Divyendra Kumar

Kluisz.ai, led by former OYO senior executive Abhinav Sinha, has raised $9.6 million (INR 82.9 crore) in seed funding. The round was led by RTP Global and saw participation from Unicorn India Ventures, Blume Ventures Founders Fund, Climber Capital, and prominent angels. Founded in early 2025, Kluisz.ai is building an open-source, AI-native cloud platform to help enterprises deploy and manage AI and edge computing workloads. Check out the full funding details : https://lnkd.in/gjs3UKNB Team Kluisz Abhinav Sinha | Venkata Surya Tej | Vamshidhar Reddy | Abhijeet Singh | #oyoCOO #OYOemployee #AiStartups #SeedFunding #CloudStartups #FundingUpdates #startupro #startupUPdates

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Verticalization of ChatGPT   Every platform starts as a horizontal. We saw this with e-com. First came the generalists (AMZ/ FK) - where you could buy everything from books to baby food to tyres. But once digital habits were formed, verticals started to emerge: Myntra for fashion, Nykaa for beauty, Lenskart for eyewear, FirstCry for baby, BB for grocery. These verticals were not just clones with fewer SKUs. They were specialists with exclusive assortment, customized UX, different supply chains, richer content. They approached the problem differently, and in many cases won the battle.   Same verticalization will play out in consumer AI. ChatGPT (AMZ of AI) has been the most exciting generational product - fastest scale up to 100m MAU, strongly improving retention cohorts. It has formed a habit and breaking that seems near impossible. Can verticals emerge here? Think AI tutors. AI wealth managers. AI fortune tellers. AI therapists. AI travel agents. AI stylists. AI dieticians. AI companions/ friends, AI lawyers.   The use cases are infinite. But the outcomes won’t be (just like ecom). The question is - what separates the big outcomes from the rest?   The way to grok this is - a) can it provide a 10x better experience vs an addictive product like ChatGPT? b) Are there enough users where this 10x better experience matters (enough for them to pay) which can yield a large business?   Just like in ecom, where 10x better experience happened on the back on assortment, pricing or convenience/ experience. Here it would manifest in the following ways - 1) Depth of intellectual specialization required: For tasks where advisors are highly knowledgeable / skillset is scarce, building trust purely with ChatGPT seems unfeasible. These are also areas where stakes are high and inaccuracy is not tolerated. High bar for trust = potential for new vertical. Here need for proprietary data is a must have. Think - wealth advisory, health/ wellness, prep for JEE 2) Depth of emotional specialization required: These areas are not transactions. They're start of a relationship. It requires understanding the user well and enabling deep sharing, having a personality/ compelling storyline yourself. Think - AI companion/ friend/ therapist.   3) Criticality of differentiated user journey: ChatGPT is apt for clear intent, low stakes use cases. Areas which are more inspiration/ discovery led, requires more visualization vs text based approach. Requires pre-empting user needs vs letting them arrive there themselves. Think - AI stylist/ travel planning/ entertainer   ChatGPT is great 'Jack of all trades, master of none'. Areas with high expertise & need for differentiated experience are most obvious for verticalization. My bias is to always go for areas with high freq usage, as you're competing with someone who has already cracked that. High frequency = higher trust = higher potential to expand catg.   Now that digital habits on GPT are set, it's time for vertical winners to emerge!

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OpenAI declared war on Google yesterday and 82% of Indian shoppers are already on their side without knowing it. ChatGPT now has "Instant Checkout." You can search for products, compare options, and complete purchases without leaving the chat window. 700 million weekly users can now shop directly through conversations. Within hours of this announcement: 📌 Etsy's stock jumped 16%.  📌 Shopify gained 6%. The market immediately understood what this means for traditional e-commerce. When people use ChatGPT for shopping, they convert at 4× higher rates than regular websites, and that is because users spend 14 minutes per session on Ai tools like ChatGPT as compared to Google's 5 minutes. India's position in this makes it even more interesting: → 87% of Indian shoppers believe AI tools help them shop faster, with AI-powered interactions showing higher engagement rates (Walmart Retail Rewired Report India, 2025) → 62% of Indians make purchases influenced by AI recommendations vs 30% globally (EY India, Aug 2024) Traditional shopping makes you open multiple tabs, visit different websites, and compare prices manually. ChatGPT collapses this entire journey into one conversation. For small businesses, this could level the playing field. A seller in Jaipur gets the same access to global users as Amazon does. For established platforms, the threat is real. Why would customers visit your website when they can complete everything through a conversation? The companies optimizing for AI discovery today will own tomorrow's market. Is your business ready for AI-powered shopping or still relying only on traditional search?

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An Indian AI startup hit $25M ARR in just 5 months. And then something even bigger happened… Google’s AI Futures Fund invested in them. The startup is Emergent. It is the ONLY platform that lets anyone build production-ready apps just by chatting with AI. Not demos. Not prototypes. Actual apps you can launch, scale and use in the real world. Builders everywhere are switching from the most popular tools in Silicon Valley… because Emergent is deeper, more stable, and built for production. You can already see the momentum… 2.5M+ builders. 3M+ apps live. And $25M ARR in 5 months. That’s how fast this is taking off 🤯 But the founder story is the part I love the most. I’ve known Mukund for some time now. Google was his first job, and that place shaped him in ways that are obvious when you see Emergent today - user obsession, scale preparedness, deep engineering and zero shortcuts. He also previously built Dunzo. Google backed that. Now he’s building Emergent with the same philosophy… and once again, Google backs him. Founders like Mukund show what Indian founders can do. We are not playing catch up anymore. We are setting the benchmark. One global product at a time 🇮🇳

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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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Circle, a full-stack platform for buying and selling pre-owned products, has secured ₹3.4 crore in a pre-seed funding round led by early-stage VC firm Titan Capital, with participation from Raveen Sastry (Co-founder of myntra). The funds will help Circle improve its AI tools for pricing, product grading, and catalog matching. The startup will expand its electronics and home categories, grow its Bengaluru operations, and enter new cities by 2026. 🔗 Read full article link in comment Ankit Misra | Chirag Kataruka #circle #D2C #buyandsell #funding #startupnews #growth

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📍 How a PhonePe Transaction Works Securely 💳 Transaction Initiation The user enters the recipient’s handle, transaction amount, and UPI PIN within the PhonePe app. 🔄 Processing via UPI SDK The details are processed through the UPI SDK or Common Library, ensuring compliance with UPI protocols. 🗄️ Data Assembly & Transmission The transaction data is securely retrieved, structured, and sent to PhonePe’s server. 🛡️ First Factor Authentication Biometric authentication (fingerprint/face ID) is applied to verify the user’s identity. 🏦 Acquirer Bank Processing The transaction is routed to ICICI, PhonePe’s acquirer, where payment markup is handled. 🔗 Final Settlement at NPCI The request is sent to NPCI, ensuring a secure fund transfer between banks. 📈 Why It Matters? Every step ensures a seamless, secure, and fraud-resistant transaction experience. 💡 Stay secure and transact smartly with UPI-powered payments! #UPISecurity #PhonePe #DigitalPayments #Fintech #SecureTransactions

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Excited to share this News, 888vc, Our Early-stage venture capital firm based in Bangalore, India has launched platfrom Gro8 backed by ₹175 crore (US$ 20M) fund to back startups focused on AI, deep tech, Enterprise SAAS and sustainability over the next three years. 💡 Key Focus Areas: 🔹 Average ticket size of ₹2–4 crores 🔹 Sector Agnostic Angel fund 🔹 Focus on globally scalable solutions 🔹 Launch of GRO8 angel platform for cross-border funding, mentorship & market access 📌 If you’re building in AI, deep-tech, or sustainability with ambitions to grow globally, let’s talk. Read more here: https://lnkd.in/gtUcYkrx #888vc #gro8 #venturecapital #angelinvestments #startups

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BEYOND CODE: India’s Next Unicorns Won’t Be Built in Apps : They’ll Be Built in Fabs, Foundries, and Factory Floors For fifteen years, India’s startup story revolved around SaaS, GMV, CAC funnels and onboarding velocity. But the world changed. Supply chains fragmented. Tariffs rewired incentives. Hardware rose from the margins to the mainstream. And suddenly, India became the gravitational center of an $800 billion global manufacturing reallocation. China’s manufacturing wages have crossed $6.10 per hour. Vietnam is operating at 92 percent capacity utilization. Mexico–US cross-border processing crossed $735 billion. India still sits at $1.80–$2.40 per hour, with PLI commitments above ₹2.7 lakh crore and FDI at record highs. This is not a narrative shift. This is an industrial shift. My latest long-form analysis breaks down why India’s next unicorns will be built on physics, materials, power electronics, sensors, robotics, semiconductors, and precision manufacturing. It covers: • How India’s manufacturing GVA nearly doubled in ten years • Why electronics exports grew 3.3× • Why hardware margins now rival software • Why deeptech patent filings are exploding • Why global VC allocation to industrial tech jumped from 9% to 45% • Why India is the only large economy with both scale and cost competitiveness • Why the founders of 2030 must be IP-heavy, asset-heavy, and execution-heavy If you want to understand the next decade of Indian value creation, this is the blueprint. Read the full article: https://lnkd.in/gEXeEhgV India’s industrial renaissance has begun. The founders who build in fabs, foundries, and factory floors will define its future. #Business #Leadership #Innovation #GlobalEconomy #EmergingMarkets #IndiaTech #Manufacturing #SupplyChain #DeepTech #IndustrialTech #Startups #Founders #Investing #VentureCapital #PrivateEquity #Economics #Technology #FutureOfWork #Strategy #Hardware #Semiconductors #Robotics #Aerospace #Engineering

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When BlissClub crossed 100 Cr in ARR, we had exactly zero people in the tech team. And this is a common trend across D2C brands that I interact with: use Shopify’s built-in capabilities and its third party apps for common use cases + work with a Shopify dev agency or freelancer for custom work. However, that doesn’t happen often to business teams. Shopify has apps to generate reports and dashboards. But, you still need people to go through them to arrive at narratives and make decisions. The problem with D2C brands, as opposed to marketplaces, is that most key costs keep increasing with scale: cost of goods, cost of advertising, cost of shipping, etc. So, there is not enough money left over to hire quality talent. Therefore, well-paid talent will stay with consumer marketplaces, while brands make do with whatever they have and do not grow to their full potential. One solution to this would be humans (or human like) capabilities being available for hire on Shopify app ecosystem for non-tech tasks and workflows too. That’s the hypothesis I am building Verkerio with: perhaps more early stage brands will hire e-commerce & growth analysts and managers, if 80% of common tasks we do is done in <10% of the cost by a Shopify app.

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"The single biggest lie I hear from founders in Delhi/NCR: 'We just need more developers'. After working with multiple small and medium-sized IT firms here, the problem isn't always headcount. It's often a lack of a scalable architecture. You can throw 10 more engineers at a poorly designed system, and all you get is 10 more engineers working on a slow, buggy product. The real solution? An infrastructure that can scale with your business from 10 to 10,000 users without breaking the bank. For a small consulting firm, this isn't about buying the most expensive tools. It's about strategic choices: - Serverless for MVPs: Pay for what you use, not what you provision. - Containerization (Docker) for consistency: A dev in Noida gets the exact same environment as a dev in Gurgaon. No more "it works on my machine" issues. - Microservices for agility: Break down your monolith so you can innovate faster and your teams can work independently. This isn't just tech talk. It's about saving lakhs in future maintenance costs and avoiding a complete re-platforming nightmare a year down the line." "Founders, have you faced this 'hire more developers' trap? What was your real solution? I'd love to hear your story." #DelhiNCR #ITConsulting #FounderLife #StartupIndia #TechStrategy #SoftwareDevelopment #Noida #Gurgaon

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The third model of quick commerce. First model: Horizontal q-comm led by players like Blinkit, Zepto, and Instamart. Products across all the categories are listed on these marketplaces. (This model has attracted investments worth $2.5Bn+) Second model: Vertical q-comm platforms with focus on a particular category. We are witnessing the very early stages of this model. Led by vertical e-comm players experimenting with q-comm (Myntra Now) and fundraising spree for new vertical q-comm platforms like FirstClub (premium grocery), Peeko (babycare), and Knot (fashion) Third model: This model is not functional yet, and it’s unclear how it will develop. The idea is that D2C players will sell directly to customers in 10-mins from their website through shared dark stores. There will be a network of shared dark stores. This model will be facilitated by backend supply chain players who will setup these dark store networks to deliver orders within a 10-mins to 1-hour timeline. Players like Blitz, Inamo, Shadowfax, and Delhivery are working on this problem statement with the highest funds been raised by Blitz (~$6Mn) till now. No D2C brand will own these dark stores. They will buy/rent shelf-space on these dark stores. These players won’t have to bear any marketing cost, so the commissions/costs are expected to be significantly less than that of marketplaces (first 2 models). It will solve 2 problems: 1. D2C brands won’t be losing website customers because of quick delivery expectation i.e. better customer data for promotions & loyalty programs and a lot of other benefits of having a customer transact on your website 2. Brands can control their P&L and pricing better without exorbitant platform commissions I think this model will gain traction only once quick commerce steals a significant share in non-grocery categories. I am bullish on the third model. This model will not replace either of the other two, it will co-exist. It will make D2C sales channel more relevant and give brands more flexibility. At least this is what I think. Really interesting to witness these paradigm shifts in Indian online commerce so closely. And the best part is that we don’t have any western parallels to predict how the future of q-comm will look like. India will set the trend. What do you think about the future of the third model? 👇 Dcluttr | Ritvik Nagpal

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𝐃𝐢𝐬𝐭𝐫𝐢𝐛𝐮𝐭𝐢𝐨𝐧 𝐟𝐨𝐫 𝐔𝐒-𝐈𝐧𝐝𝐢𝐚 𝐃𝐞𝐯 𝐓𝐨𝐨𝐥𝐬 𝐒𝐭𝐚𝐫𝐭𝐮𝐩𝐬 𝐈 𝐆𝐢𝐭𝐇𝐮𝐛, 𝐂𝐨𝐧𝐭𝐞𝐧𝐭, 𝐂𝐨𝐧𝐟𝐞𝐫𝐞𝐧𝐜𝐞𝐬 With Pranay Prateek and Team SigNoz hitting KubeCon this week, this is a good moment to share their insights on US-India dev tools GTM via An Operator's Blog. (Full episode link in the comments)

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