Apoorv Saxena

🎉 Introducing Darwin – Now Open Source! We're thrilled to announce that Darwin, our end-to-end ML platform, is now officially open source and available to the community! When scaling systems to support 300M+ users, we needed robust ML infrastructure that could keep pace. We evaluated every solution out there, but nothing fit our requirements. So we built Darwin from the ground up. What is Darwin? Darwin is a production-ready ML platform that handles the complete machine learning lifecycle – from feature engineering and model training to deployment and inferencing. It abstracts away infrastructure complexity, letting you focus on what matters: building intelligent solutions that scale. Ready to build something extraordinary? 🔗 Learn More: darwin.dreamhorizon.org ⭐ GitHub: https://lnkd.in/dBAsByg2 Explore more from Dream Horizon: https://lnkd.in/d5SnrHcf

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💡 Designing for India’s Gig Workforce Building for delivery partners means balancing simplicity, adoption, and motivation. In this podcast episode with Darshan Suthar, we spoke about what it takes to build for India’s gig workforce at scale. We explored: 🔹 Making products intuitive for non–tech-savvy users 🔹 Solving adoption challenges in real-world conditions 🔹 How gamification and incentives shape partner motivation At the heart of it all is empathy—understanding partner challenges on the ground and translating them into product choices that drive trust and impact. 🎧 Watch the full episode here: https://lnkd.in/eFSFPsVB

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Category-defining businesses have reshaped how India eats, shops, travels, and transacts. Today, they operate at a scale where patterns shift in real time and fraud vectors evolve daily. Many of them are also expanding beyond borders, serving customers across the world. Yet these brands overcome such challenges every single day. Our new brand film celebrates these very businesses. Since the early days, we at Cashfree Payments have empowered our customers with intelligent solutions built into the payments core, helping them scale with confidence in India and globally with infrastructure that learns and evolves alongside them. #OneOfYourKind #CashfreePayments

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India just unlocked its next billion-dollar talent race and it’s all about production-grade AI. Not prototypes. Not lab experiments. Real-world, revenue-driving Voice and Chat systems. And the people powering this shift? Forward-Deployed AI Engineers. The ones who can ship, not just theories. Here’s what we’re seeing on the ground: * The demand curve is madness: Startups want engineers who can take a voice or chat experience from idea to deployment without hand-holding. * Skills > years: NLP/NLU chops, voice UX intuition, multilingual systems, and MLOps readiness are beating traditional experience benchmarks. * India has become an AI proving ground: Global and homegrown players are betting on Indian teams to build production-grade conversational systems. At Talentiser, we’re deep in the trenches with these teams, helping AI-first companies hire engineers who don’t just build features, but define the product. If you’re hiring in this space or you’re an engineer looking to make a dent in Voice or Chat AI, this is the moment. Let's talk in my DMs. #AI #VoiceAI #Chatbots #ForwardDeployedAI #Talentiser #HiringTrends #IndiaAI

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“What happens after an IPO matters more.” That perspective from Kalyan Krishnamurthy reflects how Flipkart has evolved under his leadership. Over nearly a decade, Kalyan helped transition Flipkart from a high-growth, founder-led startup into a professionally managed ecommerce institution. He navigated leadership transitions, strengthened alignment with Walmart, expanded supply chain coverage across 22,000+ serviceable PIN codes and scaled a platform serving 500M+ users and 2M sellers. What stands out is his ability to shift the narrative from valuation to durability. The India domicile shift signals capital market ambition. Yet Kalyan Krishnamurthy frames the IPO as a responsibility milestone rather than a celebration. Management prepares the company. The board decides timing. That clarity of roles reflects governance maturity and institutional discipline. He speaks about building a predictable and future-proof organization through AI-enabled discovery across 200M listings, seller-focused tools that improve productivity and operational discipline that protects long-term economics. This is structured, long-horizon thinking. In today’s environment, listing-day excitement often dominates conversations while post-listing accountability defines outcomes. Retail participation in India’s markets continues to deepen. Public capital deserves transparency, compliance rigor and sustainable economics. Kalyan Krishnamurthy’s ability to grow Flipkart while reinforcing governance signals a shift from scale-at-all-costs to scale-with-discipline. An IPO changes stakeholder complexity forever. Preparing for that phase instead of chasing it reflects long-term stewardship. That mindset ultimately shapes institutional credibility. https://lnkd.in/g_Gct6Wd

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Prime Day 2025 was a defining moment for Amazon Beauty — reaffirming that customers across India are not only shopping more online, but are choosing beauty with intention. From luxury skincare to color cosmetics, salon-at-home experiences to high-performance personal care appliances — customers increasingly gravitated towards trusted, high-quality brands that offer both value and aspiration. Beauty saw standout growth across the board, led by premium and performance-driven brands that resonate deeply with today's informed, experimental, and trend-aware consumer. This momentum extended beyond core beauty. We saw a premium mindset reflected in rising demand for fine watches, everyday luxury jewelry, and elevated luggage — signaling that customers are shopping across categories with an eye for quality, style, and personal expression. What’s especially exciting is where this growth is coming from. Tier 2 and 3 cities contributed to over 70% of new Prime sign-ups, and are quickly becoming the epicenter of trend adoption. Customers from emerging India are not just online — they’re actively shaping how the country shops for fashion and beauty. As we build for the future, Amazon Beauty remains focused on helping customers discover what’s next — through inclusive selection, accessible luxury, and a seamless shopping experience. Thank you to our brand partners, sellers, and teams for making this our biggest and boldest Prime Day yet. #AmazonBeauty #PrimeDay2025 #CustomerObsession #BeautyForward #DigitalBharat Aditya Zutshi Digish Parekhkhushboo kaushalNupur SarafRuchika TripathiPankaj KothiyalShalini MattaShivali Mittal Jeet KumarServesh JasraAbhishek SahaSubhasish Sahu Atul Prakash https://lnkd.in/gxhCqnzd

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Thinking of launching a cloud kitchen reliant solely on Swiggy or Zomato? Think again. The harsh reality is, you may be setting yourself up to lose more than you imagine. A recent candid chat with a friend planning to enter cloud kitchens forced a hard look at the numbers – and the reality is stark. Here's a rough math for reference: Running the unit economics for a 100% aggregator-dependent model in the Indian QSR space paints a challenging picture. On a gross revenue of ₹100, factor in an average 15% discount, ₹25 for food costs, ₹3 in wastage (a conservative estimate!), ₹12 for staff, ₹15 for rent & utilities in metro cities, and ₹15 for marketing just to stay visible on the platforms. Then comes the big one: roughly ₹25 in aggregator commissions. Do the math – you're likely losing money on every order. Even in the absolute best of cost scenarios, the profit margins are razor-thin, leaving virtually no room for corporate overheads and other essential costs. Speaking with founders and investors, a recurring theme emerges: over-reliance on aggregator platforms erodes profitability. This trend is evident in the annual revenue reports of many food tech startups, often showing deep red numbers. (For a deeper dive, check out my earlier post on this topic – link in comments). So, what's the takeaway? The Unit Economics Trap: Aggregator-exclusive cloud kitchens often operate at razor-thin or negative margins once all costs are truly accounted for. To counter this, target a 35% Direct Order Mix: Aim for a minimum of 35% direct orders (your own app, website, potential subscription models) to regain pricing flexibility and protect your bottom line. This means you need to Reclaim Control: Owning your customer data is invaluable. Reduce dependence on high aggregator commissions and optimize your marketing spend beyond platform visibility. While cloud kitchens can benefit from potentially lower rent and streamlined staffing, you must Leverage Your Strengths Wisely; these advantages are quickly negated by significant discount pressures and commission fees. Leaders in the Indian QSR and cloud kitchen space, what's your current direct vs. aggregator sales split? What strategies are you implementing to build direct channels and ensure sustainable profitability? Keen to hear your experiences and insights! #CloudKitchen #UnitEconomics #FoodTech #AggregatorEconomics #DirectToConsumer #FoodStartupIndia #InvestorInsights #Profitability #Startups #Swiggy #Zomato

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Thrilled to share this insightful blog from our engineering team on powering real time analytics at Meesho's massive scale handling billions of events daily without missing a beat!!! #meesho #meeshoeng

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Had a good time speaking at the 10th Edition of Product Management Summit in Bangalore a few days back. My session for seasoned Product leaders covered how to measure success of any product, creating and analysing segmented retention curves, how to nurture a set of engaged (and loyal) power users, and how closely episodic NPS is correlated with customer retention for high repeat businesses. Also spoke about the link between product strategy, OKRs, and KPIs.

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𝗔𝗺𝗮𝘇𝗶𝗻𝗴 𝗗𝗮𝘆 𝟭 𝗮𝘁 𝗜𝗻𝗱𝗶𝗮 𝗔𝗜 𝗜𝗺𝗽𝗮𝗰𝘁 𝗦𝘂𝗺𝗺𝗶𝘁 🇮🇳 The energy in the room was incredible — builders, researchers, and operators all pushing the boundaries of what’s possible with AI in Bharat 🚀. Moments like this don’t just validate what we’re building, they expand our ambition. The conversations at the booth reinforced a simple truth: Bharat is ready to move from consuming AI to producing it at scale. Huge kudos to my incredible team for the passion and execution. And sincere thanks to the leadership at Meesho for backing bold bets and making platforms like this possible. Excited for Day 2.

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India just redefined AI-powered commerce. And it's not about chatbots. It's about trust, scale, and guardrails. On Oct 10 at Global Fintech Fest, NPCI, OpenAI, and Razorpay announced a collaboration that could change how 500M+ Indians discover and pay for products. But here's what excites me as someone building AI systems: This isn't just about AI agents processing payments. It's about building AI commerce infrastructure with: ✅ Compliance-first design - Built on India's trusted UPI rails ✅ Conversational commerce - Shop in your language, pay instantly ✅ Responsible AI at scale - Guardrails embedded from day one ✅ Financial inclusion - Bringing AI benefits to tier 2/3 cities The questions I'm asking: 🔹 How will AI agents verify user intent for high-value transactions? 🔹 What guardrails prevent fraud in conversational checkout flows? 🔹 How do we ensure AI doesn't push unnecessary purchases? 🔹 Can this work seamlessly across 22+ Indian languages? 🔹 What's the compliance framework for AI-driven financial decisions? Why this matters: We've seen AI content generation scale globally. But AI-powered commerce at India's scale—with built-in payment infrastructure and regulatory alignment—this is uncharted territory. If done right, this could be the blueprint for responsible AI commerce worldwide. My hope: That we build this with the same rigor we built UPI—user-centric, secure, and accessible to every Indian, not just the tech-savvy few. Kudos to Pragya Misra, Dilip Asbe, and the teams at National Payments Corporation Of India (NPCI), OpenAI, and Razorpay for taking this bold step. To fellow AI builders: How do we ensure AI commerce agents are helpful, not manipulative? Where should the guardrails be? This is the conversation India—and the world—needs to have. #AICommerce #ResponsibleAI #UPI #FintechInnovation #IndiaStack #AICompliance

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This shift from search & filters to conversation is exactly what the next wave of users needs, especially beyond metros. Engineering, at its core, is about solving complex problems with simple, intuitive solutions. "vaani” is a great example of that philosophy in action bringing natural, conversational commerce to millions. Big unlock for accessibility, discovery, and user trust. 🚀 #meesho #VoiceCommerce #DigitalIndia

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Flipkart has appointed ex-Meta senior executive Dan Neary to its board as the Walmart-backed ecommerce giant accelerates preparations for its India IPO. Neary, who led Meta’s growth across APAC for over a decade, brings deep expertise in scaling digital commerce, global markets, and platform ecosystems. His appointment comes as Flipkart shifts its domicile to India and strengthens leadership ahead of its long-planned public listing. CEO Kalyan Krishnamurthy said Neary’s global perspective will help drive Flipkart’s next phase of AI-powered retail innovation and long-term value creation. #flipkart #leadershipnews #danneary #meta #boardappointment #ecommerceindia #walmart #techleadership #ipo2025 #startupnews #digitalcommerce #aiinretail #businessupdate #ceomagazine #indiaretail #corporategovernance #industryleaders #marketexpansion #techindia

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I just published a detailed deep dive on designing a Commerce Intelligence Platform for India’s fragmented quick-commerce ecosystem. Brands today sell across Zepto, Blinkit, Flipkart Minutes, Amazon — but struggle to answer: • What is my true category market size? • What is my brand share vs competitors? • Why did my organic rank drop? • Which new launches are gaining momentum? This article covers: ✔ Full database schema (entity → fact → mart layers) ✔ Rank-based market size estimation using Zipf’s Law ✔ Sponsored vs organic separation logic ✔ Tier-based accuracy system (100% accuracy for top SKUs) ✔ Microservices architecture ✔ LLM integration for classification, entity resolution & root-cause analysis ✔ SQL queries for every major business insight It’s a complete master architecture — end to end. Would love feedback from product, data, and commerce folks. #Ecommerce #QuickCommerce #SystemDesign #DataEngineering #AI #ProductArchitecture

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Wonderful read. Very well captured that how we solved extremely complex problem, sits at the center of Flipkart core pricing engine. Very high tech impact and massive business impact. Blog Link : https://lnkd.in/gEzTiBad

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Our Tech Rails for Quick Commerce — Store 2.0 Now Live Across All Bangalore Stores. Excited to share that we’ve gone live with our omnichannel and Store 2.0 stack across all our stores in Bangalore. Each store now functions as a micro-fulfillment center, enabling 24-hour delivery city-wide. The stack includes a robust POS, real-time inventory sync, store-level warehouse management, and a distributed order management system — all built in-house by just 2 engineers in under 2 months. We’re working on scaling this to all 63 stores across India in the next 30–60 days. Huge shoutout to our engineering, operations, and retail teams for making this happen. A solid step toward our quick commerce vision. More soon. Siddharth DUNGARWAL Aniket Singh Chetan Siyal Mahadevan Pillai Bade Nikhil Kumar Alok Kumar Mishra Tanya Singh Faisal Jamal Kidwai Pratik Agarwal Devender Singh Prithwish Sinha Sanjib Samantaray E.Sagar Kumar Patra Sachin Singh Bhavna Chaudhary Ashwin Kottapally

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