Nishanth Kottapalli

Notes for early-stage DeepTech (DT) founders in India basis recurring patterns I’m seeing. Also blocking an hour on Tuesday, the 25th of Feb to answer qs related to the points below and other related matters. Registration link below if you’d like to join. Feel free to share with other DT founders. 1.     If you’re on the fence today, take the plunge. 4 out of 5 Indian seed-stage investors want to do some deep tech now 2.     Growth (early-or-late) funding is still an issue though. This will change, but start developing overseas relationships from the word go 3.     Given the above, take as much money as you can at the first round even if it means you dilute up to 35/40%. It could help eliminate a bridge round later so expected value is similar 4.     Growth-stage DT valuations are meaningfully worse than non-DT valuations because of #2 above. So don’t overvalue yourself early on lest you should price yourself out of the market later. Trade off valuation for other benefits – a higher raise, better investors, etc. 5.     Corollary of all of the above: expect to dilute 30%+ at every round. Don’t fret, it’s fine 6.     Investors will seldom make any serious effort to understand your tech, so it’s incumbent upon you to make it simple for them. You’ll have to do this with customers too. 7.     As with everything else, storytelling trumps the actual business. Work hard at this. And get your investor deck made/ spruced up from a professional. The Rs.25-50k (deck) will be very well spent 8.     Related to #7 above, invest heavily in PR from Day 1. This feels like a nice-to-have, but it’s actually important for all startups and critical for DT ones 9.     Irrespective of how cool your tech is, you are unlikely going to be able to sell your IP/ product for hundreds of millions of dollars – that just doesn’t happen in India 10. So, think and sell a business to investors. That’s also much easier for them to understand 11. The DT playbook is very different from the non-DT playbook, so work with investors who know that well. For example, Series A/ B investors want meaningful revenues, but it’s very unlikely you will have revenues till then, and a mismatch could create great friction 12. And finally, all DT is equal, but SpaceTech is more equal than others https://lu.ma/xj7ol9ci

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An area that Anjali Nair and I have been spending some time on lately, is vertical micro-drama apps globally and in India. Some key features of these apps: 📱 Vertical format designed specifically for smartphones ⏱️ Episodes run just 1-3 minutes each 📺 Full series contain 70-150 episodes (equivalent to a feature film when binged) 🎭 Scripted, melodramatic content with fast-paced plots 🔄 Cliffhangers and over-the-top storylines designed to hook viewers instantly This format originated in China and has since boomed globally: - Kuaishou hosts 100,000+ micro-drama channels with 270M daily viewers (70% of DAU) - ReelShort, DramaBox, ShortTV lead the US market - Many platforms were created by teams with mobile gaming backgrounds - Top apps saw 34M monthly downloads and $78M revenue in early 2025! It's clear to me that India is going to see a huge wave of vertical video, episodic micro-drama startups launching in the coming months. For founders building in this space, consider: 🎯 Content Strategy: Focus on culturally resonant genres - not just romance, but family dramas, mythology and comedy that speak to Indian audiences 🗣️ Language Approach: Launch with multiple regional languages from day one - Hindi alone won't capture the full market potential 💰 Monetization Mix: Design a smart freemium model with brand integrations that accounts for India's price sensitivity while maximizing revenue 🚀 Capital Efficiency: Balance content production costs with marketing spend to achieve scale before competitors 📊 Measurement: Build analytics that track not just views but completion rates and emotional engagement to prove value to advertisers We're actively seeking visionary founders ready to capture this emerging opportunity. The perfect storm of India's mobile-first population, our love for dramatic storytelling, and evolving consumption patterns makes this the ideal time to build in this space.

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How can I ride the AI wave through public markets in India? I asked this research question on ChatGPT 5Pro: "Which industries and subsequently type of companies will benefit substantial from the introduction of AI in mainstream business? Research recent past results of public companies, earnings calls of ceos and cfos and discussions to provide insights What’s the purpose of this report? As a public market investor in India, I want to get ahead of the curve and invest in publicly listed companies (from any industry) that will benefit from AI in their earnings over the next few quarters, thereby providing an edge for investing in them before the market catches on." The answer is available to read as a PDF in the link below! (Gimme feedback if this helps you and you want more! Also, if you wanna partner with me on researching and investing in Indian/Global markets, just ping or write me at alok@Games2win-dot-com #Dhandhekibaat https://lnkd.in/dp47ZCVZ

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📍 UPI moment for Indian Pincode and addresses! India has launched DigiPIN – a revolutionary digital address system by India Post, in collaboration with IIT-Hyderabad and ISRO. 🔹 What is DigiPIN? A unique 10-character alphanumeric code for every 4x4 meter location in India – like a desi GPS, but offline-friendly and ultra-precise. ❌ Why traditional PIN codes failed: One PIN covers hundreds of houses No rooftop accuracy Confusing for couriers & delays in deliveries ✅ Why DigiPIN is a game-changer: Unique code for every home, shop, or hut Works in cities, villages, remote areas Accurate voter/Aadhaar linking & faster e-commerce No personal data stored – just your location 🧭 How to get yours: Visit India Post website Enter your location Get your DigiPIN (needs GPS/GNSS enabled device) It’s part of India Post’s “Address-as-a-Service” (AaaS) initiative — open-source, interoperable, and a big step toward Digital Bharat. 🌐 So no more "Peepal ke pad ke peeche" or " Google Aunty wrong direction" :) Do you think it is a UPI moment for Indian Postal System? Let’s spread the word. Every Indian deserves a digital address. #DigiPIN #IndiaPost #DigitalBharat #Innovation #Logistics #Ecommerce #AddressRevolution #GovTech

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Introducing DynaRoute - intelligent model routing for efficient LLM usage At Vizuara, we (Pritam Kudale, Pranavodhayam P R, Raj, Rajat) have spent the last few months studying how teams use large language models in production. What we found was simple but eye-opening. Most teams rely on one large and expensive model for every kind of query, whether it is a quick factual question or a complex reasoning task. This works, but it wastes a lot of money and computing power. That is what led us to build DynaRoute (https://lnkd.in/dGSx2KRq), an intelligent routing layer that automatically analyzes your queries and sends them to the most suitable model based on complexity, cost, and performance. You do not have to change your application or rebuild your backend. You can continue using your familiar OpenAI-style API, just by switching the base URL and key. From that point, DynaRoute handles everything intelligently behind the scenes. In our internal benchmarks, DynaRoute delivered remarkable results. Real-world employee questions achieved up to 92 percent cost savings, while code-related queries saw around 74 percent savings. All of this happened while maintaining nearly the same quality and accuracy as top-tier models. For teams that are running customer support systems, coding assistants, agents, or RAG-based pipelines, DynaRoute can reduce your inference bills drastically while preserving the quality your users expect. You can think of it as a smart, adaptive router that continuously learns how to choose between models like GPT-4.1-nano, Gemini 2.5 Flash, and Claude Sonnet, depending on the query. We also provide API access so you can integrate DynaRoute directly into your own platform or agent framework. The API is OpenAI-compatible and can be configured with just a few lines of code. Here are our current plans: Free Tier: ₹0 per month, includes up to 50,000 tokens, OpenAI-compatible endpoint, and access to premium models. Plus Tier: ₹888.30 per month, includes up to 3 million tokens, unlimited requests, access to premium models, and priority support. Enterprise Tier: completely custom implementation for companies that need dedicated support, detailed analytics, and on-premise deployment. We also provide custom routing models for enterprise-level optimization. We are currently offering Enterprise Plan API access to selected partners who wish to integrate DynaRoute into their platforms. If you want to optimize the cost and performance of your LLM-based applications without compromising output quality, give DynaRoute a try. 👉 Learn more and get your API key at https://lnkd.in/gTrs9NWA

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Twin brothers from India built an AI platform that achieved $15M in ARR in just 90 days. Is this the Shopify-for-apps moment? Here’s is the full story Emergent, founded by twin brothers Mukund (ex-Dunzo CTO) and Madhav Jha (ex-Dropbox/Amazon infra), just raised $23M Series A led by Lightspeed (total $30M to date). Their pitch? A multi-agent ‘vibe coding’ platform that turns plain English prompts into full-stack apps: frontend, backend, auth, payments, deployment, all automated. And the traction is wild: 👉 YC copy in mid-2024: 700k users, $10M ARR in 2 months. 👉 By Sept 2025: over 1M people building 2M apps and $15M ARR in 90 days. Why does it matter? Because Emergent isn’t just “no-code.” It aims to be the Shopify for apps, where anyone can generate production-ready tools, deploy them instantly, and eventually monetise them. Think jewellery chains spinning up AI-pricing apps, SMBs ditching spreadsheets for onboarding tools, even healthcare patients building pain-management solutions. But here’s the catch 👇 Retention > creation. Generating millions of apps is flashy. Keeping them live, secure, and monetised is harder. Discovery and billing flows are still in their early stages. Quality & compliance. Building real apps means adhering to PCI compliance, implementing secure authentication, and maintaining safe data practices. Emergent claims in-house testing/security agents, but independent audits will matter. Competition is fierce. Replit, Builder(dot)ai, Rocket(dot)New, Cursor: Everyone is chasing “apps from text.” Emergent’s moat must be infrastructure, reliability, and a marketplace. Unit economics. Hosting and runtime LLM costs scale with the number of active users. Using cheaper models and caching helps, but the test is focused on gross margin at scale. The opportunity: The low-code/AI app market is forecast to hit hundreds of billions by 2030+. If Emergent nails reliability, discovery, and monetisation, it could be the default platform SMBs use to generate and sell apps in days, not months. Question for you: If you could build a full-stack app from a single prompt, what would you build first? ➕ Save this post and follow Zubin Kutar ⚡ to Learn & Grow 10x with AI

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RIP Robotic text — I found a Humanise AI tool that makes everything 10x more natural! Introducing ChatLLM by Abacus.AI . All AI tools in one place! - http://chatllm.abacus.ai HERE ARE ALL THE FANTASTIC FEATURES 1. ACCESS TO ALL THE SOTA LLMs ChatGPT- 5 Pro, o4, Claude 4, Gemini 2.5, Grok 4.1, DeepSeek, and many more 2. IMAGE & VIDEO GENERATION Using the best AI models, FLUX, DALL-E, Ideogram, Kling, Runway, Luma & many other tools to turn your ideas into amazing pictures & videos. 3. BUILD APPS & WEBSITES A simple prompt instantly gives you live website previews. Edit everything—colors, text, layout—effortlessly! 4. AI PRESENTATIONS ChatLLM allows you to generate Word, Excel, or PowerPoint files quickly with a single prompt. It is quick, simple, and time-saving. 5. AI PERSONAL ASSISTANT - OPERATOR AI handles tasks for you 24/7, even while you’re asleep. It can search the web and take action, acting like a personal assistant that never needs a break. 6. CHAT WITH PDF You can work with any document, no matter how long or short & when things get complicated, get a quick summary that makes sense. 7. HUMANIZE AI CONTENT RIP AI Detectors. Generate your AI content. Just click the "Humanise" icon, choose your preferred tone, and the text will become human. 8. SEARCH THE WEB RIP Perplexity - ChatLLM gives real-time answers with trusted sources, images, and videos. 9. DEEPAGENT (To literally do everything) Create mobile Apps, Websites, Technical reports, presentations and much more with simple prompts. Make edits with simple english! 10. AI CODE EDITOR + ASSISTANT: CODELLM This AI Code Editor helps you write, run, and perfect your code with ease. Vibe Coding it is! This all-in-one tool can replace all your AI tools for just $10 a month! Give it a shot! http://chatllm.abacus.ai

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Can India catchup in the global AI race? Or are we too far behind? 🤔 I think Indian companies & startups should build their own proprietary and vertical LLMs. The first wave of LLM emerged in 2018 with GPT 1 and today Open AI along with a few other companies have a massive head start over anyone else. Now building LLM is no longer constrained due to financial or technical resources. If this were the case, Google’s DeepMind or IBM WATSON would have had a headstart vs anyone else. But that didn’t happen. Right? Now I don't buy the argument that we should just build LLMs by emulating existing models. Ideas and companies are still bound by complex geo-political rules and economic factors. Open-source models may not remain open-source forever. Indian companies and startups should prioritize building proprietary vertical LLMs on top of base models but not be entirely dependent on them. They are good to begin with but one needs to detangle gradually. This approach allows for domain-specific specialization, enhancing defensibility and competitiveness in the AI landscape. We are already witnessing an intense race in GenAI, AGI and LLMs as every country is keen to compete in a sprint to emerge as the leading player in the ecosystem vs running a marathon. Key Considerations: In 2024, Indian startups raised $13.2 billion in funding, which was a 22% increase from 2023. (Source: Inc42) We do have the financial might to build LLM’s. Now about talent. Before we start building LLMs we need to have a massive pool of data that needs to be prepared, curated and cleaned. Borrowing a cue from our massive IT infrastructure we can certainly pull this off. Given the number of illustrious alumni we have across our engineering schools, grants and endowments can help us establish or encourage a stronger research culture geared towards building a homegrown talent pool of AI researchers and experts. If we can pull off space programs at a fraction of a cost then we can certainly build LLM’s. International sanctions didn’t stop ISRO from innovating. China’s Deepseek ‘Sputnik” moment is a great example that with the resources we have we need an ISRO moment to bring forward our judiciousness & resourcefulness to build an LLM from India. By focusing on vertical AI applications, Indian companies can create specialised models that serve unique market needs, providing a competitive edge in global AI.

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🚀 सहज जीवन: probably the first open-source, collaborative, public, and live Marathi book, built transparently on GitHub. 🚀 The first part is a translation of Leo Babauta's "The Effortless Life" in Marathi, and the second part is open for contributions. I’ve already added a couple of chapters there myself. The idea is simple: anyone with useful insights about leading a good life can join and contribute. Contributions are voluntary, no money involved. 💡 Eligibility criteria for contributors: - Fluency in reading and writing Marathi - Basic GitHub literacy (fork, commit, PR). LaTeX expertise is not required - And yes, you must have read almost all of PuLa. That’s non-negotiable 😉 You can either refine the translation of the pending chapters or add fresh chapters of your own. Just fork the repo, add your changes, and send a PR. You can also  your add your name as co-author, thus build your own version of the book into a PDF, print it for yourself, and even publish it for wider circulation. I’m planning to self-publish a slightly updated version via Notion Press, which will naturally come with some costs. Feel free to do the same, the PDF is freely available in the repo. If you want to add a chapter, just place it at the end and submit a PR (Pull Request). If you are not comfortable with LaTeX or GitHub, you can share me the content via Google-Docs or email, I will add that on your behalf. 👉 If you’re interested in this whole “effort,” drop a comment below or message me your Gmail ID. I’ll schedule a short online meet or create a chat group to align next steps. IMO, this is not just a book, it’s a movement: bringing open-source culture to Marathi literature. Imagine being part of a collective that publishes a free, evolving, community-owned book! 📎 Repo name: yogeshhk/SahajJeevan (... on GitHub). 📑 Attaching the partial draft PDF here for a quick taste. (It’s a very rough draft, just to give you the idea.) जय महाराष्ट्र ✨

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This is massive ➡️➡️ ➡️ https://lnkd.in/gfpq_Pj9 I always wonder why this type of companies - with so much gunpowder can go BANKRUPT — maybe even more interesting, what does it mean for the AI Ecosystem The sudden collapse of Builder.ai sent shockwaves through the startup world. Once a rising star promising "apps without developers," Builder.ai raised over $450 million from top investors like SoftBank, Microsoft and the Qatar Investment Authority. But despite the hype, the company quietly filed for bankruptcy in early 2025, citing cash flow issues, high burn rates, and an unsustainable revenue model. At its core, Builder.ai overpromised and underdelivered. Never a good business plan. While marketing positioned it as a no-code AI app builder, much of the product relied heavily on human engineers behind the scenes. This hidden services layer inflated costs while the company priced itself like a SaaS business. The illusion of scalability masked the real unit economics, and when investor sentiment cooled, the funding tap ran dry. The fallout reveals hard truths about the current AI ecosystem: inflated valuations, unclear business models, and the fine line between automation and manual labor disguised as AI. My 3 take-aways especially for AI Entrepreneurs (everyone nowadays 😂): ❶ Validate the AI core 🤖 Don’t hide human-in-the-loop systems behind an “AI” label. Investors and customers eventually notice. Build real automation and prove ROI early. ❷ Match pricing to delivery model 💰 If your product has service-heavy components, don’t price it like pure SaaS. Misaligned pricing and delivery models kill margins. ❸ Burn discipline > fundraising headlines 🔥 I get it. It feels amazing to raise big rounds. Everyone is hyped up and suddenly you're running a "$100M business". But it's all vanity and doesn't mean anything, especially if your burn increases significantly. Builder.ai raised big, but spent bigger. Hype cycles really fade— durable businesses stay lean, iterate fast, and grow based on actual demand. That's how you win the long game. I think that Builder.ai’s fall is a warning shot. In a crowded AI market, smoke and mirrors won’t scale and startups with transparent value, capital efficiency, and defensible tech will survive the shakeout. CREATE VALUE 💰 DONT CHASE VALUATION 📈 Very different discipline. #ai #Artificialintelligence #startup #entrepeneur #valuecreation #VC #venturecapital #scale #valuation #keynotespeaker

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15M+ patients 18 FDA-approved products $125M+ funding IPO in sight When I first came across Qure.ai in 2016, they were just a Mumbai-based startup trying to teach machines how to read X-rays. No media blitz. No “move fast and break things” mindset. Just deep work on a hard problem. And today, they’re quietly rewriting what global healthtech scale looks like. What makes Qure.AI worth studying? It’s not just the tech. It’s their philosophy. They’re building like a company that wants to exist in 2050. Founded by Prashant Warier, Qure tackled a problem most startups avoid: How do you scale diagnostics where radiologists are scarce—or overwhelmed—without compromising trust? Instead of chasing adoption through shortcuts, they did the opposite: - Chose medical-grade AI, not demos - Focused on regulatory clearance, not vanity metrics - Took on go-to-market complexity across public systems, pharma, and hospitals - Expanded with intentionality, not headcount Here’s what founders should take away: 1. Trust is the new moat. Regulatory-first is not slow. It’s survivable. Especially in AI, health, or finance. 2. Capital efficiency is culture. ~200 people running a global AI company? That’s design, not luck. 3. Global readiness is not an expansion strategy. With 25% revenue from the U.S., Qure isn’t entering markets. They’re designed for them. The bigger picture: The next generation of global giants won’t all come from Silicon Valley. They’ll be born in Mumbai, Nairobi, and Singapore. In sectors where compliance isn’t red tape—it’s product-market fit. They’ll scale with fewer people, clearer systems, and tighter governance. And they’ll win not because of tech alone, but because they solve for distribution, regulation, and trust—from Day 1. If you're building in a regulated industry—how are you designing for trust before scale? I’d love to hear how you’re approaching it. #FounderLens #HealthTech #GlobalStartups

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Stackoverflow 2024 global developer survey n=65K. Indian devs had the sharpest & youngest peak at <2yrs. This is the experience segment AI is going to completely overwhelm. If we aren't ready, there's lots of pain ahead. We need retraining & upskilling programs on a war footing.

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📰Leapstart in The Times of India - But This Story Started Long Before the Spotlight. For years, I sat in conferences, review panels, and boardrooms listening to the same thing, over and over again: “There’s a massive gap between what academia teaches and what the industry actually needs.” Everyone nodded. Everyone agreed. And then… we moved on. No one wanted to touch the problem - not really. Not because they didn’t care, but because the system was too rigid, too slow, too “institutional” to be redesigned. Fixing it would mean breaking something. And breaking things in education isn’t comfortable. So the conversations stayed conversations. Until one day, I started having very different discussions - not in boardrooms, but one-on-one. With CTOs. Founders. Hiring managers. Product leads. People at the frontlines of building and scaling real-world tech. I asked them: “If you had the chance to redesign the system from scratch… what would you do?” They knew exactly what needed to change They weren’t confused about the problem. They were just tired of waiting for someone else to solve it. And that’s when the real shift happened. I sat down with my co-founders - And what started as a whiteboard rant turned into a real idea. A bold one. An uncomfortable one. One that didn’t tweak the existing model, but threw it out completely and asked: 🧭 What if we build the bridge ourselves? That’s how Leapstart began - not with a pitch deck, but with the decision to stop watching from the sidelines. We weren’t trying to build a college. We were trying to answer a challenge no one else wanted to touch. And once we started building, the real questions started pouring in. From parents. From professionals. From curious, skeptical, future-focused minds: 🔹“Is AI just another trend, or will it really change the kind of careers we need to prepare for?” 🔹“Is it too risky to step away from traditional engineering?” 🔹“What exactly will my child graduate within - beyond a degree?” These aren’t easy questions. And frankly, they shouldn’t be. 📌 But here’s what we know for sure: 👉AI isn’t coming. It’s here. 👉A degree alone is no longer enough. 👉Students need a new kind of education - one that adapts as fast as the world around them. That’s what Leapstart is built for. 🎓We built a 4-year experiential program in Computer Science with specialisation in AI & Data Science that’s project-based, mentored by industry experts: thinkers - not just test-takers. Not to chase trends, but to prepare for what the world actually needs next. 📣 Parents ask: “Will this get my child a job?” It’ll do more - it prepares them for jobs that don’t exist yet. 📣 Students ask: “Is it worth it?” If you’re ready to build what’s next - absolutely. We’re thankful to The Times of India for the spotlight. But this story isn’t about us - it’s about rethinking what comes next. #Leapstart #FutureOfWork #HigherEducation #ParentsAndStudents #TechEducation #LearningWithPurpose #SkillsForTomorrow

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Lately, I’ve been noticing a fascinating shift in the Indian film industry. Filmmakers are no longer just relying on cameras, crews, and sets — many are now building AI-powered businesses. 👉 Ajay Devgn launched Prismix and Lens Vault Studios to blend AI with creative production. 👉Vivek Anchalia’s Amazing Indian Stories launched an AI-powered Creative Studio and produced India’s first AI film Naisha 👉 Shekhar Kapur is planning an AI film school in Dharavi with Universal Music, while also working on his AI-driven series Warlord Industry leaders believe more such ventures will come, as filmmakers race to become first movers. As one filmmaker said: “AI isn’t replacing creativity, it’s accelerating it.” It’s clear — the move from studios → startups is gaining serious momentum. Why Filmmakers Need AI in 2025 Content creation is more demanding and competitive than ever. AI is no longer a nice-to-have—it’s becoming essential. In Films – “AI allows us to dream bigger on smaller budgets.” From VFX to dubbing and localization, it reduces cost + time. In Web Series – Faster episode generation, personalized stories for niche audiences, quicker turnaround In Brand Ads – “Why shoot 10 versions of a campaign when AI can create them in hours?” Hyper-personalised ads at scale This is why filmmakers, studios, and advertisers are embracing AI not just as a tool — but as a business strategy. How to Take Benefits ✔️ Creators → Cut production costs, scale experiments, keep IP ownership ✔️ Brands → Blend AI storytelling with OTT ads for better targeting ✔️ Audiences → Enjoy cheaper, faster, and more diverse content Why It Matters The momentum is real — and it’s backed by market forces. 👉India’s AI market is set to triple to ₹1.4 lakh crore ($17B) by 2027 (BCG report: India’s AI Leap). 👉 Powered by 600,000+ AI pros, 700M internet users, and 2,000+ AI startups in just 3 years For media & entertainment, this is a pivotal inflection point when seen against: Advertising industry → ₹1 lakh crore Entertainment sector → ₹2.5 lakh cror The overlap of AI + content will redefine how stories are created and monetized How OTT Platforms Can Help AI fuels creativity. But OTT fuels distribution and monetization Here’s why OTT is the missing piece for AI creators: ✔️ Launch your own OTT platform → Release AI-driven content directly, without relying on external algorithms ✔️ Experiment safely → Micro web-series, AI-generated shorts, digital-first experiments ✔️ Monetize smartly → Subscription, pay-per-view, ads, sponsorships ✔️ Build community → Loyal fanbase beyond social media feeds Final Thought Filmmakers are no longer just storytellers — they are becoming tech entrepreneurs. AI shapes stories. OTT shares them If you’re a filmmaker, creator, or brand — now is the time to explore this opportunity. Call: +91 7017235483 Visit us: https://mogiio.com Vivek Anchalia Shekhar Kapur #AI #Filmmaking #OTTPlatform #Innovation #AIFilmmaking

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