Harsh Sahu

Natasha Malpani Launches ₹200 Crore Fund to Power India’s AI Startups Former Kae Capital partner Natasha Malpani has launched Boundless Ventures, an early-stage venture fund with a corpus of ₹200 crore, dedicated to supporting homegrown AI-native startups across India. The fund will focus on pre-seed and seed-stage investments in companies innovating across consumer AI, infrastructure, agent tooling, healthcare, logistics, deep tech, and make-in-India hardware. Boundless has already written its first cheques to startups including Superhealth, Armatrix, PierSight, Knot, and two stealth ventures in AI infrastructure and consumer AI. Beyond capital, the fund promises to bring narrative and network support to founders. As Malpani puts it, India today has a once-in-a-generation advantage talent density, digital rails, and ambition to build global AI leaders from day one. At Startup Veda, we’re thrilled to see local capital fueling the AI frontier. This fund signals rising maturity in India’s venture ecosystem—placing conviction behind AI-first founders well before the rest of the world catches on. Join the conversation: Which early-stage AI ventures excite you the most? How powerful is the mix of capital + storytelling for building AI startups? #Startup #AI #VentureCapital #DeepTech #StartupIndia #FounderStories

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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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Anthropic raised $13B at a $183B valuation Fundraise is greater than entirety of VC in India raised in 2024, valuation is close to that of all of India's unicorns in total The crazy part is that it's a spin-off team from OpenAI, which itself is worth $300B Different scale

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🚨 Big Change for Angel Investors in India SEBI has raised the bar for who qualifies as an Accredited Investor: 📉 Earlier: ₹2 Cr net tangible assets (excluding primary residence) was enough to start angel investing. 📈 Now: Net worth ≥ ₹7.5 Cr (with ₹3.75 Cr in financial assets) OR Income ≥ ₹2 Cr annually OR Income ≥ ₹1 Cr + Net worth ≥ ₹5 Cr (with ₹2.5 Cr in financial assets) Corporates/Trusts need ₹50 Cr net worth This raises a crucial question: 💭 What happens to those who met the earlier requirements, began their angel journey, but no longer qualify under the new rules? 👉 Will they be locked out of funds? 👉 Does early-stage capital shrink? 👉 Or will new models emerge to keep them engaged? I’d love to hear perspectives from founders, fund managers, and fellow investors. Drop your thoughts ⬇️ #AngelInvesting #StartupEcosystem #IndiaStartups #VentureCapital #AngelInvestors #SEBI #InvestingInIndia

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On this Independence Day, we are proud to announce the launch of Vizuara's first-ever AI product Our product team (Pritam Kudale and Pranavodhayam P R) has been working on this for months, and today we're launching DynaRoute - an intelligent router that automatically selects the best language model based on your query complexity and category. Here is the problem we solved: Most applications use one expensive model (like GPT-4) for everything. Simple questions like "What is the capital of France?" get the same treatment as complex reasoning tasks. It's like using a hammer for every job, even when you just need a screwdriver. DynaRoute analyzes each query and routes it to the optimal model. Simple questions go to efficient models like Gemini Flash. Complex reasoning tasks get routed to more powerful models. The result? 50-70% cost savings while maintaining performance. We tested this extensively. On our GPQA benchmark, we achieve a 9.7:1 performance-to-price ratio compared to 6.9:1 for single model solutions. For typical enterprise queries, we're seeing 93% cost savings over 300k tokens. What makes this different from AWS or Azure routers is the full spectrum access. We support open source and closed source models across GCP, AWS, and Azure. Their routers lock you into their ecosystem - Microsoft only gives you GPT models, Amazon only Claude/Llama. The integration is seamless. Drop-in replacement for OpenAI API, works with CrewAI agents, includes an MCP server for Claude, and comes with a comprehensive dashboard showing real-time savings. This is Vizuara's first AI product for enterprises, and Raj Abhijit Dandekar, Rajat Dandekar, and I are incredibly proud of what the team built. We have transitioned from education to solving real industry problems. Try it at https://lnkd.in/dGSx2KRq - free tier includes 50k tokens to test the $$ savings yourself. We just posted our product launch video on Vizuara's YouTube channel, where we give you a very detailed product walkthrough. We also explain how you can use this as an individual customer or as an enterprise to save $$$: https://lnkd.in/dtEHtHMn We will soon be publishing a paper on the concept of dynamic intelligent routing. Stay tuned. Happy Independence Day to my fellow countrymen! 🇮🇳

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