. Evaluators for different domains 3. Risk profiles for different agents MVP Pilots Enterprises 10 billion 2 billion 500 million Per project basis NA Events and starting a podcast Publishing research for agentic deployments in different industries Become an independent evaluator for enterprise agent deployments Pvt ltd 50 lakhs Yes Yes Better connection Yes Yes to thoroughly explore Yes Not sure what options are available Yes Core engine Fabric.singleaxis.ai We are building our risk data profiles evaluation datasets based on industries. Answered previously We are building a product based on evaluating enterprise ai agent deployment risks. As well as functionality audits. This is one part I need to work on more strength and would need guidance on. EU AI act Only will benefit. Every enterprise and country will demand a risk profiling and evaluation audit. Scaling evaluators will be the bottleneck Yes https://www.github.com/jrcks67 We are building them inhouse We are yet to build an iterative loop to audit and improve the same Mainly Europe and Us 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/H4euqmzkI7or-SASF_v1.3_White_Paper_latest.docx, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/H4euqmzkI7or-SASF_v1.3_White_Paper_latest.docx Our mission is to ensure make ai deployment robust reliable and safe Minority NA None checked
Jun 26, 2026 @ 11:12 AM Shivam Panwar rajputshivam2800@gmail.com 8755681776 Shivam Panwar — Founder & CEO. M.Tech (Aerospace), IIT Kharagpur. Leads strategy, product vision, fundraising and overall direction. Sangam Sahu — Chief Robotics Officer (Robotics & Product). B.Tech Aeronautical (School of Aeronautics, Neemrana / BTU); 7+ years in mechanical design and industrial product development. Has personally designed and fabricated magnetic painting rovers for ships and oil tankers, ATEX-compliant rovers, and magnetic crawlers for UT-thickness and inspection — directly the core of BlueForge's product. Rahul Giri — CTO (Engineering & Simulation). M.Tech Aerospace, IIT Bombay; deep expertise in CFD, combustion and simulation (OpenFOAM, ANSYS), with an AIAA publication. Leads R&D, modelling and the technology stack. Avinash Mishra — COO (Deployment & Operations). PG from IIT Gandhinagar + Aeronautical (BTU); currently at RDSO Lucknow on rail freight-car/bogie multibody modelling, with hands-on UAV deployment and geospatial experience. Leads field operations and the railway domain. Mukesh Jaiswal — CBO (Business & Go-to-Market). MBA, IIM Mumbai + Aeronautical (BTU); Product Manager at bp (British Petroleum) with strong skills in product management, requirement discovery, stakeholder management and financial modelling. Leads business development, partnerships and GTM. All of us are associated with Bikaner Technical University (BTU) — we met there as aeronautical/aerospace engineering students and have known each other for 5+ years through our studies and projects, which gives us strong mutual trust and complementary skills. We reconvened around the BlueForge idea and have been working together on it since incorporating SkyOps Technologies LLP in May 2026 — combining robotics & product (Sangam), R&D and simulation (Rahul), deployment and rail-domain experience (Avinash), business and product management (Mukesh), under Shivam's leadership. All Our biggest strength is a rare combination: we have a founder who has already built exactly this product. Sangam Sahu has personally designed and fabricated magnetic painting rovers for ships and oil tankers, ATEX-compliant rovers, and UT-thickness inspection crawlers — so BlueForge isn't a team learning the technology from scratch; it's a team that has already done it and is now productising and scaling it. Around that core, we're a tightly-knit, complementary, full-stack engineering team — all aerospace-trained at BTU, having known and worked together for 5+ years (so high trust, fast iteration), with deep, distinct coverage of every part the business needs: robotics and hardware (Sangam), R&D and simulation (Rahul, IIT Bombay CFD), deployment and the rail/industrial domain (Avinash, RDSO), and business, product and go-to-market (Mukesh, IIM + bp), under Shivam's leadership. BlueForge Lucknow BlueForge (SkyOps Technologies LLP) is a Made-in-India deep-tech robotics startup building autonomous magnetic-crawler rovers that blast, paint and inspect the…BlueForge (SkyOps Technologies LLP) is a Made-in-India deep-tech robotics startup building autonomous magnetic-crawler rovers that blast, paint and inspect the steel hulls of ships — automating the slowest, most hazardous and almost entirely manual step in every shipyard. We deliver this as Robotics-as-a-Service, with no capital cost to the customer, and every job feeds our Digital Hull Passport: a per-vessel digital twin of metal thickness, corrosion and coating health that powers predictive, condition-based maintenance and recurring revenue. The robot wins the contract; the data builds a long-term relationship. We're at working-prototype stage, with demand validated by a live Cochin Shipyard tender, targeting India's ₹14,000+ Cr ship-repair market and scaling to global maritime hubs. Across shipyards, the preparation, painting and corrosion inspection of ship hulls is still done almost entirely by hand — it's slow, hazardous (workers exposed to grit and fumes), inconsistent in quality, and a major bottleneck that ties up scarce dry-dock capacity. Worse, the process is "blind": almost no condition data is captured, so shipyards and owners can't track how a hull is degrading, plan maintenance, or prevent corrosion failures — leading to premature damage, costly downtime, and avoidable safety and environmental risk. BlueForge solves this on two levels: we automate the dirty, dangerous, manual work with autonomous rovers (faster, safer, consistent quality), and we capture each vessel's condition as data — turning a one-off paint job into predictive, condition-based maintenance. In short, we replace a manual, blind, reactive process with an autonomous, data-driven, predictive one. BlueForge builds a fleet of autonomous magnetic-crawler rovers that climb steel ship hulls and perform the three dirtiest, most manual jobs in a shipyard — abrasive blasting (surface preparation to SA 2½), protective coating, and corrosion/coating inspection — using Edge-AI autonomy, sensor fusion (ultrasonic thickness, dry-film-thickness and vision), and full grit/dust recovery. We deliver this as Robotics-as-a-Service: yards pay per vessel or per square metre, with no capital outlay, and get faster turnaround, consistent certified quality, and workers out of the hazardous blast zone. The lasting value is the data layer. Every job feeds the Digital Hull Passport — a per-vessel digital twin recording metal thickness, corrosion percentage and coating health over time. Our AI uses it to predict where and when corrosion will reach action thresholds, enabling predictive, condition-based maintenance instead of fixed-calendar guesswork. The robot wins the contract; the data builds a recurring, high-margin AMC/SaaS relationship that competitors — who only blast or only inspect — cannot replicate. It's a purely Made-in-India deep-tech platform. 1. We do the whole job, autonomously — not one piece of it. Competitors blast or inspect, and most are remote-controlled machines sold as capital equipment. We run one autonomous, Edge-AI platform that blasts, coats and inspects in a coordinated workflow, delivered as a service with zero customer CapEx. 2. The data moat — our real defensibility. Where rivals' sensors only help them navigate and the data is thrown away, every BlueForge job writes to the Digital Hull Passport — a per-vessel record of thickness, corrosion and coating health. This compounds: more jobs → a richer corrosion dataset → better AI predictions → deeper, recurring AMC/SaaS lock-in. A competitor can copy a rover off a spec sheet, but cannot replicate years of accumulated, asset-specific condition data. The robot wins the contract; the data keeps the relationship. 3. Founder-proven capability + IP + Made-in-India edge. Our team has already built magnetic painting and inspection rovers for ships and oil tankers (so this isn't learned from scratch); we have a patent strategy around adhesion and motion-control plus proprietary control-perception-data IP; and we're indigenous and iDEX-aligned — an import-substituting cost and policy advantage over costly Chinese and Western imports. Idea Pilots Our target customers are the organisations that own or maintain large steel hulls and assets: Ship-repair and maintenance yards (primary) — they already outsource hull blasting and painting and are our fastest entry point. Shipbuilding and defence shipyards — e.g. Cochin Shipyard (our beachhead), GRSE, Mazagon Dock — where surface prep, coating and inspection are a major throughput bottleneck. Naval dockyards and the Indian Navy / port trusts — high standards, strong Make-in-India/iDEX pull, and recurring fleet-maintenance needs. Ship owners and operators — buyers of the recurring Hull-Health AMC / Digital Hull Passport data for predictive maintenance across a vessel's life. Offshore oil-&-gas operators — for large steel structures, tanks and platforms (adjacent expansion), with railway wagons as a further adjacency. 14000 cr 6000 cr 600 cr Three layers, moving from one-time to recurring: Robotics-as-a-Service (entry): we charge per vessel / per m² for robotic blasting, coating and inspection — no capital cost to the customer. This wins the account and generates the data. Recurring Hull-Health AMC (core): an annual subscription — inspections, Digital Hull Passport updates and predictive-maintenance alerts — in Bronze (₹5–10 L), Silver (₹15–25 L) and Gold (₹30 L+) tiers per vessel/year. High-margin and sticky. SaaS analytics & licensing (future): fleet analytics, data licensing, and expansion into rail and oil-&-gas. Long-term mix ≈ 70% RaaS + AMC, 25% SaaS, 5% integration — high-margin and recurring. The robot wins the contract; the data keeps the relationship. We acquire customers through direct B2B engagement, because this is a concentrated market — a relatively small number of high-value shipyards and asset owners — so it's about targeted relationships, not mass marketing: Direct outreach to decision-makers at ship-repair, shipbuilding, defence and naval yards (procurement, production and planning heads) — e.g. Cochin Shipyard, GRSE, naval dockyards. Pilots and live demonstrations — we land on a low-risk, zero-CapEx RaaS pilot to prove SA 2½ quality and capture real data, then convert that into a paid contract and a recurring AMC. Tender participation — the demand is already budgeted and tendered (e.g. the live Cochin Shipyard tender), so we bid into existing procurement. Warm introductions & ecosystem — incubators (IIT/SCEI), innovation hubs (e.g. Ratan Tata Innovation Hub), mentors and defence networks opening doors to GRSE, CCNO and naval dockyards. Government / Make-in-India route — the iDEX and indigenous-procurement channels for defence and naval customers. Land-and-expand — once one vessel is in our system, the Digital Hull Passport pulls the customer into recurring AMC/SaaS and into more of their fleet, and strong references drive yard-to-yard expansion. A land-and-expand model: Land with a flagship shipyard beachhead — Cochin Shipyard (187 ships, ₹1,864 Cr repair, FY25), which already tenders this exact scope — on a low-friction, zero-CapEx RaaS contract. Expand the same customer from one-time service into the recurring AMC/SaaS relationship via the Digital Hull Passport, growing revenue per vessel over its life. Channels: direct B2B with ship-repair, shipbuilding, defence and naval yards (GRSE, naval dockyards), pursued via demos, pilots and the iDEX / Make-in-India route, plus incubator and innovation-hub introductions. Scale outward from the beachhead to more Indian yards and adjacent assets (railway wagons, offshore), then to overseas maritime hubs — Singapore, South-East Asia, the Middle East. Our long-term vision is for BlueForge to become the asset-health backbone of the maritime and heavy-industrial world — the trusted system of record for the condition of every large steel asset on water. We start by automating the dirtiest, most manual job in shipyards, but the destination is far bigger: a world where no ship hull, wagon or offshore structure is ever maintained blindly or on guesswork. Every asset carries a living digital twin of its corrosion and coating health; maintenance is predictive and condition-based; workers are out of hazardous blast zones; and owners extend asset life while cutting cost and emissions. Built in India, scaled to the world's major maritime hubs (Singapore, SE Asia, the Middle East) and adjacent sectors (railways, offshore, oil & gas), our ambition is to grow into a ₹300+ Cr company and make industrial assets everywhere safer, longer-lived and intelligent — a Made-in-India deep-tech platform taken global. Incorporated NA Yes We're applying to Avinya (IIT Alumni Council) because at our stage — a working-prototype, pre-revenue deep-tech venture — the right ecosystem matters as much as capital, and Avinya offers exactly that: Deep-tech mentorship & validation — guidance from experienced IIT-alumni founders, technologists and operators to sharpen our product, GTM and fundraising as we move from prototype to pilots. The IIT Alumni Council network — unmatched access to industry, mentors and decision-makers; for a hardware venture selling into shipyards, defence and the maritime/industrial ecosystem, warm introductions and credibility are invaluable. Access to capital & funding agencies — connections to angels, VCs and grant pathways to fund our rover fleet, field trials and first pilots. Like-minded founder community — a peer cohort that helps us move faster and avoid early mistakes. During the programme, our goal is to move BlueForge from working prototype to validated, pilot-ready, fundable company.During the programme, our goal is to move BlueForge from working prototype to validated, pilot-ready, fundable company. Specifically, we want to achieve: Product: complete and field-harden our rover (blasting/coating/inspection) and the Digital Hull Passport platform, and get it demonstration-ready to SA 2½ standards. Validation: secure and run a first on-hull pilot at a shipyard (e.g. Cochin Shipyard / a naval dockyard) and convert at least one pilot into a first paid contract / LOI — turning "demand is proven" into real traction. Mentorship & sharpening: refine our business model, pricing, GTM and investor narrative with mentor guidance, and strengthen weak spots (e.g. domain advisory, certification roadmap). Network & customers: use the programme's ecosystem to open doors to shipyards, defence/naval (iDEX), and industry partners, and build a credible advisory bench. Capital: become investment-ready and close our pre-seed round to fund the rover fleet, field trials and first deployments. Team & IP: formalise roles/cap table (incl. converting to Pvt Ltd), and progress our patent/IP filings. hybrid No Not applicable We're building for India first by design: our beachhead is Indian shipyards (Cochin Shipyard, GRSE, naval dockyards), and we're a purely Made-in-India, import-substituting, iDEX-aligned deep-tech platform addressing India's ₹14,000+ Cr ship-repair market and the national Maritime Development push. Winning at home gives us reference customers, real on-hull data and credibility. But the problem is global — every steel hull in the world is blasted, painted and inspected manually and maintained blindly — so the opportunity is a $40 Bn+ global market. Once proven in India, we scale to major maritime hubs like Singapore, South-East Asia and the Middle East, plus adjacent assets (railways, offshore, oil & gas). In short: built in India, for India — and engineered to take to the world. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/RbUnyAQfnTkP-Investor_Deck-3.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/RbUnyAQfnTkP-Investor_Deck-3.pdf Yes — BlueForge is both mission-driven and impact-focused, and the impact is built into the business, not bolted on. We measure ourselves on a triple bottom line — people, planet and profit: People (safety & dignity of work): hull blasting and painting is one of the most hazardous manual jobs in industry — workers spend hours inside grit-and-fume-filled blast zones. Our rovers take humans out of the blast zone, removing a serious occupational-health risk while up-skilling crews to supervise robots instead of doing dangerous manual labour. Planet (sustainability): we enable 100% grit and dust recovery (less waste and pollution), more consistent coatings, and — through the Digital Hull Passport — predictive maintenance that extends asset life, so fewer ships and structures are scrapped prematurely and lifecycle waste and emissions fall. Better-maintained hulls also mean lower fuel burn and GHG at sea. Profit & nation-building: we keep ship-repair work onshore in India (today ~30% leaks abroad), reduce dependence on costly imported automation, and build indigenous deep-tech capability aligned with Atmanirbhar Bharat and Make-in-India — strengthening a strategically important maritime and defence ecosystem. checked
Jun 20, 2026 @ 12:28 PM Sakshi sah sanjaykumarkgg283@gmail.com 2 Flood warriors india Khagaria We are developing a smart flood alert machine that detects rising water levels and automatically sends alerts to people and authorities before a flood becomes dangerous." Many people do not receive flood warnings on time, leading to loss of lives, property, and livestock. Rural areas are especially vulnerable due to a lack of early warning systems Our machine uses water-level sensors and communication technology to continuously monitor rivers and flood-prone areas. When water reaches a dangerous level, it automatically sends alerts through sirens, SMS, and mobile notifications, giving people time to evacuate and prepare." "Our solution is low-cost, easy to install, solar-powered, and designed for rural Indian conditions. It provides real-time flood warnings without requiring expensive infrastructure, making it accessible to vulnerable communities." Idea Flood-prone communities, village panchayats, disaster management authorities, municipalities, NGOs, and government agencies." Flood-prone regions across India. "Flood-prone districts in Bihar and neighboring states." Villages and local authorities in flood-prone districts of Bihar." "Revenue will be generated through the sale and installation of flood alert machines, annual maintenance services, and government or NGO contracts." Traditional flood warning systems, disaster management monitoring systems, and other IoT-based flood monitoring solutions." We will acquire customers through partnerships with local governments, disaster management authorities, NGOs, village panchayats, awareness campaigns, and direct outreach in flood-prone areas." We will first deploy pilot projects in flood-prone districts of Bihar, demonstrate effectiveness, and then expand through government partnerships, NGOs, and disaster management agencies across India." Our vision is to make every flood-prone community safer through affordable and reliable flood warning technology. We aim to build a nationwide disaster alert network that helps save lives, reduce property damage, and strengthen disaster preparedness across India." Not Incorporated yet (ideal stage) Bootstrapped Yes We are applying to Avinya to receive mentorship, technical guidance, networking opportunities, and support in developing and validating our flood alert solution for real-world deployment." We aim to build a working prototype, validate the technology, improve our business model, connect with potential partners, and prepare for pilot deployments in flood-prone areas. Yes, we are open to both hybrid and virtual participation. No Not applicable NA Our system combines weather forecasts, river water-level data, rainfall patterns, and local geographic information to generate early flood warnings up to 48 hours in advance." "We evaluate the model using prediction accuracy, alert lead time (48-hour warning capability), false alarm rate, missed flood events, and overall reliability of early warnings." Both 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/B45WWbMHk4VZ-By-sakshi-sah_20260619_122211_0000.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/B45WWbMHk4VZ-By-sakshi-sah_20260619_122211_0000.pdf NA checked
Jun 13, 2026 @ 6:30 PM Saumya Bhatt saum996@gmail.com https://www.linkedin.com/in/saumya--bhatt/ https://saum019.github.io/ +919328595592 I am the founder of the company. I have 6+ years building AI before it was cool — now working on making this a successful product. Since I am a single founder I belive this is not applicable to me. 1 Although I am currently building this venture independently, our biggest strength is an unwavering commitment to execution. I have the grit, resilience, and passion to keep moving forward through challenges and uncertainty, while staying focused on creating real value for customers. RuahAI https://ruahai.co.in/ Yet to choose a base RuahAI - Everything your day needs, organized in one place So you can focus on what truly matters. RuahAI brings your tasks, calendar, shopping, fitness, and journal together — powered by AI that listens to how you actually talk. Managing your day should not feel like a second job. Yet most of us are juggling multiple apps, priorities, and responsibilities — and when life gets busy, the first things we let go of are the ones that matter most. Our wellness, our planning, our reflection. Sometimes, without even realising it, the weight of the present holds us back — and we find ourselves drifting further from the life we actually imagined for ourselves. The chaos of everyday life makes it easy to stay busy, and quietly, painfully hard to stay intentional about the life you are trying to build. RuahAI brings everything together in one place. Tell it about your day — by voice or by text — and it organises your tasks, schedules your time, manages your shopping, tracks your wellbeing, and helps you reflect. So your energy goes toward what truly matters, not toward managing the tools meant to help you. It is an AI-powered personal companion app built around one idea — you narrate your day, and the app organises everything for you. It brings your tasks, calendar, shopping, fitness, and journal into a single place, and uses AI to quietly route, structure, and surface what matters, so you spend less time managing your life and more time living it. The deeper mission is wellbeing — not just productivity. The brain dump as the core interaction — Most productivity apps make you do the work of organising. Ruahai does it for you. Just talk, and everything lands where it belongs. Built for the life you want, not just the one you have — Ruahai is not designed around your current habits. It is designed around who you are becoming — gently nudging you toward a version of your day that is healthier, calmer, and more intentional. Not just present-centric, but quietly future-focused. The compounding personal record — Over time, Ruahai becomes a mirror — showing you a picture of the life you are actually living. How you spent your days, how you felt, how you slept, what you prioritised. That depth grows with every day of use, and the longer you use it, the more irreplaceable it becomes — not because it locks you in, but because it knows you in a way nothing else does. Defensibility — Ruahai is built to always be one step ahead. By the time a competitor figures out what users need today, we are already building for what they will need next. That forward momentum is not accidental — it is how the company is designed to move. But the deeper defensibility is the ecosystem. Ruahai does not just log what you tell it. It connects to where you shop, how you move, what you track, and the devices you already use — and weaves all of that into one coherent picture of your life. Over time, that interconnected web of your calendar, your fitness data, your shopping habits, your journal, your tasks — all talking to each other — becomes something that is genuinely very hard to replicate. A competitor cannot just build the features. They would have to rebuild the entire ecosystem, and by then, Ruahai already knows its users in a way no new entrant can match. Idea Users, Revenue, Pilots RuahAI is for: For the student aged 18 to 24 — balancing lectures, deadlines, side hustles, and a social life, trying to grow in every direction at once without losing themselves in the process. For the young professional aged 25 to 35 — navigating a demanding career while showing up for their family, their health, and the personal passions that remind them who they are outside of work. For the entrepreneur aged 28 to 45 — building something from scratch, taking meetings, making decisions, travelling, planning — all while trying to hold the rest of their life together with the same two hands. For everyone juggling multiple responsibilities at once — people who have envisioned a better, more intentional life for themselves, and those who are already living it but know that with the right planning, every day could feel a little more like theirs. NA NA NA We are in the early stages of building RuahAI and are currently focused on developing the product and gathering our first users. Revenue is something we are actively thinking about and will plan more concretely once we have the product. Our priority right now is building something people genuinely want to use — and letting the right monetisation model follow from that foundation. What we are currently considering is a model where the basic experience is free and accessible to everyone. For users who want more — additional features, deeper integrations, and a more personalised experience — a premium subscription tier would be available. The goal is to make sure RuahAI is useful from day one, and valuable enough that people want to go further with it. RuahAI operates in a space where several apps exist but none do what we do entirely. Apps like Notion, Todoist, and Motion cover parts of the experience — task management, scheduling, or AI planning — but they are built for productivity and output, not personal wellbeing. Journaling apps like Reflectly and Daylio cover the wellness side but do nothing for planning or daily organisation. Every existing solution solves one piece of the puzzle. No single app brings all of it together — planning, scheduling, shopping, journaling, and fitness — in one simple, personal, and intelligent experience. That is the space RuahAI is building in, and right now, it is largely open. NA NA Ruahai is built to always be one step ahead. By the time a competitor figures out what users need today, we are already building for what they will need next. That forward momentum is not accidental — it is how the company is designed to move NA In process Yes I want to benefit from the complete offering that you have for a startup and make this a success. Yes Core engine Not yet ready. https://ruahai.co.in/ Managing your day should not feel like a second job. Yet most of us are juggling multiple apps, priorities, and responsibilities — and when life gets busy, the first things we let go of are the ones that matter most. Our wellness, our planning, our reflection. Sometimes, without even realising it, the weight of the present holds us back — and we find ourselves drifting further from the life we actually imagined for ourselves. The chaos of everyday life makes it easy to stay busy, and quietly, painfully hard to stay intentional about the life you are trying to build. This app helps you move past that. Ruahai is not designed around your current habits. It is designed around who you are becoming — gently nudging you toward a version of your day that is healthier, calmer, and more intentional. Not just present-centric, but quietly future-focused. The impact on welness will be really positive. Yes. NA checked
May 1, 2026 @ 1:14 AM Chandravijay Rai foundercareplus@gmail.com https://www.linkedin.com/in/cvrai/ https://play.google.com/store/apps/details?id=app.dermco.ai_dermatologist_skincare +91 706611718 CTO , Software Developer 1 Care+ https://play.google.com/store/apps/details?id=app.dermco.ai_dermatologist_skincare Mumbai Care+ is an AI-powered dermatologist that analyzes skin from images and delivers personalized, evidence-based skincare routines instantly. It is a mobile-first platform designed to make dermatology accessible, affordable, and scalable, starting with India and expanding globally. Access to dermatological care is limited due to high costs, long wait times, and a shortage of specialists. Most users rely on trial-and-error or unverified advice, leading to ineffective treatments, wasted spending, and poor skin health outcomes. Care+ uses computer vision and AI to analyze skin conditions from user-uploaded images and provide personalized skincare routines instantly. It enables users to track progress, receive data-driven recommendations, and make informed skincare decisions without needing immediate clinical access. We are building an India-first AI dermatology system trained on diverse skin tones (Fitzpatrick III–VI), addressing a major gap in existing solutions. Our defensibility comes from a growing proprietary dataset, continuous user feedback loop, and integrated product experience (analysis + routine + tracking), creating a strong data + AI moat over time. Users Users Primary: Individuals aged 16–40 facing common skin issues such as acne, pigmentation, and oily/dry skin, especially in India’s urban and semi-urban markets. Secondary: Skincare-conscious users seeking personalized routines and early adopters of AI-driven health solutions. Global skincare market: ~$180B+ Includes dermatology, skincare products, and digital skincare solutions. India skincare market: ~$3.5B+ Targeting digital-first consumers actively seeking skincare guidance. Initial target: 1–2% of India’s digital skincare users (~$30M–$70M opportunity in early years). Freemium model (limited free scans + paid subscription) Subscription plans (monthly/yearly) Affiliate revenue from skincare product recommendations Future: B2B partnerships with clinics and skincare brands AI skincare apps: SkinVision, TroveSkin, Skin Bliss Indirect: Dermatologists, YouTube skincare influencers, e-commerce product recommendations Organic content (Instagram, YouTube, short-form videos) Shareable AI reports → viral loop (user shares results) Influencer collaborations in skincare niche App Store Optimization (ASO) Phase 1: Organic growth via content + viral sharing loops Phase 2: Paid acquisition (Meta ads, influencer campaigns) Phase 3: Partnerships with dermatology clinics and skincare brands Focus on retention via personalized routines and progress tracking To become the AI layer for dermatology globally, providing instant, personalized skin health guidance at scale. We aim to replace trial-and-error skincare with data-driven recommendations and build a platform connecting users, dermatologists, and skincare ecosystems. After achieving strong user traction, we plan to launch our own line of skincare products tailored to specific user skin conditions, leveraging insights from our AI-driven analysis. Not yet incorporated (in process of incorporation) NA (bootstrapped so far) Yes We are at an early stage where we have built and launched the product and are now focused on scaling user acquisition, improving retention, and refining product-market fit. Avinya offers structured mentorship, access to experienced operators, and a strong startup ecosystem, which can help us accelerate growth and avoid early-stage mistakes. Validate and strengthen product-market fit Scale user acquisition and optimize growth channels Improve retention through better product experience Build early revenue traction and unit economics Prepare for the next stage of fundraising Yes Yes Core engine Care+ uses a fine-tuned ResNet-50 computer vision model trained on dermatological datasets (DermNet, Acne04, FFHQ) for skin condition analysis. The model is exported to ONNX for optimized inference and integrated via a Node.js backend. The mobile app (React Native) captures images and sends them for real-time inference and recommendation generation. We are building a growing proprietary dataset of user-submitted skin images and interaction data (analysis results, routines, progress tracking). This dataset, especially focused on Indian skin tones (Fitzpatrick III–VI), enables continuous model improvement and personalization over time. Our defensibility comes from a data + feedback loop moat. As more users interact with the system, we collect diverse, real-world skin data and behavioral signals, improving model accuracy and personalization. Combined with an integrated product experience (analysis + routine + tracking), this creates increasing returns over time. We evaluate models using accuracy, precision/recall, and confusion matrix on validation datasets. Additionally, we monitor real-world performance through user feedback, repeat usage patterns, and consistency of predictions across multiple scans. User data is handled with strict privacy controls, including secure API communication (HTTPS), restricted access to sensitive data, and anonymization of images where applicable. We follow best practices for data storage and plan to align with global standards such as GDPR as we scale. Yes, as a healthcare-adjacent product, we may be subject to evolving regulations around AI-based medical advice. We mitigate this by positioning Care+ as a decision-support tool rather than a diagnostic replacement and plan to work with dermatology experts for compliance. Potential bottlenecks include inference latency, infrastructure scaling, and model generalization across diverse skin conditions. We are addressing this through optimized ONNX inference, scalable cloud infrastructure, and continuous dataset expansion. Yes, the AI system is built in-house with expertise in computer vision, deep learning, and full-stack integration. We have experience in model training, optimization (ONNX), and deploying AI systems in production environments. We use publicly available dermatological datasets such as DermNet, Acne04, and FFHQ for initial training. We are also building our own proprietary dataset through user interactions and real-world usage. We improve performance through continuous data collection, retraining on diverse datasets, user feedback loops, and iterative model optimization. Over time, this enables better accuracy, personalization, and robustness. We are building India-first, focusing on underserved skin types, with a clear roadmap to expand globally as the product scales. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/d1QVwpmyg183-Routine_Investor_Deck.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/d1QVwpmyg183-Routine_Investor_Deck.pdf https://drive.google.com/file/d/1cvTD_2xCrxm6blEJHoirvXecVSn6klKU/view?usp=sharing Care+ is mission-driven to make dermatology accessible and affordable at scale. Millions lack timely access to specialists and rely on trial-and-error skincare. By providing instant, AI-driven analysis and personalized guidance, we aim to improve skin health, confidence, and reduce unnecessary spending—starting with India and expanding globally. NA NA We’ve built and launched Care+ end-to-end (AI model, backend, and mobile app) and are iterating quickly based on real user feedback. We’re actively seeking mentorship on GTM, retention, and regulatory pathways, and are open to pilot collaborations with dermatologists and healthcare partners. checked
Apr 15, 2026 @ 3:41 PM Yash Garg yash@naviget.in https://www.linkedin.com/in/numberbee https://naviget.in +919873001058 Yash - CTO, Btech IIT BHU 2023, Previously engineer at AWS, Singlestore, and tech startups. Anmol - CEO, Previously built startups in edtech and food tech space, MBBS dropout We met in 2022 and were working in an edtech startup in Bangalore. We ideated Naviget in 2023, at that time we were building a price comparison app for cabs using ONDC, we continued doing this until early 2025. And later on we pivoted to aggregating premium cab services. All - Being in this market for sometime we understand the customer's needs. - Having served around 500 scheduled pre-paid rides, we understand the operations of this business. - Already partnered with multiple premium EV cab hailing companies. - Our execution speed: We have tried multiple experiments in past few months and quickly pivoted to premium & reliable ride hailing market after Blusmart's bankruptcy. We believe our execution speed and energy will help us build, break and innovate faster than anyone. Naviget https://naviget.in Bangalore Aggregator of premium ride hailing services Consistency and reliability of online cab services We aggregate premium cab services. All existing ride online cab apps have consistency and reliability issues. We promise zero cancellations, on time pickup, safe driving, AC always on. In fact Blusmart tried to solved all of these but ultimately shutdown, many of our current users previously used blusmart. Many companies are entering this space of reliable EV ride hailing, but all of them have fewer than 50 vehicles. This is an opportunity to become an aggregator. We are serving airport rides right now, but will soon expand to city rides also. There are existing services. Uber black -> None of our partners wants to work with them due to their terms. Makemytrip -> Such travel companies' focus is on airport, outstation and rental rides, but this is mostly upselling, the platform does not offer everything in ride hailing like - car tracking on app, city rides, office commute. Users Signups, Testimonials Ideally people in metro cities who earn more than 15 Lakhs a year. It includes all of the customers who earlier used blusmart for reliability even though they were on the expensive side. $20 B $7 B $700 M We charge a percentage commission on every ride ranging from 5-10% Uber black, Makemytrip, Goibibo Social Media and referrals Vehicle interior and exterior advertisements, B2B partnerships like - concierge, airlines. We want to keep our platform exclusively for reliable cab services. Anyone who wants to start their cab service will come and work with us. We also want to offer full tech stack integration in long term like vehicle tracking GPS devices, 3 way dashcams in cars, etc. instead of solely relying on driver's smartphone like other platforms. Integration into the car charging infra, real time tracking of car charging, etc. possibly expanding ourselves into smart devices in the EV OEM market as the need arises. Private Limited registered NA Yes Mentorship and more prospects to fund raising Networking and Industry connects Yes No Not applicable Indian market for now. checked
Feb 2, 2026 @ 12:49 PM ramunivagaira gnanaprakash gnanaprakash@iittp.ac.in https://www.linkedin.com/in/gnana-r-310644261/ http://NA +91 7396144250 founder We met through LinkedIn, where we connected based on shared interests in technology and startup building. He is an student of IIT Madras. We have been working together for the past 6 months, collaborating closely on ideation, market validation, and early-stage product planning for this startup. No Our biggest strength as a team is the combination of deep technical problem-solving and practical execution. We complement each other with strong engineering and research experience from IIT ecosystems, while staying tightly aligned on building a market-driven, outcome-focused product. This balance allows us to move quickly from insight to implementation. deepenk NA Yes. I am currently working as a Project Scientist at IIT Tirupati on an industry-oriented robotics research project. An AI-powered decision engine that helps users instantly choose and complete the best possible option for shopping, food, rides, travel and hospitality without switching between multiple apps. Consumers waste time and money comparing prices, offers, delivery times, and reviews across many platforms. Even after checking multiple apps, users still struggle to identify the true best choice because prices, availability, reliability, and execution quality constantly change. The platform acts as a single AI brain that understands what the user wants, evaluates all viable options across commerce platforms, and decides the best execution path automatically. Users don’t compare they ask once and act. Others help users choose. Our AI decides and executes — across ONDC and all platforms.” MVP Signups 60,000 cr 20,000 cr 15,000 cr Transaction margin on ONDC in-app executions Affiliate commission from redirected platforms Aggregated intelligence for sellers and brands Demand insights for partner brands buyhatke, honey Product-led growth: Users discover us through search, referrals, and demos because the value is immediate (one ask → best decision). ONDC ecosystem leverage: Discovery through ONDC-aligned partners, sellers, and use cases. High-utility use cases: Food, rides, and deals drive repeat daily usage and word-of-mouth. Founder-led early adoption: Campus users, young professionals, and early adopters for MVP validation Phase 1: Launch in top cities with high-frequency categories (food, rides, essential shopping). Phase 2: ONDC-first in-app execution + smart redirection where needed. Phase 3: Expand across categories (travel, services) and partner with sellers/brands using insights. Phase 4: Scale nationally as the default AI decision layer for commerce To become the AI decision layer for commerce and services in India where users ask once, and the system decides and executes the best way to buy across all products and services. NA na Yes for alumuni network and incubation mentorship support, funding support Validate our AI decision-layer + ONDC-first model with real users Refine product-market fit for high-frequency use cases (food, rides, shopping) Get guidance on architecture, compliance, and scaling within the ONDC ecosystem Prepare for pilot launches and partnerships with sellers and platforms Sharpen our go-to-market and investor readiness Yes open to hybrid mentoring sessions. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/Z6vedWQVnewJ-DEEPENK-PP_cm.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/Z6vedWQVnewJ-DEEPENK-PP_cm.pdf http://NA Yes. Our mission is to simplify digital commerce and make fair access possible for everyone. By using an AI decision layer and ONDC-first execution, we help users save time and money, support local sellers, and reduce dependency on closed, high-commission platforms. The impact is better outcomes for consumers and more equitable access for small and regional businesses. NO IIT TIRUPATI E-cell We are currently focused on MVP validation, building with simulated data to demonstrate the final user experience. The goal is to validate user behavior, decision accuracy, and ONDC-first execution before scaling with real integrations. checked
Jan 27, 2026 @ 4:00 PM Nisha Mutneja Ishan Grover nishamutneja@gmail.com https://www.linkedin.com/in/nishamutneja/ http://NA +91 8767673231 Nisha Mutneja (Co-Founder & CEO) Core Expertise: Market Research, Business Model Scaling, Product Development, and Growth Strategy. Nisha brings a robust background in building and scaling technology solutions globally. She led the growth strategy for the conversational AI startup, ConvoZen, where she successfully scaled the business from $100K to $1.5 Million ARR within one year. Her experience also includes founding a Metaverse EdTech startup, scaling it to 20,000 students, and holding a pivotal Business Lead role at The Viral Fever (TVF). This background ensures our solution is designed for market viability, user adoption, and long-term financial sustainability. Education: Integrated M.Tech in Nanotechnology, IIT Bombay & Amity University. Work Experience: Director GTM - ConvoZen, Founder - TalentedHippo. Business head at TikTok, TVF. Ishan Grover (Co-Founder & CTO) Core Expertise: AI Engineering, Multilingual NLP Development, and Data Science. Ishan provides the essential technical depth required to build a sophisticated and reliable AI Companion. He served as the AI Engineering and Data Science Lead at ConvoZen, where he was responsible for architecting and optimizing the scalable conversational AI solution that garnered national recognition. His experience, including time at Ola, ensures our product is built on robust, performant, and secure infrastructure, capable of handling the nuances of regional linguistic models and real-time distress detection. Education: B.Tech, IIT Guwahati. Work Experience: AI Lead at ConvoZen, Data Scientist at Ola. We met on the very first day of our jobs at ConvoZen (NoBroker Group) while completing joining formalities. What started as a chance meeting quickly turned into a close working partnership—we were soon collaborating across multiple projects, including AI India initiatives, and found ourselves naturally aligned in how we thought about problems, users, and execution. Over the next one year at ConvoZen, we worked side by side almost every day. Many of our best ideas came from long lunch conversations that blended work, life, and curiosity. Over time, we became more friends than co-workers—we built deep trust, complementary strengths, and a shared way of thinking. That trust is what led us to start this company together. We’ve now been building this startup for the past 3–4 months, with the confidence that comes from having already worked closely under real pressure and responsibility. No Our biggest strength is the combination of deep technical execution and sharp product-market judgment, built on real experience working together under pressure. Ishan brings strong AI engineering depth and the ability to turn complex ideas into reliable, scalable systems. Nisha brings clarity on users, business viability, and go-to-market execution—ensuring what we build solves a real problem and can sustain itself as a business. What makes this truly powerful is that we’ve already worked together for over a year in a fast-moving AI startup, shipping production systems, solving hard problems, and making decisions together daily. We have strong trust, honest communication, and a shared bias toward execution. In practice, this means we move fast without losing focus—building the right product, not just interesting technology, and aligning technical decisions tightly with user needs and long-term impact. Shoonya AI Technologies PVT Ltd NA Dual Degree Dissertation, Btech A culturally intelligent AI companion designed to reduce loneliness and support everyday life for the elderly India is rapidly becoming an ageing society, with 150M+ people over 60 today, projected to double over the next two decades. At the same time, families are becoming nuclear, geographically dispersed, and time-constrained—leaving many elderly people emotionally alone. Loneliness isn’t just a social concern. Large global studies cited by the WHO and Harvard researchers show that chronic loneliness and social isolation in older adults are associated with a ~25–30% higher risk of early mortality and a ~30% higher risk of cognitive decline and dementia, along with significantly increased rates of depression and anxiety. Yet most solutions today focus on physical health or emergencies, while daily emotional connection—conversation, familiarity, and feeling heard—remains largely unaddressed, leaving a vast elderly population emotionally unsupported in everyday life. We are building a culturally intelligent, multilingual AI companion for the elderly that provides emotional support, daily assistance, and meaningful companionship—designed for trust, simplicity, and long-term engagement. At its core, the companion is emotionally aware and grounded in evidence-based wellbeing and emotional-support frameworks. It is designed to recognize emotional states such as loneliness, anxiety, or low mood and respond with empathy, reassurance, and stabilizing conversation—without positioning itself as clinical therapy or medical care. What differentiates our solution is its deep cultural intelligence. The AI can engage using familiar philosophical and spiritual frameworks—such as ideas of karma, dharma, acceptance, devotion, and life cycles—which many elderly users already draw upon for comfort and meaning. This allows conversations to feel emotionally safe, relatable, and reassuring rather than generic or transactional. The companion supports everyday needs through: -Natural, voice-first conversations in the user’s preferred language -Gentle emotional check-ins and companionship -Reminders for medications, routines, and appointments -Culturally familiar stories, reflections, and cognitive engagement -Detection of emotional or behavioral shifts, with optional caregiver alerts Designed specifically for seniors with low tech literacy, the experience is intuitive, non-intrusive, and dignity-preserving. For families and caregivers, it offers peace of mind—while ensuring the elderly user retains autonomy, privacy, and agency. In essence, we are creating an AI companion that blends emotional intelligence, cultural familiarity, and practical support—helping elderly users feel heard, supported, and less alone in their daily lives. Emotional wellbeing as the core use case: Built first and foremost for daily emotional support and companionship—not utilities or monitoring. Deep cultural intelligence: Conversations draw on familiar language and value systems (e.g., acceptance, devotion, life cycles), creating trust and emotional safety that generic assistants lack. Elderly-first design: Voice-led, low-cognitive-load interactions designed specifically for aging users, not adapted from consumer tech. Compounding personalization: Longitudinal understanding of emotional baselines, routines, and preferences increases relevance and retention over time. Proven execution capability: Built by a team that has already shipped and scaled real-world conversational AI together. MVP Pilots Elderly individuals (60+) living alone or semi-independently, especially those experiencing loneliness or reduced daily social interaction Elderly users with low to moderate tech literacy, who benefit from simple, voice-first, culturally familiar interfaces Adult children (35–55 years) living away from parents and seeking peace of mind without intrusive monitoring Family caregivers looking for consistent emotional support and daily engagement for elderly loved ones Senior living communities, home healthcare providers, and NGOs focused on elder wellbeing and engagement India TAM ≈ ₹75,000 Cr annually (~$9B) TAM calculation: 150M elderly (60+) × ₹5,000/year (avg) Assumptions: Target population: Elderly (60+) in India ~150M people today, projected to exceed 300M by 2050 Blended annual ARPU (B2C + B2B): ₹4,000–6,000 (₹299–499/month subscription, post-hardware) India SAM ≈ ₹15,000 Cr annually (~$1.8B) SAM calculation: 30M reachable elderly × ₹5,000/year Assumptions: ~20% of elderly are digitally reachable Urban & semi-urban households Smartphone / voice-device access via self or family Middle & upper-middle income families India SOM ≈ ₹200–300 Cr annually (~$25–35M) SOM calculation: 500,000 users × ₹4,000–6,000/year Assumptions: Initial India-first rollout Urban families + senior living communities ~1–2% penetration of SAM over 3–5 years We follow a hardware-enabled, subscription-led revenue model designed to lower adoption friction while building long-term recurring revenue. One-time Hardware Sale (Initial): Customers purchase a dedicated, elderly-friendly device priced at ~₹7,000, optimized for voice-first interaction, low cognitive load, and high reliability. This creates immediate revenue while anchoring daily usage. Subscription (Post Year 1): After the first year, users transition to a monthly subscription of ₹299–499, covering AI companionship, emotional support, multilingual conversations, reminders, and ongoing personalization. B2B / B2B2C Licensing: Senior living communities, home healthcare providers, NGOs, and institutions can deploy the device at scale via bulk hardware pricing + per-user licensing contracts. Premium Add-ons (Optional): Paid caregiver dashboards, emotional trend insights, and priority alerts for families and caregivers. Indirect competition: Amazon Alexa and similar general-purpose voice assistants that elderly users may use for basic tasks. These products are command-driven and transactional, and are not designed for emotional companionship, cultural grounding, or elderly-first interaction. Direct competition: There are currently no well-established, scaled AI companions built specifically for elderly emotional companionship with cultural and linguistic grounding, particularly in India. Existing solutions either focus on utilities, monitoring, or Western-centric companionship rather than daily emotional engagement and trust. This positions us in a largely untapped category at the intersection of emotional intelligence, cultural familiarity, and elderly-first design. We are currently pre-launch and do not have customers yet. Our planned acquisition channels are: Adult children (35–55 years) via digital marketing and referrals, as they are the primary decision-makers for elderly parents Housing societies, senior communities, NGOs, and religious/community centers as trust-led distribution points Home healthcare providers and elder-care service companies through B2B/B2B2C partnerships Assisted onboarding and demos, ensuring high activation among elderly users Our GTM strategy follows a phased rollout: Phase 1: Pilot & validation (0–6 months) – Small pilots (20–50 users) to validate engagement, trust, and safety Phase 2: Family-led B2C launch (6–12 months) – Scale through families using a one-time hardware purchase Phase 3: Institutional partnerships (12–24 months) – Expand via senior living communities, NGOs, and healthcare partners Phase 4: Subscription & retention – Convert engaged users to subscription after Year 1 To become the most trusted emotional and care interface for aging populations—helping people age with dignity, connection, and meaning at global scale. Start with one product people pay for Sell a simple, elderly-friendly device and earn recurring revenue through a subscription once users see daily value. Increase value for families over time Add paid features for families and caregivers—such as wellbeing summaries, alerts, and coordination—only after trust and usage are established. Work with organizations that care for elders Offer the same product to senior living communities, home-care providers, NGOs, and insurers through contracts instead of individual sales. Use one core system across many devices Extend the companion into other useful devices (wearables, medication aids, home units) without rebuilding the product each time. Share insights responsibly with institutions With user consent, provide anonymized insights that help healthcare systems and governments improve elder care—creating another revenue stream. Repeat this model in other countries Adapt language and culture, while keeping the business model and technology the same. Ongoing NA Yes We are applying to the IITACB Incubator (IIT Alumni Centre Bengaluru) because it offers the unique combination of infrastructure, mentorship, and ecosystem connectivity critical for early-stage deep-tech and AI startups like ours. IITACB provides founders access to seasoned mentors, industry networks, and collaborative spaces that help turn visionary ideas into scalable, real-world solutions—exactly what we need to refine our product, accelerate go-to-market execution, and build credibility in the elder-care tech space. Being part of IITACB also connects us to a broader innovation ecosystem of IIT alumni, investors, and research partners in Bengaluru, which will help us strengthen our technical foundation, access potential partners and customers, and prepare for investment conversations. We believe that this environment—blending practical startup support with world-class mentorship and networking—will significantly boost our ability to scale responsibly and impactfully in the elderly tech and AI companion domain. During the programme, we want to move from a strong concept to a validated, deployable product with clear proof of demand and a credible path to scale. Specifically, we aim to: Build and ship a working MVP of the AI companion hardware + core software, ready for real-world elderly use. Run structured pilot deployments with 20–50 elderly users to validate daily engagement, trust, emotional usefulness, and usability. Refine product-market fit by iterating on onboarding, interaction design, and cultural/emotional responses based on real user feedback. Validate pricing and willingness to pay, including the ₹7,000 device price and post-year subscription model. Establish early partnerships with senior communities, NGOs, or elder-care providers for potential B2B/B2B2C rollout. Strengthen our go-to-market and compliance readiness, including ethics, data privacy, and safety boundaries for elderly users. Prepare for the next stage of growth, including a clear roadmap, metrics, and investor readiness. By the end of the programme, our goal is to have a validated product, real user evidence, and a clear execution plan for scaling responsibly in the elderly care ecosystem. yes Our startup is mission-driven, with impact built directly into the product. We are addressing the growing problem of loneliness and emotional neglect among the elderly, especially as families become smaller and more geographically dispersed. Our AI companion provides daily emotional support, familiar conversation, and practical assistance—helping elderly users feel heard, supported, and independent. We believe impact must be sustainable to scale. Families and institutions pay for peace of mind and better outcomes, while elderly users receive consistent, non-intrusive support. Our success is directly tied to reducing loneliness and improving everyday wellbeing for aging populatio Yes. As a woman founder building a deep-tech and AI startup, I am part of an underrepresented group in the technology and startup ecosystem, particularly in roles involving AI engineering, product leadership, and company building. This perspective shapes how we build—bringing a strong focus on empathy, inclusion, and real-world usability—especially important when designing technology for vulnerable and often overlooked populations like the elderly. Santosh Arali checked
Jan 10, 2026 @ 5:07 PM Dr. Vasu Shanmugham vasuphy07@gmail.com https://www.linkedin.com/in/v%20asu-shanmugam-150537273/ http://NA +919751474633 As a battery technology specialist with deep experience across the full value chain—from raw material design to cell and pack development—I am passionate about enabling India’s clean energy transition through innovation in sustainable energy storage. Having worked with global automotive leaders such as Volvo Cars in Sweden, I bring a strong technical and industrial perspective to develop localized, scalable, and high-performance solutions in battery materials. My focus lies in advancing cathode active materials (CAM), leveraging data-driven R&D and clean process engineering to support India’s electric mobility and renewable energy ambitions. Through my startup initiative, I aim to build a robust, indigenous supply chain that integrates cutting-edge science, AI/ML, and sustainable manufacturing to deliver impactful solutions for the nation’s energy security and net-zero goals. Yes My biggest strength is the novelty and the uniqueness of the product, which is the first of its kind being patented and developed in Bharat, with me holding the patent for the Cathode Active Material production technology, which is a crucial component in battery manufacturing process and is currently being imported 100% into the country. Taking this technology to the market will reduce our import dependency to a large extent. Enercell Material Techonology Private Limited Ph.D IIT Madras Patent-filed Cathode Active Material (CAM) production technology, which is a critical component in EV batteries, currently 100% imported India's energy storage and EV sectors are heavily import-dependent, with 60-85% of battery cell costs tied to imported materials, creating supply chain vulnerabilities, cost risks, and delays. No scalable domestic cathode active materials (CAM) solution exists despite government PLI schemes pushing for 60% domestic value addition and projected demand of 150,000-193,000 tons by 2030. This reliance on China-dominated imports (70% global share) exposes manufacturers to geopolitical risks, price volatility, and hinders localization goals for EV boom (15 GWh in 2025 to 65 GWh by 2030) and stationary storage. Enercell develops indigenous CAMs for lithium-ion (LFP, LMFP, NMC series) and sodium-ion batteries, using AI/ML for rapid discovery, optimization, sustainable processes, fast development cycles, and scalable, OEM-ready manufacturing. The B2B model supplies battery manufacturers and OEMs, localizing the supply chain to cut import dependency, mitigate risks, and enable PLI compliance. Phased GTM includes R&D/pilot partnerships (2025-2027), India/APAC scaling (2027-2030), and global expansion, with revenue from material sales, IP licensing, consultancy, and JVs led by Dr. Vasu Shanmugam and IIT-experienced team. First of its kind in Bharat since presently we are importing 100% CAM, primarily from China. Enercell can become an effective replacement to this import dependency and can become a global player in the next 5 years. MVP Pilots Battery manufacturers USD 28 Billion USD 1.5 Billion USD 200 Million in the first year of operations. Licensing and royalty; joint ventures with established players like Tata Batteries and Amaron; slowly migrating to owned manufacturing model Himadri Specialty Chemicals, Altmin Private Limited, Epsilon Advanced Materials. Through one on one interaction and negotiation to top-level decision makers since this is a purely B2B product. Getting into Licensing/Royalty sharing or Joint Venture with reputed battery manufacturers after conducting pilots with them for checking our industrial grade quality and efficiency. To become a global player in the Cathode Active Material (CAM) market, which is presently dominated by China, but can be captured through better quality and value for money. Private Limied Bootstrapped Yes Apart from the opportunity to work again with my IIT peers, it will give me a unique opportunity to network with my peers, thereby helping me in getting the right connects for reaching the right markets. We want to have three good players in the EV/Battery manufacturing sector becoming associated with us in commercial capacity for developing our business. Yes. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/y0tIl9YOYzHv-Enercell-Pitchdeck.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/y0tIl9YOYzHv-Enercell-Pitchdeck.pdf EnerCell targets critical gaps in battery cathode materials by developing indigenous, advanced CAMs (LFP, LMFP, NMC, sodium-ion) using AI/ML for rapid discovery. Core mission centers on reducing India's 60-85% import dependence, enabling PLI scheme compliance (60% domestic value addition), and supporting national EV/energy storage growth (193K tons CAM demand by 2030). Impact Elements Sustainability: Differentiates via "environmentally friendly processes" and sustainable manufacturing, contrasting China-dominated low-cost imports. Economic Localization: Bridges supply chain vulnerabilities, creates domestic jobs, and cuts costs/risks for battery OEMs in a $1.2-1.5B 2025 India CAM market. ​Phased National Contribution: R&D/pilots (2025-27) scale to India/APAC leadership (2027-30), aligning with Make-in-India and PLI incentives. Yes. Battery manufacturing is a very niche area in the startup ecosystem. RaM Ventures Shortlisted for DST NIDHI grant scheme at NIT Trichy incubator and IIT Mandi PropelX grant scheme. checked
Jan 10, 2026 @ 1:17 PM Tarun khandelwal Tarunkhandelwal123@gmail.com 09460190079 petroleum engineer Yes battery recyclem b tech scrap battery recycling profit and future demands MVP Revenue loham Yes yes checked
Jan 1, 2026 @ 11:26 AM Testing Form Submission Testing Form Submission http://Testing%20Form%20Submission http://Testing%20Form%20Submission Testing Form Submission Testing Form Submission Testing Form Submission No Testing Form Submission Testing Form Submission Testing Form Submission Testing Form Submission Testing Form Submission Testing Form Submission Testing Form Submission Users Revenue Testing Form Submission Testing Form Submission Testing Form Submission Testing Form Submission Testing Form Submission v Testing Form Submission v Testing Form Submission Testing Form Submission Testing Form SubmissionTesting Form SubmissionTesting Form SubmissionTesting Form SubmissionTesting Form SubmissionTesting Form SubmissionTesting Form SubmissionTesting Form SubmissionTesting Form SubmissionTesting Form Submission No Testing Form Submission Testing Form Submission Testing Form Submission 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/55JVmF8NHsCN-importance-of-startup.png, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/55JVmF8NHsCN-importance-of-startup.png http://Testing%20Form%20Submission Testing Form Submission Testing Form Submission Testing Form Submission v checked
Jan 1, 2026 @ 10:55 AM jerry jerry@gmail.com http://linkedin.com/in/jerry http://NA +91 9887653362 web designer 1 year No team work ARAMS NA sdfghm asdfgh fghg asdgf MVP Revenue efgrd fsgbnv afdsfdgfbnv asdfgb sdf sxdcvb asdfgb asxdcvb asdfvb asxdcvb savbn No asdfvb asdb sdvb 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/TtZHOIdGtobv-Start-up-Business-Advisory.jpg, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/TtZHOIdGtobv-Start-up-Business-Advisory.jpg http://asdfvgb sdcvb sdb sdfg sdvb checked
Dec 29, 2025 @ 4:49 PM Ramakrishnan Selvaraj uday@quantindia.tech http://linkedin.com/in/uday-mukundamgari-55180628 http://catbots.tech 91 8790095951 Ramakrishnan Selvaraj, Co-founder, Head of Dev | Uday Kumar, Co-founder, Managing Partner While building algorithmic trading bots for Indian markets. We have been working together for 7 years. Yes Deep expertise in financial/crypto markets Full spectrum of software development catBots catbots.tech Automated trading platform for crypto High entry barrier to access risk/reward balanced investing strategiesin crypto Automated trading with optimized risk/reward strategies Market adaptability, resilience of the bots Users Signups HNI's, Hedge funds, Family Funds NA NA NA Software Service Fee + Profit Share Algo trading platforms referrals, word of mouth NA To be best in class automated trading platform in crypto NA 0 Yes To spread the word, gain customer, go to market strategy To spread the word, gain customer, go to market strategy Hybdrid 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/zii9Mkhzuwfm-Catbots_Designed_PD_v5.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/zii9Mkhzuwfm-Catbots_Designed_PD_v5.pdf impact-focused. Objective is to onboard clients as the impact of automated trading is clear and evidenced through results. NA IITians Whatapp checked
Dec 28, 2025 @ 4:26 PM Harsh Kumar jha@faoud.com https://faoud.com 06201001984 Harsh : Growth, Technology, Artificial Intelligence, Strategy and Scaling, Vash : FMCG Industry Expertise + Sales & Business Development Me and Vash have now worked for 2 years together while building faoud, and understanding what needs to changed. Vash has been in the fmcg manufacturing industry for now 5 years, and started with contributing a great deal during manufacturing of Sanitizers during covid initial lockdown period. I met Vash at an event in IIT Bombay, where he had come as an investor and I was pitich for my that time project. That project finished and we stayed in touch. We sat on the topic of taking manufacturing online and networked and hence inception of Faoud, your factory on cloud happened. We are going strong today and are have a vision of taking india's manufacturing to its new generation. Yes We come from a backgroud of engineers, our team conviently distributes well into network /algorithm and manufactruing. We have from very initial days put in very core of the company that Faoud stands to use software to solve a long going problem or fragmented and unreliable process of manufacturing in india. We focus on msmes and smes to put them in a network that looks at them as a facility with technology and a potential to grow. Faoud : Factory on Cloud https://faoud.com Only Online Contract Manufacturing Service where FMCG Brands can get Finished Goods from Factories direct to warehouse. FMCG contract manufacturing today is primarily “project to project” P2P basis which is fragmented, slow, and opaque—making it hard for brands to turn around the entire manufacturing project within stipulated timeline and budget. Also it is difficult for brand owners to find reliable factories and leaving large factory capacity underutilized. World’s Only Online Contract Manufacturing Service where FMCG Brands can get Finished Goods from Factories direct to warehouse. A. How Faoud benefits stakeholders: 1. For Brands - Faoud uses AI to pick the right factory for every order, and AutoBid gives instant, competitive pricing, to all partner Brands 2. Faoud brings factories steady business and clear standards, so they share capacity and keep service quality high. B. Faoud puts the entire contract manufacturing process, finding factories, managing production, and QC, onto one simple platform. C. Faoud verifies every partner, protects data, and gives full visibility, so both sides work with confidence. Faoud is defensible because it combines software, data, supply-side control, and execution expertise into a manufacturing operating system that compounds with every order. Users Users, Pilots, Signups Faoud’s target customers are D2C brands, emerging FMCG companies, and mid-sized enterprises that want to launch or scale cosmetics, nutraceutical, food, or pharma products quickly without building or managing their own manufacturing infrastructure. $ 1000 Billion (Global FMCG Contract Manufacturing Market) $ 1.3 Billion (Indian FMCG Contract Manufacturing Market) $ 130 Million ( 10% of SAM ) Manufacturing Commision IndiaMart(Sourcer Path - Alternate competitior), No real direct competitors. NA NA Faoud’s long-term vision is to become the default manufacturing infrastructure for FMCG brands, quietly powering how products are formulated, produced, and delivered—much like cloud platforms do for software—by making manufacturing faster, more predictable, and accessible without requiring brands to own factories or manage complex supply chains. Done None Yes To get connected to like mided people to share our vision with, and even possibly find an investor. Possibly Investment, Guidence into the industry, Collaborators. All works. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/ZwejJL4xDKFi-Pitch-Deck-Faoud-28-December.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/ZwejJL4xDKFi-Pitch-Deck-Faoud-28-December.pdf https://youtu.be/9OKpPvAA3to Yes, Faoud is a mission-driven startup with a strong, practical impact focus. Our mission is to democratize access to manufacturing by making high-quality FMCG production faster, more transparent, and less capital-intensive. Today, manufacturing is inefficient and skewed in favor of large incumbents, forcing emerging brands to navigate long timelines, opaque pricing, and high minimum order quantities. Faoud reduces these structural barriers by turning manufacturing into a shared, on-demand infrastructure that enables small and mid-sized brands to compete on speed, quality, and innovation. At the same time, we create meaningful impact on the supply side by improving capacity utilization, predictability of demand, and revenue stability for partner factories—many of which are underutilized despite strong capabilities. By aligning incentives between brands and manufacturers through technology, data, and standardized processes, Faoud delivers impact that is embedded in its business model rather than treated as a parallel objective. NA TEG_Global checked
Dec 28, 2025 @ 3:40 PM Bharatheesha PL bharatheesh@medi-impact.com https://www.linkedin.com/in/bharatheesh-pl-27137425/ https://medpashealth.in/ +919008983388 Co-founder & CEO , Bharatheesh has 18+ years of leadership experience in HealthTech & Digital Healthcare Expertise in product strategy, B2B growth, and SaaS-based health solutions Awarded ‘Entrepreneur of the Year’ by Business Connect; published corporate author Ex-Business Head, Birlamedisoft, Ricoh Innovations MBA, Annamalai University I and my co-founder Srinivas use to work for Ricoh innovation a Japanese MNC , we worked together for 5 years and I know him from past 10 years now ... Yes Strength is very senior and domain expert team on the leadership position as well as core team Mediimapct Healthcare Pvt Ltd - Medpass https://medpashealth.in/ Medpass, India’s First Health mobile wallet app dedicated for usage across healthcare and wellness providers Unable to fund healthcare and access to quality care The Solution: MedPass An Integrated Healthcare Ecosystem Powering India’s Digital Healthcare Revolution All-in-One App for Quality Care, Cost Savings & Financing All-in-One App for Quality Care, Cost Savings & Financing Revenue Revenue Broad statement – Anyone needs healthcare services would be Medpass customer , it cover covers from just born baby up to 90 years Early adopter as per the current data Age range from 35 to 75 years are our most used customers ₹23,490 Cr 600 Cr 325 Cr B2B2C Afford plan , Qube health During Offline events and online campagains All-in-one digital healthcare app that combines access to quality care, medical loans, insurance, & instant cost savings - creating an integrated ecosystem for patients, healthcare providers, & financial partners To be present in all metropolitan city's and Tyre 2 & 3 city's And support our customers to access quality healthcare and save money on every trx as well 22062020 2.5 Cr Yes Community and funding support Networking and fund raising and learn as well Yes for online 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/uu42lii89s9X-1Growth-Story-Deck-Medpass897.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/uu42lii89s9X-1Growth-Story-Deck-Medpass897.pdf https://www.youtube.com/watch?v=VhP9LqN_WrU&t=81s ediimpact Healthcare Private Limited is a Bangalore based Healthtech company and creator of Medpass, India’s First Health mobile wallet app dedicated for usage across healthcare and wellness providers Medpass is a digital platform that supports consumers to improve the management of their health expenditures. Medpass wallet can be used at healthcare providers such as hospitals, clinics, Homecare services, laboratories, pharmacies and other healthcare providers . MedPass wallet that could be used for all healthcare Services under one platform and Customers save money on each transaction No Received an email NA checked
Dec 27, 2025 @ 2:10 PM Radha Baran Mohanty radhabaran.mohanty@datamatrixai.co.in https://www.linkedin.com/in/radhabaran-mohanty-50938227/ http://www.datamatrixai.co.in 8847822146 Co-Founders We started working together in December 2024 while we were part of the IISc Generative AI and Prompt Engineering course. year Yes Datamatrix.AI Pvt Ltd brings together IIT-rooted leadership and deep enterprise technology expertise to build robust and scalable AI-driven products. One of our co-founders is an IIT alumnus with 27+ years at Infosys, where he last served as Delivery Manager for North America clients, leading large-scale digital transformation programs. His leadership sets a strong foundation of strategic clarity, process excellence, and enterprise-grade execution capability. Our engineering team comprises 10 senior AI professionals, the majority of whom have 15–27 years of experience at Infosys across AI, data engineering, enterprise architecture, and software delivery. This seniority and breadth of experience give us a unique advantage: we combine startup agility with enterprise-level rigor, ensuring reliability, security, and scalability in every solution we build. We have already developed commercial-ready AI products, including a usage-based global Speech-to-Text SaaS platform, an AI-driven BI insights chatbot, and multiple agent-based automation tools that extract intelligence from multimodal enterprise content (PDF, PPT, Confluence, SharePoint, Tableau, etc.). These products demonstrate our ability to convert complex business challenges into market-ready solutions. Our strength lies in building practical, high-impact AI systems grounded in real-world enterprise needs—automating workflows, improving decision-making, and enabling operational efficiency for businesses in BFSI, retail, and B2B services. With IIT alumni leadership, seasoned engineering talent, and proven product-building capability, Datamatrix.AI is equipped to leverage the IIT Bangalore ecosystem and scale into a globally competitive deep-tech AI company. Datamatrix.AI Pvt Ltd https://datamatrixai.co.in Datamatrix.AI is transforming how enterprises work by building reliable, real-world AI systems that automate processes and deliver insights. Responsibly. Organizations today are drowning in documents and dashboards. Key business insights are locked inside fragmented reports, presentations, and siloed data platforms. CXOs and senior leaders face delays, blind spots, and inefficiencies due to: ·Time-consuming manual analysis ·Poor integration across formats and platforms ·Limited access to insights at the point of decision-making EDIS(Enterprise Document Intelligent System) transforms how leaders consume and interact with data. It: ·Automatically generates insights, summaries, trend analyses, and strategic reports through Natural Languge Queries from any format of data(structured and unstructured. Turn unstructured and structured enterprise documents into instant, actionable insights without depending upon an analyst with privacy and security of the data.. Revenue Revenue, Pilots Enterprise level CXO's, Functional Heads, Senior Management USD 25 Billion USD 5 Billion USD 1 Billion Licence Based and SaaS based HILA by Vian.ai From known network, LinkedIn and references Direct Sales, Partnerships with SI, Engage CXO's in enterprise events Build Datamatrix.AI into a AI focused firm with products and services that cater to Enterprise solutions needs. Pvt Ltd NA Yes For mentoring, incubation space, funding and networking. Funding Not now 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/wDZVmg7XoC0c-DatamatrixAI-Company-Profile.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/wDZVmg7XoC0c-DatamatrixAI-Company-Profile.pdf We are buidling a mission-driven startup to transform organisations into AI first and AI ready organisation. NA Flyer which was circulating in Startup Ecosystem by IDFC Bank checked
Dec 25, 2025 @ 4:48 PM Vijendra goyal vgoyal.iitbhu@gmail.com http://www.linkedin.com/in/vgoyal29 http://swiftontime.com 919538356544 Product and business strategy We are close friends Yes Team building, problem solving SwiftOnTime swiftontime.com Private mass transit systems Metro cities traffic problems Providing mass transit system hub to hub and point to point On time, stress free , fixed seat, premium , comfortable office rides and back MVP Users, Pilots, Signups Daily office going people 18000 crore 1800 crore 150 crore revenue model is based on per-seat, pre-booked shared shuttle rides priced at ₹100 per trip, complemented by monthly subscription plans and corporate commute contracts for predictable, recurring revenue. Quick Ride, Hopr. By reaching out to offices and employees directly Starting from the fixed route with high density of office commuters To provide a safe swift sustainable mass transit system to daily commuter on fixed routes which motivate people to not to use their cars for daily fixed and planned commute. Done None Yes To get mentorship and funding Support to make it successful startup No as of now Mission driveb NA WhatsApp group iitacb checked
Dec 25, 2025 @ 12:38 PM Tarun Singh tarun.singh.cer22@iitbhu.ac.in https://www.linkedin.com/in/tarun-singh-30ab31188/ https://tripflow.whispr.in +917906142543 Tarun Singh (Co-founder): Product and technical lead responsible for system architecture, AI workflows, backend development, and overall product strategy. Leads execution, travel API integrations, and MVP development. Engineering background at IIT (BHU) with experience leading technical teams and building real-world products. Rohit Kumar (Co-founder): Full-stack and operations lead responsible for frontend development, feature implementation, testing, and deployment. Actively supports backend integration and product iteration. Engineering background at IIT (BHU) with experience delivering campus-scale tech projects. Collaboration: We work closely and support each other across roles—stepping in whenever one of us gets stuck—to ensure fast execution, shared ownership, and continuous progress. We met around 12 months ago while working together on the technical team of IIT (BHU)’s cultural fest, where we collaborated closely on building and managing tech systems under real deadlines. I served as the Tech Head, and Rohit was part of the technical team from a junior batch. Since then, we’ve continued working together on TripFlow, collaborating daily on product development, problem-solving, and execution. Yes Our biggest strength as a team is execution with shared ownership. We collaborate closely, step in to help each other whenever one of us gets stuck, and move fast from ideas to working solutions. With complementary skills across backend, AI workflows, and full-stack development, we’re able to iterate quickly, learn from real user feedback, and consistently push the product forward despite limited resources. TripFlow https://tripflow.whispr.in TripFlow is an AI-powered travel agent that plans and books complete trips end-to-end in one click. Trip planning is fragmented and time-consuming, forcing users to switch between multiple apps for flights, hotels, itineraries, and bookings. This leads to wasted time, confusion, and poor decisions. TripFlow solves this by automating trip planning and execution into a single, intelligent, end-to-end experience. TripFlow provides an agentic AI travel planner that automates the entire trip journey. Users simply describe their trip in natural language, and TripFlow instantly finds the best transport options, recommends stays, creates a complete day-wise itinerary, and enables end-to-end booking in a single flow. By combining real-time data, personalization, and execution, TripFlow eliminates the need to juggle multiple apps and makes trip planning fast, simple, and seamless. TripFlow is unique because it combines AI-driven trip planning with real-time execution in a single workflow. Unlike tools that only suggest itineraries or OTAs that only handle bookings, TripFlow acts as an agentic AI travel agent that plans, optimizes, and executes trips end-to-end. Its defensibility comes from deep API integrations, workflow orchestration, and continuously improving personalization from user interactions. While easy to copy in theory, replicating the system’s reliability, learning, and execution speed creates a strong practical barrier to entry. MVP Signups Our target customers are frequent travelers aged 18–35, starting with students and young professionals who are tech-savvy, budget-conscious, and prefer digital tools. They travel for leisure, short breaks, or group trips and value speed, convenience, and personalization. As TripFlow scales, we plan to expand to a broader global audience of travelers who want a simpler, end-to-end way to plan and book trips. ~$10.9 trillion — Global travel and tourism market. ~$700 billion — Global online travel planning and booking market (digital + OTA-driven). ~$20–115 million (India, near-term) — Based on capturing 0.1–0.5% of India’s ~$23B online travel market, starting with students and young professionals. TripFlow follows a hybrid revenue model. Users pay a planning fee to generate personalized trip itineraries, and we earn commission-based revenue from bookings of flights, hotels, and experiences through integrated travel partners. Over time, we plan to introduce premium subscriptions and B2B partnerships for additional revenue streams. Our main competitors fall into two categories: Traditional OTAs: MakeMyTrip, Booking.com, Expedia — strong in bookings but require users to manually plan and compare across multiple steps. AI Trip Planners: tools like Layla, Roam Around, and GuideGeek — good at itinerary suggestions but do not handle real-time pricing or end-to-end bookings. TripFlow sits at the intersection, combining AI-driven planning with real-time execution and booking in a single flow, which most competitors do not offer. We acquire customers through a community-led and product-first approach. Initially, we focus on college and student networks, using campus ambassadors, early access programs, and referrals to drive adoption. We also leverage social media content that highlights travel planning pain points and encourages organic sharing. As we scale, we plan to expand through partnerships with travel communities, content creators, and targeted digital campaigns to reach young professionals and frequent travelers. Our go-to-market strategy starts with college and student communities, leveraging early access, referrals, and campus ambassadors to drive organic adoption. We validate the product through beta testing and feedback loops, then expand to young professionals via travel communities and social media. As traction grows, we scale globally through localized offerings and partnerships with travel platforms and creators. Our long-term vision is to make trip planning completely autonomous. We aim to build TripFlow into a global AI travel agent that understands user preferences deeply and can plan, optimize, and book trips end-to-end with minimal input. Over time, TripFlow will become a personalized travel companion that learns from every journey, helping users travel smarter, save time, and explore the world with zero planning friction. In Process NA Yes We’re applying to IITACB Incubator because it offers the exact ecosystem we need to scale TripFlow from a working MVP to an industry-ready product. IITACB’s access to IIT alumni, experienced mentors, industry tie-ups, and investor networks is critical for refining our product, strengthening our go-to-market strategy, and preparing for commercialization. We particularly value the incubator’s focus on deep-tech, applied innovation, and structured mentorship, which aligns with our agentic AI-driven travel platform. Being part of IITACB will help us validate TripFlow with real users, build strategic partnerships, and grow within a strong alumni-backed innovation ecosystem. During the programme, we want to refine TripFlow into a scalable, user-ready product. Our goals include improving the user experience through mentor feedback, validating our business model with real users, and strengthening our go-to-market strategy. We also aim to build strategic industry partnerships, prepare for fundraising with a strong pitch, and gain insights from experienced mentors to avoid early-stage mistakes. By the end of the programme, we want to exit with a stable product, early traction, and a clear roadmap for growth. We are open to online mentoring sessions based on mentor availability and programme requirements. 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/szIHsznY68te-TripFlow-Pitch-deck_Final_choladeck.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/szIHsznY68te-TripFlow-Pitch-deck_Final_choladeck.pdf Yes, TripFlow is a mission-driven startup focused on simplifying how people plan and experience travel. Our mission is to remove the friction, time waste, and stress involved in trip planning by using AI to automate decision-making and execution. By making travel planning faster, more accessible, and personalized, we aim to empower students and young professionals—especially those with limited time or budgets—to explore more opportunities, cultures, and experiences. Over time, we want TripFlow to democratize access to smart travel planning globally, making travel easier and more inclusive. NA E-Cell, IIT BHU checked
Dec 25, 2025 @ 12:15 PM Rajat Aggarwal rajat.a@hrgenie.tech https://www.linkedin.com/in/rajat-aggarwaliitdelhi/ https://www.hrgenie.tech +91-8800234668 Rajat - Founder & CEO - handle sales, product vision, product design and features, partnerships, data experiments and prompt design I have been full-time on hrGENie since mid-2024 and we are already live with paying customers Yes A compact, IIT‑caliber founding core that deeply understands the recruiter’s problem, can build complex AI infra, and has already proven it can turn that into customer value and revenue hrGENie https://www.hrgenie.tech End-to-end AI hiring engine Improving interview to offer % hrGENie is the AI screening layer that sits between job boards and ATS, turning 1,000 messy resumes into ready-to-interview candidates with 70% offer rates. ​ How: JD → skill rubric → resume scoring (hours/roles/recency) + 10-min voice AI → ranked pipeline with evidence (comm, skills, gaps). ​ Result: 60% faster hiring, recruiters spend 20% bandwidth vs 80%, ₹1.7L revenue from 5 SMBs already Unique: Dual validation (resume depth + voice AI) against a single skill rubric—no one else ties resume scoring to live interview validation consistently. ​ Defensible: Data moat—every hire trains your model (120K candidates → role-specific benchmarks), creating switching costs (6-18mo historical data lost) Revenue Users, Revenue, Testimonials SMBs, Recruitment agencies, enterprises & GCCs $76.8B $20-25B ≈ $500M-1.5B Usage Based Pricing - per resume and per AI interview minute Naukri & LinkedIn Currently through my IIT Delhi Network but we have started marketing to acquire inbound leads now. GTM: Founder-led sales to high-volume SMBs (₹1K/resume screened), expand to agencies (₹3K), enterprises (₹5K)—60 customers = ₹1Cr ARR. ​ Phase 1 (Now-Jun26): 20 SMBs + 3 agencies via job portals/colleges + AnyDay Job (50K job seekers). ​ Phase 2 (Jul-Dec26): API integrations (5 portals), IIT pilots, enterprise/GCCs → 1Mn ARR. Vision: Become India's AI hiring evaluation layer - 90% interview-to-offer, 10-day time-to-hire for 1.2M recruiters, 100Cr ARR in 5 years. Endgame : Every quality candidate gets fair shot; recruiters focus on relationships, not resume piles. YES NA Yes IITACB (AJVC) gives IIT Delhi alumni like me structured validation, network access, and pre-seed runway to scale from ₹1.7L MRR to ₹1Cr ARR. ​ Perfect timing: Product live, paying customers (Codeyoung/Fitelo), need mentorship for enterprise pilots + CTO hire. ​ Home advantage: IIT network for pilots (already started), recruiter connections in Delhi NCR. Networking + Funding + Mentorship + Key hires yes, both works for me. Both Yes—mission-driven: End resume-pile chaos so skilled candidates (no IIT tag needed) get fair shots, not ghosted. ​ Impact proof: 87 hires via hrGENie (vs manual rejection piles), 100% candidate feedback (vs 1%). ​ Long-term: 90% interview-to-offer, 10-day hiring for 1.2M recruiters = fairer jobs market. NA RAM Ventures checked
Dec 24, 2025 @ 6:31 PM Dr. JAGADEESH DALER jagadeeshdaler@vnir.life https://www.linkedin.com/in/dr-jagadeesh-daler-94a0951a/ http://www.vnir.life 7875109447 Founder & Director We met during academia-industry discussions at NCL pune and started on building VNIR Biotechnologies Yes Science, Technology, Expertise, Industry Skill sets VNIR BIOTECHNOLOGIES PVT LTD www.vnir.life Translational science to marketable products and services Building molecular probes for various life-science industry verticals Building molecular probes for various life-science industry verticals - Biopharma, Diagnostics, FMCG, Alternative foods, Seed industry and Research institutes IP led, Sensitive, Customizable, Accessible, Affordable, Stable signal. Revenue Biopharma, MedTech, FMCG, FoodTech, AgriTech, Research labs, Testing Labs NA NA NA Product market - revenue- growth- global No one in India email, cold calls, exhibitions, trade shows, social media Products- End-users-Customers-B2b market Growing the company to global scale Generating employment opportunities Contribution to Bioeconomy Private Limited 2.3 cr Yes scaling up manufacturing, connect to potential investors, build global network improve manufacturing practices, raise funding - series A, expanding marketing team In-person and hybrid 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/qcUnEyK1byhS-VNIR-Pitch_Dec-2025-DST-NIDHI_DERBI.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/qcUnEyK1byhS-VNIR-Pitch_Dec-2025-DST-NIDHI_DERBI.pdf https://www.youtube.com/watch?v=vkVoAbhjavc Deep-tech, Science based new age venture to smart manufacturing of high value products to deserving customer base. Health tech/Biotech checked
Dec 24, 2025 @ 5:54 PM Ramalingeswara Rao K V kvramalingeswararao@gmail.com https://www.linkedin.com/in/RamalingeswaraRaoKV/ http://www.LanKeys.blogspot.com +919449501439 Founder, NIRAM Single Founder. Yes 🟠 Google Scholar: https://scholar.google.com/citations?user=z17ckXIAAAAJ 🟠 www.RaamRas.blogspot.com 🟠 www.TriChakri.blogspot.com NIRAM www.LanKeys.blogspot.com Information Technology Improves Cyber Security; Target of Technology; Innovation in AI, NLP, TTS, etc.; Accessibility for PwD; .... ✳️ Information Technology (IT): ⭐️ NIRAM LanKeys (www.LanKeys.blogspot.com) is a patented Multi-purpose Natural Language Processing Tool. I have participated in the Launchpad programme at NSRCEL in IIMB. ⭐️ Network (Pitch & Honor): https://LanKeys.blogspot.com/p/network.html ⭐️ Videos: Demo: https://youtu.be/7TAhbNFFd48 Product Life Cycle: https://youtu.be/renM_eB1BVU ⭐️ Number of Patents: 2 (Published-1 and Granted-1). Patent #1 [Published]: METHOD AND SYSTEM FOR TRANSLITERATING TEXT FROM ONE LANGUAGE TO MULTIPLE LANGUAGE SCRIPTS. Intellectual Property BHARAT/India 🇮🇳 Patent Application No. 931/CHE/2012. World Intellectual Property Organization 🌐 Patent Application No. PCT/IN2013/000155. Patent #2 [Granted]: SYSTEM AND METHOD FOR AUTOMATIC NAMING CONVENTION OF AUDIO FILES BASED ON USER PREFERENCE. Intellectual Property BHARAT/India 🇮🇳 Patent No. 473442. Patent Application No. 2686/CHE/2014. Number of Patents: 2 (Published-1 and Granted-1). MVP Testimonials B2G, B2B, B2C Globally -NA- -NA- -NA- Globally -NA- Patent license; Products & Services. B2G, B2B, B2C 🟠 Making our country BHARAT 🇮🇳 as perfectly Product and Services based... ⚪️ Making more Research Scholars in our Country BHARAT 🇮🇳. 🟢 Win the heart of the whole World🌏 with Freedom😊, Peace🕊, and Love🧡🤍💚. Registration is in process/progress. No No Network and Grant. Network In-person 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/erLvipukIfOv-Ram.pdf, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/RDEKhACtel9i-Ram_SPM_Summit2024.jpg, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/MNLJlZ9SwohA-Ram_IIT_Tirupati_IITTNiF.pdf, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/Br4eMv3p8jjI-Ram_ArtParkIISc_July2025.jpg, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/c8mhCvQL4Di1-IIMB_PGPEM_SustainabilityInnovationChallenge.jpg, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/eVZGweGL2CaQ-IITmumbai_Eureka2024_Certificate-of-NIRAM-LanKeys-www.LanKeys.blogspot.com_.jpg, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/SpH7QPizVDAL-P2_PatentNumber473442.jpg, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/1Wl78d6eZU5Y-P1_WIPO.jpg, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/uvazaRsjCzFQ-NIRAM-LanKeys-Pitching_17Oct2025.jpg, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/cJghVNbyl7Zq-NIRAM_LanKeys_PitchDeckBM_17Oct2025.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/erLvipukIfOv-Ram.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/RDEKhACtel9i-Ram_SPM_Summit2024.jpg, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/MNLJlZ9SwohA-Ram_IIT_Tirupati_IITTNiF.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/Br4eMv3p8jjI-Ram_ArtParkIISc_July2025.jpg, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/c8mhCvQL4Di1-IIMB_PGPEM_SustainabilityInnovationChallenge.jpg, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/eVZGweGL2CaQ-IITmumbai_Eureka2024_Certificate-of-NIRAM-LanKeys-www.LanKeys.blogspot.com_.jpg, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/SpH7QPizVDAL-P2_PatentNumber473442.jpg, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/1Wl78d6eZU5Y-P1_WIPO.jpg, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/uvazaRsjCzFQ-NIRAM-LanKeys-Pitching_17Oct2025.jpg, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/cJghVNbyl7Zq-NIRAM_LanKeys_PitchDeckBM_17Oct2025.pdf https://youtu.be/7TAhbNFFd48 Both. ⭐️ Network (Pitch & Honor): https://LanKeys.blogspot.com/p/network.html ⭐️ Videos: Product Life Cycle: https://youtu.be/renM_eB1BVU IIMB NSRCEL, Innovation Center in IIITB, C-CAMP, MSMF TBI in Narayana Hrudayaalaya. Ramesh Rao N, IITACB. www.RamalingeswaraRaoKV.blogspot.com checked
Dec 24, 2025 @ 5:20 PM Piyush Pratap Singh zoetapps123@gmail.com https://www.linkedin.com/in/piyushpps/ http://www.mymirro.in 918919738792 Piyush - Co Founder & COO, IIT BHU(Varanasi) Co’2020. Mayank - CoFounder & CEO, IIT BHU(Varanasi), CO’2020 We have been batchmates since 2016 back at college & have know each other for almost 10 years now. We have been working on this startup since a year Yes I bring the AI enablement experience, user empathy, distribution analysis, business opps realisation, product marketing experience from previous stints at multiple D2C & B2B Orgs having worked as Analyst & Product Mgmt & Marketing roles. Mayank brings in his data analysis, software architecture, tech visualisation & AI & Prompt Engg experience through his professional & personal side businesses experience. MyMirro www.mymirro.in We are your Personal AI Stylist in your pockets We are trying to solve for the centralised problem solving product for any query related to fashion by means of forming deep personal companionship through our proprietary AI Models. We are a one stop solution when a user thinks about their personal fashion. From answering any fashion related personal query to curating their wardrobe outfits for daily or ocassion based experiences, to helping them shop smarter by helping them with personalised on body decision making through virtual Tryons & avatars, to solving for instant gratification via Style Check feature that scores the outfit before stepping out and suggests quick fixes, to some community features like outfit battles which ranks participants based on who dresses the best in their group. We are MyMirro, your personal AI Stylist. One place for all things fashion. We have made considerable advancement in formulating the right UX for positioning Fashion as a daily need for people of India. We have pivoted twice across B2C & B2B solutions, and have zeroed down on the best way to execute fashion for users. Market research comes with talking to right users and right mix of marketing Users Users We are targeting the Genz population of India. These folks relate very deeply with what they wear to who they identify and want to be perceived as in society. Quick adopters of Consumer AI, global citizens & easy spenders on wants & needs make then our ideal customer profile. We have calculations that we can reveal when discussed. “” “” NA Alta Daily, Essembl, Acloset, Indyx Paid + Organic marketing on socials, Offline promotions, Amabassador programs We want to become a habit for the Genz population in India, introduce revenue unlocks on app, make styling a reality & not a concept meant only for view & then go global. Looks matter. You hair, your eyewear, your makeup, your outfit, your shoes. What you wear & how you wear along with where & why behind a certain ocassion would become important in the coming years. Everyone will have their own identity & distinct style. We want to be the single point solution for anything related to Look Orchestration - what to wear, how to wear, what to shop, where to shop, how to improve etc will be our top use cases. Essentially a world where every single person is more aware about themselves and what goes good on them so that they are their most confident self all the time including during times when it matters most. We have incorporated as Pvt Ltd We are bootstrapped and are beginning our first round in 2nd week of January 2026 Yes To get access to global alumni expertise, networks & opportunity to meet like minded folks. We would love to secure our first round of cheques through angels who believe in the idea. We would love to network and or receive warm intros to folks outside direct network, so that we keep growing our access to expertise, funds & mentors. Yes 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/oRynr5hKEPew-My-Mirro-Pitch-Deck_compressed.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/oRynr5hKEPew-My-Mirro-Pitch-Deck_compressed.pdf NA checked
Nov 28, 2025 @ 2:13 AM Dibyalochan Sahoo dibya0512@gmail.com https://www.linkedin.com/in/dibyalochan-sahoo-0616a2177/ http://NA +91 7683934947 Founder: Dibyalochan Sahoo — IIT Madras, Batch of 2023 Potential Co-Founder: Kalyani Buradkar — 3rd Year B.Tech, IIT Indore (pursuing) We are a 4-member team with 30% of the MVP already completed. We began working together two months ago after I connected with everyone through LinkedIn via a business subscription, as by that time our company was not officially incorporated. No Our biggest strength is the exceptional blend of deep technical expertise and unstoppable execution. We have a highly qualified team of IIT graduates and experienced computer scientists capable of building a complex engineering design and simulation platform and service. The founder brings strong product development experience, business insight, relentless focus—and the kind of driven, almost unreasonable determination needed to take this product all the way. Together, we combine technical excellence, industry knowledge, and a shared passion to build India’s first homegrown engineering design and simulation suite. Anin Technologies Pvt Ltd NA India’s first homegrown engineering design & simulation suite—AI-enabled, globally benchmarked, best-in-class user-friendly UI, affordable, backed by outstanding service. Most businesses—especially MSMEs—cannot afford the high-cost, outsourced engineering design and simulation software currently dominating the market. There is no Indian homegrown engineering design and simulation company, creating a major gap in accessibility, innovation, and affordability. Both MSMEs and large industries across construction and manufacturing struggle due to dependence on outsourced product and design teams—resulting in delays, high costs, security concerns, and lack of control over the development process. Addressing the gap created by the absence of a homegrown Indian company in engineering design and simulation software. Fixing the challenges MSMEs & Large industries in construction and manufacturing due to dependence on outsourced product and design teams. An all-in-one digital engineering suite that is globally benchmarked and built for a global market—featuring a modern, interactive UI comparable to mainstream applications, addressing the usability gaps currently seen in existing global solutions Homegrown & affordable – 5–10× cheaper while maintaining global quality. AI-driven productivity – Faster modelling and simulation; global players are slow to adopt. Modern interactive UI – Best-in-class, mainstream-grade user experience. Service advantage – Strong India-based support and parallel design-service team insights. MVP Pilots MSMEs , Large industries, construction,manufacturing, aerospace,defense, semiconductor, training center, educational institution $200Bn $10Bn Subscription+ service Autodesk, DS, Synopsys, Cadence design system Free training & subscriptions for students & institutes - cost-effective way to learn and build skills from the ground up. Platform for complex design projects - attracts professionals and learners. Client-ready market - offers ready solutions for quick adoption. Existing service team - upsells to current customers. Social media & content - showcases projects and success stories. Seminars & workshops - enables direct engagement and lead generation. next 4 month-finish building MVP, 2026-27-start providing design and consulting service, 2028-first product launch Evolve the company into two strong verticals—a world-class engineering software product and a global design services division. As the product matures, we aim to scale development, continuously innovate, and strategically acquire global companies to build a multi-billion-dollar digital engineering enterprise. Incorporated in Nov-2025 NA Yes funding & mentorship funding & mentorship preference-Online,hybrid 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/iNaGdTvgWBwO-Anin-Technologies.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/iNaGdTvgWBwO-Anin-Technologies.pdf Yes, we are building a mission-driven startup. Our goal is to capture the multi-billion-dollar global digital engineering market, serving construction, manufacturing, and heavy industries through innovative software products and services. We aim to elevate India’s engineering and design capabilities to a global level, creating homegrown solutions that compete internationally and drive industry-wide innovation. NA checked
Nov 1, 2025 @ 12:33 AM Alok Kumar Barnwal alok@autocash.ai https://www.linkedin.com/in/alok1000/ http://www.autocash.ai +1-9144605200 Alok: CEO and Founder, Hemant: Head of Technology, Co-founder We met each through IIT Network and had common friends. First time working together at Autocash. Yes Alok has a deep domain expertise in Finance, Treasury and Cash management. Hemant has deep expertise in Technology particularly in the field of AI. he has worked for large as well as startup with success exits. Autocash AI https://autocash.ai Revolutionalizing cash and working capital management for businesses Real-time visibility and forecasting of cashflow and working capital Autocash unifies financial data across banks, ERPs, and business systems—covering cash, payables, receivables, customers, and vendors—to deliver powerful insights into cash flow and working capital. It helps CFOs and finance teams automate key processes and make smarter, faster decisions by leveraging advanced AI, data science, and agentic automation frameworks for intelligent, real-time financial management. Product-Market Fit Testimonials Our primary customers are CFO organizations within mid to large enterprises, particularly in North America. However, Autocash is designed to be industry-, geography-, and size-agnostic—making it adaptable for finance teams across a wide range of sectors and regions seeking to optimize cash flow and working capital through intelligent automation. 10B 2B 500M Monthly subscription for the platform, transaction based pricing for automation and outcome based revenue Nilus, AGICAP, GTreasury, Kyriba, HighRadius Direct outreach, referrals, and strategic partnerships. Focuses on CFOs and finance leaders via targeted marketing, industry events, and collaborations with ERP and banking partners. To become the world’s leading intelligent finance platform and the trusted Copilot for CFOs—transforming cash and working capital management through AI-driven insights and automation, while empowering finance teams to operate with greater speed, intelligence, and efficiency at a significantly lower cost. Delaware C Corp NA Yes Leverage the strong IIT alumni network, access experienced mentors, and connect with investors and industry partners. Refine our product-market fit, strengthen GTM strategy, and build partnerships within the IIT and enterprise ecosystem. Hybrid 1, https://iitacb.org/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/UdvCNqhEHE02-AutoCash-Pitch-for-IITACB.pdf, /home/u799217236/domains/iitacb.org/public_html/wp-content/uploads/forminator/1902_05f18c19543f314835710ffec30a12dd/uploads/UdvCNqhEHE02-AutoCash-Pitch-for-IITACB.pdf Yes — Autocash is a mission-driven startup focused on transforming how businesses manage cash flow and working capital. Our goal is to empower finance teams, especially in mid-sized enterprises, with AI-driven tools that reduce manual effort, improve financial visibility, and enable smarter, faster decisions. By making advanced financial automation accessible at a lower cost, we’re helping organizations operate more efficiently, strengthen liquidity, and drive sustainable economic impact. Both Alok and Hemant as IIT alumni (IIT Kharagpur and IIT Guwahati respectively). checked