Milind Kopikar

On February 18, during India's AI Impact Summit, a company called Sarvam shipped a 105-billion-parameter model trained from scratch in India on government-subsidized GPUs, designed for 22 Indian languages. It outperforms DeepSeek-R1 on certain benchmarks at one-sixth the size. The same summit produced $200 billion in investment pledges from Amazon, Microsoft, Google, and Reliance. The headlines were about the money. The real story was Sarvam. This post examines in detail why it took this long, what changed, and whether Sarvam is the first crack in an old equilibrium or a lonely exception. "Indians Rule Big Tech. Why Can’t India Build?": Link in comments.

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From our PearX S25 cohort, meet Pravāh, the AI-native operating system for the electric grid When Mohak Mangal, Dhruv Suri, and Aman Gupta looked at the strain on the U.S. electric grid, they saw a system pushed to its limits. Exploding demand and unpredictable supply have made blackouts increasingly common. This costs the economy more than $150B a year, a number that could 10x in the next five years. Mohak Mangal and team founded Pravāh to help fix it. Their platform helps utilities and grid operators make real-time decisions on load, generation, and congestion, reducing blackout risks, optimizing power procurement, and bringing much-needed stability to the backbone of modern life. We’re proud to support the Pravāh team as they take on one of the toughest and most important infrastructure challenges of our time.

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🔧 Unibose Technology Private Limited raises ₹5.5 Cr to scale robotics for confined space safety We at o2 Angels Network are proud to have led the ₹5.5 crore funding round, co-led with IN44 Capital in Unibose, a cutting-edge industrial #robotics company focused on eliminating human risk in hazardous confined spaces. The round also saw participation from Startup Singam, and a strong network of strategic angel investors who share our conviction in India’s #deeptech manufacturing potential. Unibose’s ATEX Zone-0 certified #No_Man_Entry_Robots (NMER) are designed for use in toxic, flammable, and high-risk environments, replacing dangerous manual work with scalable, #AI-powered robotic systems. ⚙️ Product portfolio includes: ·       Oil & gas storage tank cleaning robots ·       Sewer and drain maintenance bots ·       Rail wagon and process vessel cleaning systems ·       Remote inspection units with intrinsically safe vision technology At the heart of this vision is the passionate founding team - Manikandan Dakshinamoorthy, Sakthivel Panneerselvam, #Samayaraj_D, Venkatesh Sundaramurthy whose clarity of purpose and relentless execution have been instrumental in taking Unibose from lab to large-scale field deployments. They are not just building a product — they are creating a mission-critical platform that saves lives and transforms the way industries operate in hazardous environments. This investment will support in: ✅ Expanding into new geographies including the #Middle_East and #Africa ✅ Scaling up manufacturing and field deployments ✅ Accelerating R&D to serve critical industrial use cases 🛢️ Their solutions are well-positioned for adoption by leading industry players including Indian Oil Corp Limited, Hindustan Petroleum Corporation Limited, Reliance Industries Limited (Oil Pumps), Oil and Natural Gas Corporation Limited (ONGC), Oil India Limited / ऑयल इंडिया लिमिटेड, aramco, ADNOC Distribution, ENOC/EPPCO International, Emarat - Emirates Petroleum Company P.J.S.C, and more. 💡 At o2 Angels Network, we back founders solving high-impact, high-risk industrial challenges with technology that protects lives and transforms operations. Our portfolio includes Fabheads Automation, Green Tiger Mobility Pvt. Ltd., Eeki, CultYvate, Skye Air Mobility, NAVARS EDUTECH, Janitri, Velectron Labs Private Limited, Abhiyantrik Solutions, Nexstem, REGRIP "RE-ENGINEERED TYRES", SpaceFields, Unibose Technology Private Limited, BQP, Vgenomics and many others pushing the boundaries of innovation. Lastly, we're excited to support Unibose on its journey to build IP-led, Made-in-India robotics that deliver real-world value at scale. #IndustrialRobotics #Deeptech #MakeInIndia #StartupFunding #AI #ImpactInnovation #CleanTech #HardTech Office of the Principal Scientific Adviser to the Government of India, Startup India 🔗 Read more: https://lnkd.in/deD_T8vT

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As part of the IndiaAI Mission, Avataar is building UAI (Unified AI Interface) - a foundational DPI layer with thin, durable rails for trust and interoperability, connecting models, data and compute into a cohesive, discoverable ecosystem. We are privileged to collaborate with Prof. Ramesh Raskar (MIT) and Project NANDA: Architecting the Internet of AI Agents in shaping a broader “Internet of AI Agents” vision - exploring how a discovery layer for India’s evolving digital public infrastructure can unlock openness, innovation and responsible scale together. Equally grateful to Aafreen Siddiqui Sherwani (United Nations) for anchoring the dialogue, and to Pradeep Gupta (NVIDIA), Tanvi Lall (EkStep Foundation), Vineet Singh (Digital Green) and Jibu Elias (Mozilla Foundation) - for a thoughtful, forward-looking exchange on what it truly takes to build open AI platforms for India. The real opportunity ahead is not just technical, it is architectural. How we design these rails now will shape how intelligence compounds across citizens, enterprises and governance systems for decades. What principles should guide the design of AI infrastructure at national scale? #IndiaAI #DigitalPublicInfrastructure #ViksitBharat

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Tech experts Katey Creel and Akito Tanaka deliver the hottest trends and news from the sector. In this episode, Katey speaks with India correspondent Sayan Chakraborty about how the South Asian country’s deep tech startups are vying for investor attention in a landscape long dominated by quick-revenue ventures like e-commerce and ride-hailing. https://lnkd.in/dFuXkw8E

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A founder who has spent 32 Years building IP-Owned Tech in India's Defense Sector. Ashok Atluri, Founder of Zen Technologies Limited shares a growth story bootstrapped from Hyderabad: -Revenue: ₹60 Cr (FY21) → ₹930 Cr(FY24) -Market cap: 40 Cr (2012-13) → 13000 Cr today -Growth: 400X in 12 years Takeaways from our conversation: 1. India historically imported 65–70% of its defense equipment. Today, defense exports have grown more than 30× over the past decade, with the private sector contributing around 60% of exports. Domestic defense production has increased to ₹1.27 lakh crore, a 174% rise since FY 2014–15. 2. For over two decades, Zen built advanced simulators but struggled to sell them in India because single-vendor bids weren’t accepted. The IDDM policy in 2015 gave preference to IP-owning Indian companies and allocated 75% of the capital acquisition budget to local sourcing. And decades of R&D became a real market worth ₹200 billion. 3. Defense tech startups in India have raised $184 million in VC funding since 2020. Zen’s journey shows that IP-owned Tech built with self-funded R&D can build the most defensible advantage, similar to how Apple captures value through IP rather than manufacturing. 4. Zen’s anti-drone systems were proven in field operations, leading to export inquiries from over 20 countries. This mirrors the broader trend of India’s defense exports growing from ₹1,940 crore (FY14) to ₹21,083 crore (FY24). Field-tested solutions build trust far faster than lab demos or pilot projects. 5. Government fundings are rewarding innovation over manufacturing. Programs like iDEX provide up to ₹10 crore for proven concepts, while DRDO offers ₹50 crore per system under the Technology Development Fund. This shift allows companies to reinvest profits into next-generation R&D. 6. Ashok believes that not all technologies should be patented. Highly secretive or complex innovations can be reverse-engineered if patented. Instead, patent what is obvious to outsiders to protect your competitive edge. 7. Build with a focused approach on Pareto technologies with maximum impact. Instead of chasing every opportunity, Zen concentrated on the 20% of technologies delivering 80% of results, anti-drone systems and simulators. Prioritizing high-leverage areas compounds impact effectively. 8. Time market entry around overlooked gaps: In 2018, drones were a hot topic, but there was little attention on anti-drone systems. Zen entered this gap and was ready when the need became urgent, from regional conflicts to domestic security. Opportunities often lie where others are silent. 9. Create policies around your innovation: Self-funded R&D firms face unique risks that conventional procurement rules often overlook. Zen advocated for new categories rather than adapting breakthrough technologies to unsuitable frameworks, ensuring their innovations could be evaluated on merit. Full Episode https://lnkd.in/gnAFEj3f

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Can we please call the recent changes to the H1B visa fee for what they are? They are not a disguised boon, not a clarion call, not anything of the sort. They are an unfortunate and misguided decision—with no silver linings. Look at the companies with the highest H1B approvals over the last three years: Amazon, Tata Consultancy Services, and Infosys. Two of the three are services-focused. For decades, many middle-class Indians have walked this path to a better life (that seemed out of reach unless they went to the few top schools in the country), especially when the odds of making it through India’s top schools are ~0.25%. With such high entry barriers, these aspirants won’t suddenly pivot to becoming founders (nor is that everyone’s dream) or slot into roles at cutting-edge innovation firms (how many such roles exist, and how many applicants can actually be absorbed?). The economic disincentives, lack of demand, and sheer counterintuition make that belief hard to justify. The more likely outcome: a worsening underemployment challenge—one we rarely report on, let alone measure comprehensively. For those who do want to build for India’s 1.4Bn+ population, the increase in H1B fee is hardly the catalyst they’ve been waiting for. Real catalysts would be greater ease of doing business, less corruption, and a reduction in fanaticism. Secondly, the argument around this leading to a boom in entrepreneurship in India exposes another deep-lying bias. Having been a founder and having worked alongside founders for nearly a decade, one of my long-standing peeves is our tendency to idolize entrepreneurship. Let us not place entrepreneurship on a pedestal where employed folks need to "graduate to". It can (and has) led many founders to sacrifice too much and lose too much. Entrepreneurship is brutally hard, demanding, and sacrificial, with extremely low odds of success. Let’s not pretend that those who seek a stable, comfortable life “should” or “want to” become founders. I certainly stand with the fact that this is not merely an economic policy change but has humanitarian perspectives too. With great economic might comes responsibility. I hope that we see ourselves clearly for what we truly are: a pale blue dot, without imaginary borders. This is us, per the NASA Voyager-

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I had a fascinating conversation with Abhishek Das about how to win in AI (+ why horizontal > vertical) Abhishek is a pioneer in agentic AI (2016 PhD thesis on agents that can see, talk, and act + Meta FAIR Lab researcher) & co-founder of Yutori (Radical Ventures, Felicis, Elad Gil, Sarah Guo, Scott Belsky, Guillermo Rauch, etc) My biggest learnings: 1. Errors compound viciously in multi-step processes In complex workflows, each decision is a point for errors to multiply. 90% accuracy sounds great until you realize that over a 10-step workflow, you're failing more than succeeding. Over 50 steps, you're basically guaranteed to fail. On top, the long tail of edge cases in every process makes this worse. You can't train on every possible scenario. Instead, your agents need to detect mistakes quickly and backtrack. The effort to get there is enormous - getting from 50% → 80% → 99+% reliability scales almost linearly in effort. There's no shortcut. 2. Depth on one thing creates memorization, not generalization If you train too narrowly - on one customer, one workflow, one use case - your model learns the quirks, not patterns. You get brittle intelligence that can't transfer. Yutori initially built a food ordering agent for DoorDash. It worked beautifully. But when they tested it on other food sites - same category, similar UIs - it collapsed. The model had memorized DoorDash's quirks instead of learning how food ordering works. 3. To win in horizontal AI, pick a capability, then go wide Building in horizontal AI is as competitive as it gets. As a small startup, focus on a single, powerful capability, do it incredibly well, and apply it broadly. After their DoorDash experiment failed to generalize, Yutori scoped down to one capability: Agents that monitor the web for anything you care about - specific but broadly applicable. Training on all sites on the web across diverse UIs within that single capability made the model robust to become the best at this capability. 4. Research and product have to talk Many AI companies have big research teams. When research and product operate in isolation, you get either science projects that never ship or products built on shaky technical foundations. Ideas should flow both directions. Sometimes research unlocks a capability that product can ship. Sometimes product shapes the research roadmap. The key is visibility across the company. 5. In fast-moving spaces, plan in 3-month horizons Anything beyond that has too much variance - both in what you can build and what the world will look like. Have rough sketches for 6 to 12 months, but plan in quarters. You can't predict further out, pretending otherwise wastes everyone's time. 6. Everyone should read user feedback Customer feedback has to reach every corner of the company At Yutori, all onboarding emails come from the founder / replies land in his inbox. On top, everyone on the team, no matter how technical, rotates through reading user feedback

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🚀 Funding Update in the Indian Startup Ecosystem Mumbai-based Luma fertility, a tech-enabled fertility care startup, has successfully raised $4 million in seed funding, led by Peak XV Partners (via its Surge program), along with participation from notable investors like Ameera Shah (Metropolis Healthcare) and Vijay Taparia (B2V Ventures). Founded by Neha K Motwani, Luma Fertility is building a patient-first platform to offer end-to-end reproductive care—covering IVF, fertility assessments, egg freezing, at-home diagnostics, and more. The startup is leveraging technology and empathy to modernize fertility services in India. 📍 With a flagship clinic in Bandra West, Mumbai, Luma now aims to expand across multiple cities over the next two years. This is yet another sign of rising investor confidence in healthtech and femtech sectors in India. As a funding consultant, I closely track such movements and assist businesses in navigating their own equity and debt funding journeys. 📩 If you're a startup or growing company looking to raise capital or explore funding options, feel free to connect. #FundingNews #StartupFunding #SeedFunding #LumaFertility #PeakXV #HealthTech #FemTech #IndianStartups #Linkedin #techindia #healthcare

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Meet the Tycoons building India's "Second Act" in DeepTech and AI - 2026 We are witnessing a fascinating transition. Serial founders are taking their IPO winnings and "war-room" experience to solve problems that were previously considered "too hard" for the Indian ecosystem. Here are the 6 heavyweight insights into what the Tycoons are building next: 1) Deepinder Goyal (Zomato) - TEMPLE He is building a brain-health wearable that tracks cerebral blood flow in real-time 🧠 He wants to prove the "Gravity Ageing Hypothesis" - the idea that gravity affects brain blood flow over decades. Deepinder wants to make brain health as trackable as heart rate. Traction: He’s invested $25M of his own wealth and recently raised a $54M round at a $190M valuation. He’s currently hiring "engineer-athletes" with <16% body fat to join the mission. Expect a limited rollout by late 2026 🧬 2) Mukesh Bansal (Myntra/Cult.fit) - NURIX He is building an AI-native services platform building "custom AI agents" for enterprises 🤖 He wants move from "Physical Wellness" to "Digital Intelligence." Nurix builds voice and text agents that handle sales and support with human-like nuance. Already raised $27.5M from Accel and General Catalyst. They are currently operational with an annual revenue run rate of approx ₹5.35 Cr as they scale their Series A ⚙️ 3) Aman Gupta (boAt) - OFFBEAT STUDIOS A new entrepreneurial "Aman 2.0" venture launched following his transition to a non-executive role at boAt 🎬 While the exact "product" is in stealth, Aman’s vision is to back "bold, hungry, and impatient" ideas that disrupt traditional consumer categories. Launched on March 3, 2026. Aman has officially stepped away from daily boAt ops to lead this, marking a shift from "Volume Hardware" to "Offbeat Innovation" 🎧 4) Mukund Jha (Dunzo) - EMERGENT An "agentic vibe-coding" platform that builds full-stack apps via AI 💻 He wants to make software development as easy as chatting. Mukund is moving from the "Logistics of Goods" to the "Logistics of Code." $100M total funding raised (Series B) as of Jan 2026. They’ve hit a $100M Annual Run Rate in record time, proving that "Vibe-coding" is the new industry standard ⚡ 5) Shashank ND (Practo) - CENT He is constructing a preventive health startup that uses AI-assisted whole-body MRI and 120+ biomarkers to screen for 300+ conditions 🛡️ To catch cancer and heart disease before you even feel a symptom. It's the "Antivirus" for the human body. Raised $5M in Seed funding (March 2026). They’ve already completed 1,500+ scans with 26% showing meaningful findings. Physical centers are opening in Bengaluru, Delhi, and Mumbai now 🏥 ➡️ The Insight: The "Second Act" of these tycoons is a masterclass in Risk Evolution. They are using their personal capital to fund scientific bets that could define the 2030s. They aren't just building companies - they are building the technological "Sovereignty" of a new India 💎

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India is not behind on talent. It is behind on risk appetite. Building LLMs or foundational AI infra is not about capability. It is about capital. Not just any capital, but capital that is comfortable with long timelines, unclear outcomes, and massive burn. Most of India’s funding still chases near-term traction. SaaS, fintech, consumer. Sectors where returns are easier to model. But AI infra does not play by those rules. It demands belief before proof. The Middle East launching a sovereign fund to accelerate AI through public private bets is not just money. That is intent. India will not build foundational AI by hoping startups will figure it out alone. It needs conviction at the system level. And a willingness to back uncertainty at scale.

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Cerebras is bringing its AI supercomputers to the UAE’s Stargate project ◾ Deploying megawatt-scale AI infrastructure across the Gulf, India & Pakistan ◾ Partnering with Abu Dhabi’s G42 ... part of the U.S.-UAE Stargate deal ◾ Competing head-on with Nvidia in AI compute ◾ Planning 12–15 data centers within 8 months ◾ IPO refiling “soon,” says CEO Andrew Feldman The UAE is quietly building the world’s largest AI hub outside the U.S.

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I recently had the privilege of moderating a fireside chat at Stanford University Graduate School of Business with Vijay Krishnan, Founder & CTO of Turing, alongside Prateek Sharma (Managing Partner, Ahead VC). Moving beyond the usual buzzwords, Vijay shared some deep-cut insights on the AI landscape, market dynamics, and career strategy. Here are a few that really stayed with me: 🌐 Market Alpha Gets you the Global Maximum Vijay echoed Marc Andreessen’s idea that market is the biggest determinant of startup success. After his first exit, he resisted investor pressure to “move fast” and instead invested heavily in exploration, searching for the right market with the best opportunity. He prioritized a global maximum vs shuffling around local peaks. Strategic patience is super valuable. 🔄 Agility + Open-Mindedness = Reinvention Turing began as a developer marketplace and reached unicorn status. But when OpenAI approached them for GPT-3 work, they leaned into a new frontier, evolving into an AI accelerator powering frontier labs and enterprise deployments. Agility and open-mindedness helped them embrace “right-place-right-time” opportunities, as they dared to reinvent. 🏗️ Vertical AI Still Has Moats The narrative that foundation models will swallow every vertical? Vijay pushed back. Companies with deep system integrations, compound products (vs point solutions), and strong distribution create defensible value. Vertical players that solve real workflows wouldn’t vanish overnight just because models gets better (unless there’s AGI…then all bets are off!). 🔧 Consulting Will Focus on Plumbing + Context In the enterprise AI wave, strategy decks won’t cut it. The winners will be the ones who can do context engineering, who identify high-value use cases and actually implement, customize, and plumb AI into complex legacy systems. 🚀 Career Advice: Stay Close to the Frontier For early-career folks, Vijay’s message was clear: “The closer you are to the frontier of AI, the better.” That’s where the opportunities compound. What do you think? #AI #GenAI #FrontierAI #AIInfrastructure #EnterpriseAI #FutureOfWork #TechCareers #VentureCapital #StartupStrategy #Turing #StanfordGSB

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