Category: Startup Funding News

Rocketlane builds software that helps professional services teams run customer implementations and project delivery. Resource planning lives there too. Rocketlane Nitro, the company’s AI execution layer, secured a strategic investment from Atlassian Ventures on July 7, 2026. The investment comes just months after Rocketlane raised a $60 million Series C. Many enterprise implementations still rely on spreadsheets, scattered documents, and generic project management tools. Founded in 2020 by former Freshworks executives Srikrishnan Ganesan, Vignesh Girishankar, and Deepak Bala, Rocketlane aims to solve these challenges with purpose-built software.

What is Rocketlane Nitro and how does it work?

Rocketlane is basically a delivery operating system for services teams. Once a deal closes, it can pull customer context from the CRM and spin up a project from templates. It also turns handoff material like SOWs into an execution plan people can actually work from. The company’s current pitch is broader than onboarding now — it’s trying to cover the path from signed contract to go-live inside one PSA platform.

The customer side is a big part of the product. Rocketlane gives teams a branded client portal with real-time visibility, shared plans, forms, documents, and updates, so customers don’t need to chase implementation managers over email to figure out what’s stuck. It also supports automated reminders and follow-ups. Authentication options like magic links or SSO matter when lots of outside stakeholders are involved.

Internally, the software goes past project tracking. Teams can match people to work based on availability, skills, and workload. They can track time, forecast capacity, and see profitability while delivery is still happening instead of after finance closes the month. That distinction matters because a lot of older tools still split project execution and staffing. Margin visibility often sits somewhere else.

Nitro is the part Atlassian is really betting on. Its agents can generate documentation and convert SOWs into plans. They can also flag risk signals, help with migrations, and automate configuration and validation tasks that usually eat up delivery hours. In early deployments, Nitro has cut delivery effort by as much as 50%. That’s an ambitious number, but it’s tied to a specific kind of repetitive implementation work instead of vague AI productivity talk.

Who founded Rocketlane and how did the company get here?

Built from a Freshworks lesson

Rocketlane didn’t come out of nowhere. Ganesan, Girishankar, and Bala had already built Konotor, a mobile-first messaging product that Freshworks acquired in 2015. At Freshworks, they helped relaunch Freshchat and spent enough time in larger enterprise deals to notice something most software companies treated as an afterthought: onboarding and implementation were critical, but the tooling around them was weak. They started Rocketlane in April 2020, had the product in internal use by December that year, and took it to market in June 2021.

Why this team looks credible

That background matters because Rocketlane’s founders aren’t first-time operators guessing at a workflow. The three have worked together for more than a decade, founded Konotor in 2012, and later built Freshchat from 0 to $13 million in ARR as one of Freshworks’ fastest-growing products. Before writing code for Rocketlane, they ran more than 80 customer interviews. That’s not glamorous. It is, however, how boring, painful enterprise workflows usually get turned into good software.

Traction, rounds, and the cap table

The company’s numbers have started to catch up with the story. Revenue more than doubled over the past year, average deal size is up 4.5x since 2023, and the customer base now tops 750 globally, including 20 companies on the Forbes Cloud 100 list. In March 2026, Insight Partners led a $60 million Series C, bringing total funding to $105 million; that round followed a $24 million Series B backed by 8VC, Matrix Partners India, and Nexus Venture Partners. Rocketlane said that capital would go into R&D and enterprise go-to-market. Global expansion is part of it too. It has already added offices in London, New York, and San Francisco.

Can Rocketlane beat legacy PSA tools?

This is where Rocketlane gets interesting. Buyers don’t just compare it with one set of rivals — they compare it with dedicated onboarding tools like GuideCX, heavier PSA platforms like Kantata and Certinia, and generic work-management products like monday.com, Asana, and Smartsheet. Rocketlane’s argument is that those older stacks either stop at project visibility or lean too hard toward billing and back-office control, while Rocketlane tries to combine client collaboration and delivery execution. Resource planning, time, and AI agents sit in the same system. If that pitch lands, the moat isn’t “we also added AI.” It’s that the AI sits inside the workflow where delivery work already happens.

Why did Atlassian back Rocketlane Nitro now?

The simple answer is that Rocketlane now fits a bigger enterprise story than customer onboarding software. Atlassian is already a customer and uses Rocketlane internally for AI-driven professional services delivery, which makes this strategic investment more interesting than a normal venture check. It suggests Rocketlane has crossed into software that large platform companies see as useful for themselves, not just for smaller SaaS teams.

Timing matters too. The investment comes right after Rocketlane launched Nitro and only a few months after the Series C, so this doesn’t look like a company scrambling for cash. It looks like a company trying to speed up a category shift — from project management for services teams to execution software that automates chunks of the work. Rocketlane has been blunt about that ambition, and Ganesan’s line gets right to it: “The teams that will win are the ones willing to rethink delivery from scratch.”

For customers, the appeal is pretty practical. If Nitro can reliably handle documentation and migration work, services teams get to spend more time on design choices and customer outcomes instead of project hygiene. Admin cleanup and early risk detection are part of that pitch too. This category has seen plenty of promises before.

Why are investors betting on professional services automation?

Because the market is no longer tiny, and the workflow is no longer optional. Grand View Research expects the global professional services automation software market to reach $40.25 billion by 2033, growing at a 14.7% CAGR from 2025 to 2033. North America held a 42.1% revenue share in 2024, while Asia-Pacific is projected to grow fastest at 16.8%. That’s a pretty good setup for a company with roots in India and expansion underway in the US and UK.

AI has changed the timing. Insight argues that more than half of its 550-plus portfolio companies expanded customer success teams over the past year, while the share of teams dedicated to customer success and professional services has kept rising since 2022. It also notes that 42% of SaaS companies now charge for implementations, and points to a sharp jump in forward-deployed engineer hiring during 2025. That tells you the market isn’t just buying software anymore. It’s buying help getting software, and now AI, into production.

What should buyers watch after the Rocketlane Nitro deal?

Rocketlane Nitro now has money, momentum, and a strategic backer with serious enterprise credibility. But the test isn’t the press release. It’s whether these AI agents keep saving time once projects get ugly — strange customer data, long approval chains, scope creep, and the kind of implementation weirdness that never shows up in a demo.

Watch 2 things next. First, whether the Atlassian relationship turns into deeper product or distribution leverage. Second, whether Rocketlane can turn fast growth into durable category leadership against GuideCX on one side and bigger PSA suites like Kantata and Certinia on the other.

Read how Mowito raised a $3M pre-seed led by Version One Ventures to build physical AI software that helps industrial robot arms learn factory tasks through human demonstrations instead of manual programming.

FAQ

• What funding did Rocketlane announce? Rocketlane announced a strategic investment from Atlassian Ventures on July 7, 2026, and it didn’t disclose the size of that check. The deal came only months after Rocketlane’s $60 million Series C in March 2026, which brought total funding to $105 million.
• How does Rocketlane Nitro work? Rocketlane Nitro is an AI execution layer inside Rocketlane’s PSA platform. It can turn SOWs and handoff material into project plans, generate documentation, surface risk signals, assist with resource decisions, and automate work like migrations, validations, and configuration tasks across the delivery lifecycle.
• Who founded Rocketlane? Rocketlane was founded in 2020 by Srikrishnan Ganesan, Vignesh Girishankar, and Deepak Bala, all of whom previously worked together at Freshworks after selling Konotor to the company in 2015. Their background matters because they’d already built one SaaS product through acquisition and then scaled Freshchat before starting Rocketlane.
• Is Rocketlane part of the professional services automation market? Yes — Rocketlane sits squarely in the professional services automation market, though it also overlaps with onboarding, project delivery, and client collaboration software. Grand View Research forecasts the PSA software market will reach $40.25 billion by 2033, which helps explain why investors are backing companies that can modernize implementation work with AI.

Mowito’s physical AI helps standard industrial robot arms learn new factory tasks by observing people instead of relying on manual programming. The Bengaluru startup has raised a $3 million pre-seed round (₹28.6 crore) led by Version One Ventures, with participation from All In Capital, Unisol, and iSeed. The company aims to reduce the time and cost factories spend on rigid setups and custom programming for inspection and assembly tasks. It also takes too much specialist labor. Founded in 2024 by Puru Rastogi and Adityanag Nagesh, Mowito is building AI software for manufacturing lines in India and the US.

What does Mowito physical AI actually do?

At the center of the product is NeuralPick, Mowito’s software stack for industrial robot arms. Customers configure the application through a web interface and upload site-specific data. The model then learns the parts and conditions on that manufacturing line. Then it deploys the robot with ongoing cloud updates instead of starting another long programming cycle from scratch. It’s built to run on standard robot arms, not custom hardware that forces a buyer to rebuild the whole cell.

And the details matter here. NeuralPick combines computer vision and force sensing. This lets robot arms see, feel, and handle parts without relying on fixed jigs or rigid fixtures. The company pitches rapid line reconfiguration and browser-based training. It also promises operator-friendly controls instead of a setup that only an outside robotics integrator can maintain. Mowito says its system can achieve ±200 micron accuracy for inspection and assembly. It also adapts to moving conveyors, making it more practical than generic AI factory solutions.

The use cases are concrete, not theoretical. In one automotive case study, Mowito says a robot with one arm-mounted camera replaced eight fixed cameras and reduced inspection costs by more than 60%. It checks for defects, missing parts, and dimensional errors across multiple product variants. In another case study, Mowito says its software helped a partner achieve sub-100 micron accuracy on a live smartphone assembly line in India.

That gives you the “before versus after” pretty fast. Before Mowito, a factory might need multiple camera stations and rigid part presentation. It might also need manual recoding every time a component changed. After Mowito, factories can use one adaptable robot cell to inspect, assemble, tend machines, and handle wires or connectors with less custom rework. It’s still hard robotics. But it’s a cleaner software pitch than most automation vendors manage.

Who built Mowito physical AI and what’s the early traction?

Mowito was founded in 2024 by Puru Rastogi and Adityanag Nagesh, and it now operates across Bengaluru and Detroit. The company’s thesis is that industrial robots should be taught on the floor by operators and demonstrations, not treated like brittle systems that need months of specialist integration every time the job changes. That’s why its early focus has landed in automotive and electronics manufacturing, where even tiny variations in parts or positioning can wreck throughput.

Why Puru Rastogi fits the technical side

Rastogi’s background is about as robotics-native as you’d want for this kind of company. His public profiles link him to Carnegie Mellon University’s robotics program, the Robotics Institute, and Near Earth Autonomy, where he worked on motion planning, mapping, and localization for aerial systems. He’s also been linked to CleanRobotics and the TrashBot project. This experience shows he has built robots for real-world environments, not just controlled demonstrations.

Where Adityanag Nagesh brings edge

Nagesh looks like the more commercial cofounder. His public profiles and company records link him to Insieve Technologies and Sensara Technologies. His LinkedIn profile also highlights his robotics and manufacturing background at Mowito. That mix matters because startups like this don’t fail only on tech. They fail when nobody can translate the tech into a buying decision inside a real factory.

What traction is visible already

The startup isn’t selling a science project. Mowito says its robots are already running on manufacturing lines at a Fortune 500 automotive company and at one of the world’s largest electronics contract manufacturers. It also says it supports customers from Bengaluru and Detroit. That’s a smart split: India gives it engineering depth and a growing manufacturing base, while Detroit puts it close to US auto buyers and suppliers that actually spend on automation.

How the Mowito funding round came together

The new Mowito funding round is a $3 million pre-seed led by Version One Ventures, with participation from All In Capital, Unisol, and iSeed. Angel backers include Thinking Machines Lab CTO Soumith Chintala, Foundry Robotics founder and CEO Adarsh Kulkarni, Coformer.ai cofounder and CEO Ashish Kulkarni, and Better Capital founder and CEO Vaibhav Domkundwar. The money is earmarked for a US expansion, engineering and go-to-market hiring, broader deployments across automotive and electronics manufacturers, and continued development of the physical AI platform.

Where Mowito sits against rivals and old-school alternatives

Mowito isn’t entering an empty category. The legacy alternative is still the same old mix of fixed camera inspection and rigid fixtures. It also includes system integrators and robot programming that can take weeks or months to modify for each new part family. The newer overlap comes from several directions at once: Wandelbots made its name by letting non-programmers teach robots new tasks, Vention sells code-free cloud programming and digital-twin deployment, Standard Bots pushes AI-native industrial robot arms with real-time recording, and Mujin offers a no-code robotics platform that works across brands. Mowito’s differentiation is tighter and more specific: it wants standard industrial arms to learn from operator demonstrations, then adapt on the line with vision and force feedback for inspection, assembly, and machine tending rather than selling a whole replacement robot stack.

Why Mowito’s physical AI round matters now

A $3 million pre-seed round doesn’t sound huge in a market that loves giant robotics headlines. But for this kind of company, it’s enough to matter. Mowito already has live industrial proof points, so this round is less about inventing the category and more about proving it can repeat deployments, ship reliably, and shorten the sales cycle in the US. That’s a different problem. And it’s the one that separates interesting robotics startups from actual businesses.

The use of funds tells you what investors think the bottleneck is. Mowito isn’t talking about building flashy new humanoids. It’s putting money into US expansion and engineering depth. It’s also hiring for go-to-market roles and funding more rollouts inside automotive and electronics factories. That suggests Version One and the angel group are backing a practical thesis: there’s room for a software layer that makes existing robot arms more useful before factories go shopping for entirely new machines.

Rastogi summed up the pitch neatly: “We believe robots should learn the same way people do: by observing and repeating. This funding allows us to accelerate that vision, expand globally, and bring Physical AI to more manufacturing environments.”

How big is the industrial robotics market Mowito is chasing?

It’s big enough that even a narrow slice could build a serious company. Grand View Research estimates the global industrial robotics market was worth about $33.96 billion in 2024 and projects it will reach roughly $60.56 billion by 2030. The International Federation of Robotics has also said more than 4 million robots are now operating in factories worldwide, with annual installations above 541,000 units in 2023 — the second-highest level on record.

Why now? Because the enabling stack is finally catching up. Deloitte’s 2026 outlook points to better compute and newer robot AI models such as vision-language-action systems and world models. It also points to heavier investment from large tech and robotics players as the forces likely to accelerate adoption through 2030. That doesn’t mean factories suddenly want “AI” as a slogan. It means buyers are more willing to pay for robots that can handle variation without a fresh integration project every quarter.

Final take on Mowito physical AI

Mowito physical AI is interesting because it’s chasing a boring problem in the best possible way. No grand robot mythology. Just a hard claim that existing industrial arms should be easier to train, faster to redeploy, and less painful to own.

If Mowito can turn those first automotive and electronics wins into repeatable US deployments, it won’t just look like another robotics startup from Bengaluru. It’ll look like a credible factory software company with hardware-level consequences.

Read how Norm AI raised a $120M Series C led by Khosla Ventures to build AI-native legal and compliance systems that combine agentic AI with attorney oversight through its affiliated law firm.

FAQ

• What funding did Mowito raise? Mowito raised $3 million in a pre-seed round, which the source article values at about ₹28.6 crore. Version One Ventures led the round, and the cap table also includes All In Capital, Unisol, iSeed, and angel investors such as Soumith Chintala and Vaibhav Domkundwar.
• How does Mowito’s physical AI work on industrial robot arms? It works by letting factories configure a job in a browser and train the model on site-specific data. Then they deploy it on standard robot arms with ongoing software updates. Mowito’s NeuralPick stack combines vision with force sensing so the robot can inspect, assemble, and handle parts with less dependence on jigs, rigid fixtures, or manual recoding.
• Who are the founders of Mowito? Mowito was founded in 2024 by Puru Rastogi and Adityanag Nagesh. Rastogi brings a deep robotics background shaped by Carnegie Mellon and Near Earth Autonomy, while Nagesh adds company-building experience and a business-side view of how industrial automation gets sold and deployed.
• Is Mowito a manufacturing robotics company or a warehouse robotics startup? Right now, it’s best described as a manufacturing robotics and physical AI startup. Its visible traction and case studies are in automotive and electronics production, especially inspection, precision assembly, and machine tending, even though some older profile pages around the company also reference warehouse automation roots.

Norm AI builds legal and compliance AI systems — plus an affiliated AI-native law firm — and it just raised $120 million in Series C funding to push that model deeper into enterprise legal work. Big companies have wanted faster legal output for years, but the old choices were basically the same two headaches: expensive hourly firms or internal teams buried under review work. Founded in July 2023 by John Nay, the New York company is betting that legal services should look a lot more like software operations than traditional law firm staffing.

What is Norm AI and how does it work?

Norm AI sells what it calls “agentic law” — software that embeds legal rules, policies, and regulatory standards into AI agents so companies can run high-stakes workflows with more structure than a generic chatbot gives them. Its affiliated firm, Norm Law, then uses those same systems to deliver outside counsel work, with AI agents doing the first pass. Human attorneys step in for supervision, judgment, refinement, and negotiation.

Here’s the practical workflow. A client’s standards — statutes, regulations, internal policies, legal workflows, precedent, and risk posture — get encoded into the system through Norm’s Legal Engineering process and its LEAP platform. That gives the AI something closer to an operating manual than an open-ended prompt. In legal work, “close enough” usually isn’t close enough.

The product doesn’t stop at drafting or review. Norm is also building supervisory AI, a verification layer for other AI agents working under legal constraints. So the pitch isn’t only “let our AI do legal tasks.” It’s also “let our AI check whether other AI systems are acting in ways the law allows.”

For customers, that changes the experience a lot. Instead of handing work to a billable-hour team and waiting for rounds of review, they get an AI-first workflow tuned to their own standards. Then comes attorney oversight where it actually matters. And because Norm Law prices on outcomes rather than hours, the company is trying to flip the usual incentive stack on its head.

Who founded Norm and why did they build it?

Founding story

John Nay founded the company in July 2023 after years spent working on the overlap between AI, legal theory, and regulatory reasoning. The research foundation goes back to 2016 through 2022, and by 2024 Norm had formalized “Legal Engineering” as its own discipline — a way for lawyers to translate legal judgment directly into AI systems.

That origin story matters because Norm didn’t start as a generic AI wrapper looking for a vertical. It started from a narrower question: can legal standards be turned into structured machine behavior without losing the judgment layer that makes law usable? That’s a much more ambitious problem. It’s also a more defensible one if the company gets it right.

Why John Nay fits this market

Nay’s background gives him more credibility here than the average AI founder pitching “law, but faster.” He has been affiliated with Stanford’s CodeX center for legal informatics, served as a visiting scholar focused on AI and law at Vanderbilt Law School, and published research on aligning AI with human legal standards and on legal reasoning capabilities in large language models.

That academic path shows up in the product design. Norm isn’t just automating text generation. It’s trying to make legal judgment legible enough for AI systems to use. Then it has to make that judgment legible enough for lawyers to supervise. That’s a subtle distinction, but it’s the whole company.

Early traction

By November 2025, Norm had built a team of more than 35 lawyers trained as Legal Engineers, and its client base represented more than $30 trillion in assets under management. Norm Law launched that same month with an initial focus on financial services clients, and in January 2026 former Sidley Austin executive committee chair Mike Schmidtberger joined as chairman and partner.

That’s a serious signal. Not because headcount is everything — it isn’t — but because regulated institutions usually don’t buy legal AI on vibes. They buy when they think the workflow, supervision, and accountability model won’t blow up on them later.

How did Norm AI raise $120M and who are its rivals?

On July 7, 2026, Norm closed a $120 million Series C led by Khosla Ventures at a $1.2 billion valuation. Participants included Bain Capital Ventures, Craft Ventures, Coatue, Vanguard, New York Life, TIAA, Tony James, Jeff Hammes, Fenwick LLP, and Blackstone. The company has now raised more than $260 million in total.

This round sits on top of an unusually fast capital ramp. Norm’s timeline shows a $48 million raise in January 2025 from investors including Vanguard, Blackstone, Bain Capital, Citi, TIAA, and Coatue. That was followed by an additional $50 million Blackstone investment in November 2025 tied to the launch of Norm Law.

The obvious direct rivals are Harvey and Legora, two of the best-funded names in legal AI. Harvey confirmed a $160 million round at an $8 billion valuation in December 2025. Legora hit a $5.6 billion valuation in April 2026.

Norm’s bet is a little different. Harvey and Legora are mainly known as legal AI software platforms for lawyers and legal teams. Norm is trying to own both the tooling layer and the service-delivery layer through Norm Law. It’s also pushing into supervisory agents for AI operating in regulated settings. The legacy alternative it’s attacking is still premium law firms billing by the hour.

Why does this Norm AI round matter?

The fresh capital is earmarked for product development, more attorney hiring, broader practice-area coverage, and more work on supervisory agents for enterprise AI deployments. This isn’t just a marketing round. It’s a capacity round. Norm is trying to add legal depth and technical depth at the same time.

And that’s the hard part in this market. Lots of legal AI companies can demo drafting. Fewer can persuade major institutions to trust AI in live matters, then wrap that trust into an outside-counsel model with senior lawyers on top. Khosla’s stated thesis was basically that Norm has a credible path to AI-native legal work at institutional scale. That’s a much stronger claim than “this saves time on memos.”

There’s also a second layer here. Because Norm already serves in-house teams and runs an affiliated law firm, every new workflow can feed both product improvement and service delivery. If that loop works, the company won’t just be another legal copilot vendor. It could become part software company, part legal infrastructure provider for AI-heavy enterprises.

How big is the legal AI market?

The broader legal technology market is already large and still expanding. Grand View Research pegs it at $28.7 billion in 2025 and projects it to reach $69.7 billion by 2033, with North America holding a 49.0% revenue share in 2025.

The narrower legal AI segment is smaller, but it’s growing faster. Grand View’s legal AI outlook estimates a $1.445 billion market in 2024, rising to $3.918 billion by 2030 at a 17.3% CAGR. Solution software made up 92.17% of revenue in 2024. The big use cases include contract management and legal research. Compliance and regulatory monitoring are in the mix too, along with document drafting and review, and analytics.

That tracks with what buyers actually want now. Not magic. Not robot lawyers. They want reliable systems that can cut review time, apply policy consistently, and create an audit trail when the work touches regulation. That’s why companies like Norm are getting funded even in a crowded market — the budget isn’t really for novelty. It’s for trust and control.

Norm AI isn’t chasing a small workflow tweak. It’s trying to rebuild how premium legal work gets produced, supervised, and priced. The next real test won’t be another headline round — it’ll be whether more institutions let this model spread across additional practice areas and higher-stakes matters.

Read how Even Realities raised a $150M pre-Series B led by Meituan at a $1B valuation to build display-first smart glasses that deliver hands-free information through a subtle heads-up display without using a camera.

FAQ

• What did Norm raise in its latest funding round? Norm raised $120 million in a Series C round announced on July 7, 2026, and the deal valued the company at $1.2 billion. Khosla Ventures led the financing, and Norm said its total funding now tops $260 million.
• How does Norm Law actually work? Norm Law runs on Norm’s AI platform, with AI agents handling the first pass of legal work based on precedent, positions, and risk posture. Attorneys supervise, refine, and negotiate. The firm’s model is unusual because it charges on outcomes instead of hourly billing, which is a direct break from how most large law firms still price their work.
• Who is John Nay and why is he relevant here? John Nay is Norm’s founder and CEO, and his background is unusually tied to the exact problem the startup is tackling. He has worked with Stanford’s CodeX and Vanderbilt Law on AI-and-law research, and his published work has focused on translating legal standards into forms AI systems can reason with.
• Is Norm a legal tech company or a law firm? It’s both, and that’s the whole point of the model. Norm sells legal and compliance AI to enterprise clients, while Norm Law delivers AI-native outside counsel services on top of that stack, starting with financial services and other institutional work.

Even Realities builds display-first smart glasses that project useful information into your line of sight without putting a camera on your face. The startup has now raised $150 million in a pre-Series B led by Meituan, with Tencent returning, at a $1 billion valuation. That matters because a lot of smart-glasses companies are chasing content capture and AI assistants, while many professionals still want something quieter—something that helps in meetings, travel, and daily work without making every interaction feel recorded. Founder and CEO Will Wang, a former Apple engineer who worked on Apple Watch and iPhone programs, started the Shenzhen-headquartered company in 2023 with other ex-Apple engineers and co-founders from tech and luxury eyewear, including Lindberg.

What do Even Realities smart glasses actually do?

Here’s the simple version: Even G2 is a pair of prescription-friendly smart glasses with a built-in heads-up display. You pair the glasses to the Even app, choose what you want surfaced, then interact through touch controls on the frame, voice, or the optional Even R1 smart ring. The display appears only when needed. The glasses are trying to behave more like normal eyewear than like a tiny headset.

The hardware is more serious than the minimalist look suggests. Even G2 uses a dual micro-LED setup—one display per lens—with waveguide optics and touchpads on both temples. It also has a four-microphone array, BLE 5.4 connectivity, up to 2 days of battery life, and an IP65 dust-and-water rating. Even supports prescriptions from -12.00 to +12.00, which is a bigger deal than it sounds in eyewear, because prescription support is where lots of “cool demo” wearables get messy fast.

What do you actually get on screen? The core software stack is built around quick-glance utilities. Conversate shows prep notes and surfaces AI cues when unfamiliar names or references come up. It sends an AI summary to the phone afterward. Teleprompt keeps scripts or imported text in view. Translate and transcribe are part of the pitch too. So are navigation, notifications, dashboards, and voice commands through “Hey, Even.” Even’s AI layer is powered by its own EvenLLM, and its developer docs show the company already wants third parties building plugins, widgets, dashboards, and AI skills for the G2.

Before, you’d glance at your phone, fumble for notes, or quietly search something mid-conversation. With Even’s setup, the company is trying to move those little interruptions into the background. It’s a modest ambition compared with full AR. But it’s also a lot easier to explain why someone might wear it all day.

Who built Even Realities smart glasses and why?

From Apple hardware to eyewear

Even Realities was founded in 2023 by ex-Apple engineers, and Wang is the clearest public face of the team. He worked on Apple Watch and iPhone programs before starting Even, while other co-founders came from mainstream tech and luxury eyewear, including Lindberg. That mix matters. Smart glasses aren’t just a software problem or just a fashion problem. If the optics are bad, nobody cares. If the frames look awkward, nobody wears them.

The company moved fast. It shipped Even G1 in 2024, which Wang described as the lightest waveguide smart glasses on the market at the time. Then it followed with Even G2 in November 2025, dropping the camera entirely and focusing on a heads-up display plus the optional R1 ring for control. The whole thesis is pretty blunt: build “display-first” glasses for people who want information, not a wearable content machine.

Why the founders have real market fit

Wang’s background helps explain the product choices. Apple experience tends to push teams toward integration, comfort, supply-chain discipline, and boring-but-critical details like fit, power, and component packaging. Even’s optical story follows that logic. Wang says the company has invested most heavily in optics. Its proprietary Even HAO system—short for Holistic Adaptive Optics—ties together the microchip, waveguide, and prescription support from the start instead of treating them as separate modules.

The privacy angle follows from that. Wang calls smart glasses “the most personal computing device people will ever wear,” and Even designed around that idea in both hardware and software. Translation features transcribe speech into text rather than storing audio recordings. User data is encrypted. The infrastructure is built to meet Europe’s stricter privacy expectations. That doesn’t solve every concern. But it’s a much cleaner answer than “trust us, the camera’s fine.”

The early traction is stronger than you’d expect

Even isn’t coming to market as a lab project. Wang says the company beat its own 10,000-unit goal and became the first in its category to sell more than 10,000 pairs. Headcount jumped from about 30 to 40 people in 2024 to roughly 300 to 400 today. More than half of users are in the U.S.—its fastest-growing market—and the bulk of its developer community is there too, even though the company manufactures in China and still doesn’t sell domestically in China. Its main markets today are the U.S., Japan, South Korea, the Middle East, and Europe.

The customer base is unusually specific. Wang says most buyers are male professionals aged 30 to 50, and about a third are company executives. The frames start at $599 before tax, while prescription lenses or the R1 ring add another $200 to $300, putting the average order around $1,000. Even is already profitable at that premium end of the category. That’s not mass-market pricing. It is, though, a useful signal that this audience is paying for utility instead of novelty.

Funding and how Even compares with Meta and Snap

The new round brings in $150 million at a $1 billion valuation. Meituan led the pre-Series B, Tencent came back in, and earlier backers include HSG, the firm formerly known as Sequoia China. For a 3-year-old hardware startup, that’s a very loud vote of confidence.

Competition is where the strategy gets clearer. Meta’s recent glasses push centers on camera-equipped AI eyewear: Ray-Ban Meta has sold millions. Oakley Meta adds a 3K camera and sports focus, and the June 23, 2026 Meta Glasses launch starts at $299. Snap’s new SPECS, unveiled on June 16, 2026, go the other way—full augmented-reality glasses with a 51-degree field of view, two Snapdragon processors, and a $2,195 preorder price. Even sits in the middle. It offers a real display and prescription support, but skips the camera and the heavier AR pitch. It’s trying to feel like everyday eyewear instead of a gadget first.

Why does this Even Realities smart glasses round matter?

This round matters because smart-glasses hardware is brutally expensive in all the unsexy places—optics, display integration, custom prescription work, manufacturing yield, miniaturization, and software that doesn’t feel half-baked. Even isn’t raising to prove it can build one nice prototype. It has already shipped 2 generations and built a developer layer. It’s also found a paying professional audience. The money gives it room to keep pushing the hardest part of the product, which is exactly where Wang says the company has concentrated its effort: optical performance.

It also says something about investor appetite. Meituan and Tencent aren’t backing a cheap accessory story here. They’re backing the idea that there’s a real market for smart eyewear that behaves more like a discreet second screen than like a social-media camera. If Even can hold onto its U.S. growth, keep margins intact, and expand its software usefulness without breaking its privacy promise, this funding starts to look less like a speculative hardware bet and more like an early claim on a very specific kind of wearable computing.

How big is the smart glasses market in 2026?

Pretty big already, and still early. Grand View Research expects the global smart-glasses market to reach $14.38 billion by 2033, growing at a 24.2% CAGR from 2026 to 2033. North America held more than 34.4% of the market in 2025, and the U.S. market alone was valued at $793.9 million in 2025 with a path to $3.72 billion by 2033.

The timing makes sense. In June 2026, Snap unveiled public-market SPECS, and Meta introduced a fresh Meta Glasses line after already selling millions of Ray-Ban Meta units and expanding the Oakley Meta family. That tells you the category is splitting into submarkets: camera-first AI glasses, fuller AR computers, and quieter display-first wearables like Even. That split is healthy. It means the market is finally getting specific about what glasses are actually for.

Can Even Realities smart glasses win on privacy?

Maybe.

Even Realities smart glasses aren’t trying to turn everyone into a creator or a livestreamer. They’re trying to become the eyewear version of a low-friction second screen for work, travel, and conversation. If the company can keep its optics ahead of the pack while the giants crowd in, the next thing to watch isn’t just sales. It’s whether users keep choosing camera-free utility over flashier AI glasses.

Read how Next Bharat Ventures launched a ₹2,000 crore Fund-2 to back rural Indian startups with patient capital, hands-on founder support, and a long-term strategy focused on profitable businesses serving the country’s next billion consumers.

FAQ

• What funding did Even Realities raise?
  Even Realities raised $150 million in a pre-Series B round at a $1 billion valuation. Meituan led the deal, Tencent participated again, and HSG is among the earlier backers. The round stands out because Even is only 3 years old and is already selling hardware at premium prices rather than chasing a low-cost rollout.
• How do Even Realities smart glasses work?
  Even G2 works like a heads-up display built into everyday glasses. Users pair the glasses with a phone app, then control features through touchpads on the frame, voice commands, or the optional Even R1 ring. The software centers on glanceable tools like live translation, teleprompting, navigation, notifications, and Conversate, which can surface context and send conversation summaries to the phone.
• Who founded Even Realities?
  Will Wang founded Even Realities in 2023 with other ex-Apple engineers and teammates from tech and luxury eyewear. Wang previously worked on Apple Watch and iPhone programs, while 2 co-founders came from eyewear companies including Lindberg. That mix of consumer electronics and premium frame expertise is a big part of why Even has focused so heavily on optics, prescription support, and wearability.
• Is Even Realities an AR glasses company or an AI glasses company?
  It’s closer to a display-first smart-glasses company than a pure AR headset maker. Even G2 has AI features, but its pitch is lighter and more practical than Snap’s standalone AR SPECS and more privacy-focused than Meta’s camera-equipped AI glasses. Think discreet information overlays and daily utility, not immersive spatial computing.

Next Bharat Ventures is a Suzuki-owned impact investment firm that backs Indian startups serving rural and informal-economy customers. The firm has launched a second fund with a ₹2,000 crore corpus, significantly larger than its first fund. The move reflects growing interest in corporate-backed rural impact investing in India. Many startups serving non-metro India still struggle to access patient early-stage capital. Founded in 2024 and led by CEO Vipul Nath Jindal, the firm backs profitable businesses focused on local livelihoods and long-term impact.

What does Next Bharat Ventures actually do?

At a practical level, Next Bharat Ventures runs a hybrid model. It invests directly in early and growth-stage startups that already have product-market fit and revenue. It also runs founder programs that help companies get investment-ready before a cheque is written. Fund-2 will invest in rural healthcare, mobility, financial services, agritech, and cleantech. It will also back retail tech, productivity tools, micro-entrepreneur enablement, livelihood creation, and AI for social impact.

For a founder, the funnel is more hands-on than a standard VC pitch process. The residency flow includes application review and multiple interview rounds. It also includes on-site field visits and final selection. Selected companies receive equity funding. The in-person part of the program runs out of Bengaluru and is paired with mentorship, founder community, and exposure to a wider operating network.

The support layer is the interesting bit. Next Bharat isn’t just writing cheques and waiting for quarterly updates. Its programs promise market-access help through Suzuki and other partners in India and Japan. The broader platform also includes exchanges, fellowships, and corporate collaboration programs. That explains why some portfolio startups are already piloting in Japan instead of staying boxed into a purely domestic startup narrative.

Fund-2 adds another wrinkle: half the corpus is set aside for a fund-of-funds strategy. So alongside direct startup bets, Next Bharat will act as an LP in other high-performing VC firms, much like it already did through relationships with firms such as 3one4 Capital, Sparrow Capital, and Northpoint. That’s a pretty blunt admission that impact investing needs portfolio construction discipline, not just good intentions.

Who founded Next Bharat Ventures and how is it different?

The founding story

Next Bharat Ventures was launched in 2024 as a wholly owned subsidiary of Suzuki Motor Corporation, with offices in GIFT City, Bengaluru, and Hyderabad. Jindal’s pitch is that India’s “next billion” consumers and workers sit in rural and informal markets that most mainstream VC firms still underwrite badly or ignore altogether. He’s been explicit about the thesis: back founders “creating quality of life in India’s rural informal economy” because that’s where the next leg of growth will come from.

Why Vipul Nath Jindal fits this brief

Jindal isn’t coming at this as a tourist investor. Forbes identified him in 2025 as a former Suzuki Motor executive who launched Next Bharat Ventures to invest in Indian social enterprises, and recent coverage around Fund-2 describes him as an IIT Hyderabad alumnus. That mix matters. He understands the Japanese parent, but he’s also selling a very India-specific thesis around local economies, not imported Silicon Valley templates.

Traction and early signals

The first fund, launched in 2024 with a corpus of ₹340 crore, has already become more than a pilot effort. Next Bharat has made 20 investments so far, including E-bik, MeMeraki, and Atypical Advantage, and Jindal has said 80% of startups from the first fund are already EBITDA positive. Separate reporting on the platform says it has supported more than 50 impact startups overall through capital, mentorship, and ecosystem support. Several portfolio companies are already testing business pilots in Japan.

The portfolio gives a clearer sense of how broad the firm wants to be. Atypical Advantage works on employment and income generation for people with disabilities. MeMeraki connects traditional artists with customers through contemporary commerce. KrishiVan is building a digital agriculture platform around machinery, services, and marketplace access. It’s not a narrow agritech fund. It’s a wider bet on livelihoods and local productivity.

Fundraising details

Fund-2 is structured for a longer game. The new vehicle has a 15-year life. It will start investing in the coming month and is expected to make 10-12 deals a year over the next 4 years. Next Bharat says average ticket sizes will move up to about $500,000 to $1 million, well above the ₹1 crore to ₹5 crore range it used from Fund-1. It will also reserve capital for follow-ons into existing portfolio companies across both funds. Suzuki separately said on July 1, 2026 that it would invest $200 million into NBV Fund-2, after putting $40 million into the first fund in July 2024.

How does it compare with Aavishkaar and Omnivore?

This is where Next Bharat gets more interesting. Aavishkaar Capital has been doing overlooked-sector investing since 2001, has closed 8 funds, manages close to $500 million, and writes much larger $5 million to $25 million cheques into financial inclusion, food and agriculture, and essential services. Omnivore, by contrast, is a specialist agritech and rural-economy investor whose third fund targeted $130 million with a heavier emphasis on food systems, climate resilience, and farmer outcomes.

Next Bharat sits in a different pocket. It’s earlier and more operational. It’s also more corporate-backed and broader than a pure agritech fund. It also has a built-in Japan bridge and a fund-of-funds sleeve, which most rural-impact investors don’t pair in the same vehicle. Legacy alternatives for a founder in this market are usually fragmented angel money, grant capital, or mainstream VCs that still prefer urban SaaS, fintech, or consumer internet stories. That gap is what Suzuki is trying to monetize.

Why does the ₹2,000 crore Next Bharat Ventures fund matter?

The obvious answer is scale. But the more important answer is check size and intent.

Fund-1 proved there was room for a rural-first impact platform. Fund-2 says Next Bharat now wants to finance companies after the experiment stage, once they’re already generating revenue and need bigger growth capital. That shift matters because plenty of impact startups don’t die from lack of ideas. They die in the ugly middle — after early validation, before institutional scale capital shows up.

It also matters for Suzuki. In its own words, the company said it has direct links to only about 400 million people in India out of a population of roughly 1.4 billion, and sees Next Bharat as a route to connect with “the next billion” beyond mobility. So this isn’t charity in corporate-VC clothing. It’s a long-duration market access strategy dressed as impact capital.

Then there’s the exit logic. Jindal expects exits through SME IPOs once companies build durable revenue bases, rather than forcing them toward vanity valuations or rushed M&A. If that works, Next Bharat Ventures could end up backing a class of Indian startups that look boring by venture standards but very good by cash-flow standards.

How big is India’s impact investing market?

The category Next Bharat is betting on isn’t tiny anymore. IMARC estimated the India impact investing market at about $3.02 billion in 2025 and projects it could reach roughly $22.5 billion by 2034, implying a 24.25% CAGR. That’s a fast-growing pool of capital, even if the segment still feels underbuilt compared with mainstream venture.

The broader VC backdrop has improved too. Bain-IVCA coverage showed India-focused VC fundraising rebounded to about $5.4 billion in 2025 from $2.7 billion in 2024, with larger fund closes helping reset the mood after the post-2021 slowdown. Put those 2 numbers together and the timing makes sense. More venture money is returning, but specialist theses are getting sharper. Rural livelihoods, agritech, financial inclusion, and local productivity are no longer side bets. They’re becoming investable verticals with their own fund managers and playbooks.

Conclusion

Next Bharat Ventures is trying to prove that rural India doesn’t need a handful of unicorns nearly as much as it needs hundreds of profitable, durable businesses.

That’s an ambitious claim. But it’s grounded in a clear structure: bigger cheques, patient capital, Japan access, and a willingness to back companies that serve markets most VCs still misunderstand. The next thing to watch isn’t the headline corpus. It’s whether Fund-2 can turn that thesis into repeatable exits through SME listings and disciplined follow-on rounds.

Read how BCT Ventures raised ₹42 crore in seed funding from 3one4 Capital to build AI-native nutrition and wellness brands by partnering with trusted practitioners and turning their expertise into protocol-first consumer health products.

FAQ

• What is Next Bharat Ventures Fund-2? It’s a new ₹2,000 crore impact fund launched by Suzuki-owned Next Bharat Ventures in July 2026 to back Indian startups serving rural and informal-economy markets. The vehicle is designed for a 15-year life and is expected to invest across sectors such as healthcare, mobility, financial services, agritech, cleantech, retail tech, and AI for social good.
• How does Next Bharat Ventures work for startups? It works as both an investor and an operating platform. Startups can come through a residency process that includes applications and interviews. It also includes field visits and final selection, after which selected companies receive equity funding plus mentorship, founder community support, and possible access to Suzuki-linked networks in India and Japan.
• Who is Vipul Nath Jindal? Vipul Nath Jindal is the founder and CEO of Next Bharat Ventures, which he launched in 2024 as Suzuki’s India impact-investing arm. He’s a former Suzuki Motor executive, was featured on Forbes’ 30 Under 30 Asia 2025 list in finance and venture capital, and recent coverage identifies him as an IIT Hyderabad alumnus.
• Is rural impact investing in India becoming a bigger category? Yes, and the numbers back that up. IMARC put India’s impact investing market at about $3.02 billion in 2025 with projections of $22.5 billion by 2034, while Bain-IVCA coverage showed total India-focused VC fundraising rebounding to $5.4 billion in 2025. That doesn’t mean every rural startup thesis works, but it does mean specialist capital is getting more institutional.

BCT Ventures is a Mumbai-based consumer brands platform that uses AI-native operations to build nutrition and wellness brands from practitioner expertise. It has launched with ₹42 crore in seed funding from 3one4 Capital at a time when generic supplements are losing appeal among urban buyers who want more trusted, protocol-led health products. Founded in 2025 by Kashyap Vadapalli, KV Ravi Shekhar, and Anubhav Sonthalia, the company is tackling a specific gap: experts may have credibility, but very few have the machinery to turn that trust into a consumer brand.

What is BCT Ventures and how does it work?

BCT Ventures is building brands, not just software. The model starts by partnering with practitioners and medical experts. It uses owned content channels to detect demand, turns those signals into “protocol-first” products, and scales distribution through AI-led performance marketing. Its three in-house engines are Resonance for trust and attention, Nucleus for product creation, and Meridian for paid growth and optimisation.

That operating loop is more specific than the usual “AI for brands” pitch. Resonance handles topic selection, scripting, production support, distribution, and audience feedback around practitioner-led content. Nucleus then uses those engagement signals and practitioner protocols. It also uses whitespace mapping to define what should actually be formulated before manufacturing begins. Meridian picks up only after that, automating creative testing, media buying, budget allocation, attribution, and return-on-ad-spend optimisation.

For a practitioner, the workflow is straightforward. BCT first selects experts it thinks have real authority and category fit. Then it helps grow their audience. It develops products around what that audience is already asking for and launches those products under the expert’s authority. After launch, it keeps iterating through campaign data, customer behaviour, and pin-code-level targeting so each cycle sharpens the next one.

Before this kind of setup, a doctor, nutritionist, or wellness expert would need to stitch together content teams, formulators, manufacturers, paid marketing, and working capital by hand. BCT is trying to compress that into one platform. Meridian’s target is 3x better RoAS with a fraction of the team size usually needed for performance-led consumer growth. Ambitious, yes. But the claim is tied to an actual operating model.

Who founded BCT Ventures and why this team fits?

The founding story

BCT Ventures was founded in 2025, and the three co-founders have known each other for about 16 years. That matters more than it sounds. This isn’t a random founder match built around an AI trend. The company was structured around three different muscles from day one: brand and distribution, content-led audience building, and performance marketing plus commercialisation.

It is starting with nutrition and wellness because the founders see a category where trust, education, repeat buying, and premium pricing matter. Vadapalli has framed the thesis in broad tech terms, arguing that digital changed distribution, data changed decision-making, and AI will change how brands are “conceived, built, and scaled.” That isn’t just a slogan for BCT. It’s the company’s whole bet.

Why the founders have market fit

Kashyap Vadapalli brings the classic consumer-operator background. At Pepperfry, he spent about 9.5 years, including stints as CMO and Chief Business Officer, and helped scale Pepperfry’s net sales from roughly ₹20 crore to ₹600 crore. Before that, he worked across eBay, Cadbury, and Tata Interactive, giving him experience in category building, private labels, and omnichannel expansion. That’s the sort of unglamorous work consumer brands live or die on.

Ravi Shekhar’s fit is different. He worked at Doubtnut and advised founders at Vedantu and Purplle, with a strong bias toward content-native growth. He helped Doubtnut scale to about 15 lakh daily active users through a YouTube-first strategy. BCT also links him to Purplle’s rosemary water category build, which reached roughly ₹200 crore in revenue within 12 months. If BCT’s core idea is that audience trust should shape product creation, Ravi’s past work looks like the closest proof point.

Anubhav Sonthalia is the monetisation specialist in the trio. He founded performance marketing company Sokrati in 2010, scaled it to serve more than 200 brands, and later sold it to Dentsu in a deal BCT pegs at about $100 million. Post-acquisition, he led Dentsu’s performance marketing practice in India. That matters because BCT doesn’t just need to launch products. It needs to keep customer acquisition disciplined in a category that can get expensive fast.

Track record, launch status, and the seed round

There’s a pattern across the team. Vadapalli has seen brand scaling from the operating side. Shekhar has built audience systems that convert attention into demand. Sonthalia has already had a meaningful exit and then run scaled media operations inside a large network. The company’s own shorthand is blunt: one founder built a ₹600 crore consumer brand, another built audiences in the millions, and another exited at $100 million. For investors, that’s a much easier story to underwrite than a first-time founder deck.

BCT isn’t in stealth. It has publicly launched, is based in Mumbai, and is already inviting conversations with investors, practitioners, and strategic partners through a live site. It will work with a small number of practitioners at a time and be selective about who gets onboarded. That suggests the team sees expert quality as a gating factor, not an interchangeable supply pool.

On fundraising, the company has raised ₹42 crore in seed capital from 3one4 Capital. No additional investors were named in the launch announcement. 3one4’s Anand Batra said BCT is building an operating model with AI embedded across insight, product development, distribution, and growth from day one, while also pointing to the founding team’s mix of demand creation, audience scale, operational depth, and venture-building experience.

How does BCT Ventures compare with wellness brands and aggregators?

BCT sits in an unusual middle ground. On one side, there are scaled wellness brands like OZiva, which became important enough for Hindustan Unilever to fully fold into its health and wellbeing business after OZiva reached about ₹480 crore in 2025 revenue. Those companies compete for the same consumer wallet in supplements and preventive health. They are still brand-first businesses. BCT is trying to be the machinery that creates several such brands.

On the other side are India’s house-of-brands operators like Mensa Brands and GlobalBees. They typically acquire or partner with digital-first brands that already exist, then scale them with capital and operating support. BCT’s model is earlier than that. It doesn’t want to buy traction after the fact. It wants to generate the demand signal, build the product, and own the growth loop from scratch, with practitioners as the trust layer.

The legacy alternative is even less flattering. A lot of India’s supplement market is still crowded with generic SKUs, broad wellness claims, and distribution-first selling. BCT’s differentiation is practitioner authority, protocol-led formulation, and owned audiences rather than heritage branding or brute-force ad spend. That won’t make execution easier. It does make the positioning clearer.

Why are investors backing this seed round now?

This round matters because BCT isn’t launching one SKU and figuring it out later. It’s trying to build the production system before the portfolio exists. That means content operations, formulation logic, manufacturing coordination, media tooling, and partner onboarding all have to work together early. Seed capital makes that kind of front-loaded build possible.

3one4 is clearly backing the team as much as the thesis. That’s sensible. A lot of AI-commerce startups talk about automation, but BCT’s founders have already run large-scale brand, audience, and performance functions. If this works, the upside isn’t just one successful wellness label. It’s a repeatable consumer-brand creation engine that could extend into other categories where trust and education drive buying. The company has already said it plans to expand only into adjacent categories that reward those same traits.

How big is India’s nutrition and wellness market?

The timing isn’t random. Kearney estimates India’s broader health and wellness market at about $40 billion in 2024, with nutraceuticals alone valued at $8 billion and growing at 11% CAGR from 2023 to 2027. That same research projects the Indian nutraceuticals market reaching $11 billion by 2027. Functional foods and beverages make up the biggest chunk.

There’s also a wider demand tailwind behind BCT’s launch. IMARC puts India’s health and wellness market at $164.35 billion in 2025 and projects it to hit $257.94 billion by 2034. Kearney adds two numbers that explain why preventive care is getting serious attention: medical inflation in India was 14% in 2024, and 80% of the population has micronutrient deficiencies. When healthcare gets costlier and consumers start treating supplements as routine spend instead of an occasional fix, platforms like BCT stop looking quirky and start looking timely.

BCT Ventures still has a lot to prove. Building one trusted wellness brand is hard enough. Building a repeatable engine for several of them is harder. If the company can show that practitioner-led demand converts into efficient, repeat purchases, this could become one of the more interesting consumer-brand experiments to watch in India over the next 12 months.

Read how PlayBlue raised a $2.7M seed co-led by Centre Court Capital and MIXI Global to build an omnichannel sports retail platform that combines flagship stores with ecommerce for sports gear, fitness equipment, athleisure, recovery products, and nutrition across India.

FAQ

• What is the BCT Ventures funding round? BCT Ventures has raised ₹42 crore in seed funding from 3one4 Capital. The round coincides with the company’s public launch in 2025 and gives it capital to build out its AI-native consumer brand platform in nutrition and wellness.
• How does BCT Ventures work? BCT Ventures works by combining practitioner-led content, product formulation, and performance marketing inside one operating loop. It grows expert audiences through Resonance, turns those signals into products through Nucleus, and scales customer acquisition through Meridian.
• Who are the founders of BCT Ventures? BCT Ventures was founded by Kashyap Vadapalli, Ravi Shekhar, and Anubhav Sonthalia. Their backgrounds span Pepperfry, eBay, Doubtnut, Vedantu, Purplle, Sokrati, and Dentsu, which gives the company a mix of consumer brand building, audience scaling, and paid-growth experience.
• Is BCT Ventures a wellness brand or a house of brands? It’s closer to a brand-creation platform than a single wellness label or a classic roll-up. Unlike aggregators such as GlobalBees or Mensa, which scale existing brands, BCT wants to build new practitioner-led brands from scratch, starting in India’s nutrition and wellness category.

PlayBlue is a new omnichannel sports retail startup that wants to sell sports gear, athleisure, footwear, fitness equipment, recovery products, and nutrition through flagship stores and a pan-India ecommerce platform.

The PlayBlue funding round brings in $2.7 Mn, or ₹25.7 Cr, in seed capital co-led by Centre Court Capital and MIXI Global, with WEH Ventures also participating. The problem it’s chasing is clear: India has tons of sports consumers, but not enough organized places to compare brands and get credible buying advice. Nor are there enough places to shop the same way online and offline. Founded in 2025 by former GMR Sports CEO Satyam Trivedi and former Cult.fit executive Jayam Vora, the company is trying to build that missing retail layer before bigger incumbents seal the market.

That’s the pitch.

Now it has money to test whether it works.

What is PlayBlue and how does it work?

PlayBlue is building a multi-brand sports retail format for India that blends physical stores with ecommerce. A customer is supposed to discover products online, buy in-store or through the app, and get doorstep delivery. They’d still have access to human guidance instead of just scrolling endless product grids. That sounds simple. In sports retail, it usually isn’t.

The product itself isn’t just “a website plus stores.” PlayBlue will carry 100+ Indian and global brands across categories, not just one private label or one sport. The idea is that a runner, weekend cricketer, serious gym user, or school athlete can shop in one place. They won’t have to bounce between single-brand outlets, marketplaces, and neighborhood dealers with uneven stock.

Its stores are being designed as experiential spaces, with staff who’ve actually played sports and can help buyers choose the right gear rather than the most marketed gear. That expert-guided layer matters more in sports than in regular fashion retail. Shoe fit, equipment quality, recovery tools, and training accessories are all easy to get wrong.

PlayBlue is also pushing speed and community. It talks up quick-commerce style delivery for urgent purchases. Its stores will also double as offline touchpoints for local sports groups, runners, and pickup communities. So the model isn’t only about transaction volume.

It’s also about becoming a habit.

Who started PlayBlue and why now?

The founding idea

PlayBlue’s founding logic is less about retail theater and more about behavior change. Trivedi and Vora are betting that India is shifting from a country that mostly watches sport to one that increasingly plays it. Their framing is that people didn’t stop caring about sport — they just aged into jobs, bad retail experiences, and fragmented product discovery.

That’s why the company isn’t launching as a narrow D2C brand. It’s going after the broader discovery problem instead.

Why these founders fit sports retail

Satyam Trivedi comes from the institutional side of sport. Before PlayBlue, he led GMR Sports and had earlier roles at RPSG Sports and Adani Sportsline. That gives him operating experience across teams, leagues, franchises, commercial rights, and sports infrastructure — not just consumer marketing. He understands how the sports business works when money, fandom, and physical infrastructure collide.

Jayam Vora brings the consumer and fitness angle. He co-founded Fitternity, which scaled into one of India’s best-known fitness booking platforms before its 2021 acquisition by Curefit. He later worked inside the Cult.fit setup, where he was involved with Gold’s Gym India and the cultpass network of 300+ gyms. That background matters because PlayBlue isn’t selling just products.

It’s selling repeat engagement inside an active-lifestyle category.

Taken together, the pairing makes sense. One founder knows sports institutions. The other knows consumer demand, fitness distribution, and habit-driven categories.

Early rollout, traction, and the seed round

PlayBlue is still early. The platform is in launch mode, with the company launching soon and opening its first stores later this year. Its initial rollout starts with a 15,000 sq. ft. flagship in Bengaluru, with Mumbai and Delhi NCR next in line.

Centre Court Capital and MIXI Global co-led the seed round, with WEH Ventures joining. The money will go into its first flagship stores and its pan-India ecommerce launch. It has also laid out a pretty aggressive operating plan: 150 stores over the next 5 years, a community of more than 1 Cr users, and a target of reaching ₹100 Cr in revenue while aiming for operational profitability before the next fundraise.

Ambitious? Very.

For a company that hasn’t opened its first store yet, definitely.

How PlayBlue stacks up against Decathlon, Sports Station, and newer challengers

The obvious benchmark is Decathlon, which already has 100+ stores across India and huge advantages in sourcing, assortment depth, and price architecture. If PlayBlue tried to beat Decathlon head-on with a copycat format, that would be a rough fight.

So it isn’t doing that. At least not exactly.

PlayBlue is positioning itself as a multi-brand curator rather than a dominant private-label chain. That puts it closer to formats like Sports Station, which operates 40 stores across 30 cities, and to organized multi-brand sportswear retail more broadly. It also overlaps with newer operators and category builders such as Agilitas, which is expanding across manufacturing, brands, and offline retail, and with emerging labels like Heelium on the brand side.

Its real competition, though, is more fragmented than those names suggest. Single-brand stores don’t solve cross-category discovery. Generic marketplaces solve breadth but not trust. Local sports shops solve proximity but often not assortment or expertise. PlayBlue’s bet is that a shopper will pay for convenience, curation, and advice in one place.

That’s the strategic edge its investors are backing.

How the PlayBlue funding will be used

Seed money at this stage isn’t about vanity. It’s about whether the startup can turn a concept into a functioning retail machine.

For PlayBlue, that means building flagship stores that don’t feel like inventory dumps. It also means standing up ecommerce that works nationally and stitching both together so stock, service, and fulfillment don’t break the customer experience. Omnichannel sounds nice in decks. It gets messy fast once store ops, delivery speed, brand onboarding, and returns enter the picture.

The round also gives PlayBlue a window to prove something important to future investors: that organized sports retail in India can be more than a niche premium play. If it can show demand across categories and move toward profitability before the next raise, the company’s story gets a lot stronger.

There’s also Centre Court Capital’s involvement. The fund recently closed its maiden corpus at ₹410 Cr, above its original ₹350 Cr target, so this isn’t a random tourist bet on consumer buzz.

How big is India’s sports retail market?

The macro case is why this startup exists at all. A joint Google and Deloitte report projects India’s sports market will grow to $130 Bn by FY30 from $52 Bn in FY24. That’s not a small category expansion.

That’s a structural shift.

Vora has put a narrower consumer lens on it, arguing that India’s sports and active lifestyle market could cross $30 Bn by 2035 and require more than 15,000 new sports retail touchpoints. That’s the part traditional retail still hasn’t fully addressed. Demand is broadening beyond cricket fandom into running, fitness, racquet sports, school athletics, recovery, and everyday athleisure.

And timing matters. More parents are spending on sport. Fitness is now mainstream, not niche. Athleisure has blurred the line between performance and lifestyle buying. Consumers also expect the same thing they expect everywhere else: fast delivery, better selection, and less confusion.

That doesn’t guarantee PlayBlue wins.

But it does explain why investors think this category is finally worth building for real.

Final take on PlayBlue funding

The smartest thing about PlayBlue funding isn’t the round size. It’s the founder mix.

Trivedi knows the business of sport. Vora knows how to build consumer demand in fitness-led categories. If they can make expert-led, multi-brand sports retail feel normal in India — not premium, not intimidating, just useful — PlayBlue could carve out a place between giant chains and messy marketplaces. The next thing to watch is simple: whether the first stores in Bengaluru, Mumbai, and Delhi NCR actually create repeat behavior, not just launch-week curiosity.

Read how Age Care Labs raised ₹85 crore in a Series B1 round led by Shrem Group to build an end-to-end elder care platform spanning home care, assisted living, and premium senior living communities.

FAQ

• What is the latest PlayBlue funding round?
  PlayBlue has raised $2.7 Mn in seed funding, which is about ₹25.7 Cr. Centre Court Capital and MIXI Global co-led the round, with WEH Ventures also participating, and it’s meant to support store launches and the ecommerce rollout.
• How does PlayBlue work as a sports retail platform?
  PlayBlue works as an omnichannel sports retail business that combines physical stores with online discovery and delivery. It plans to sell across categories like athleisure, footwear, gear, nutrition, and recovery, while adding expert staff and faster fulfillment to make product selection less painful.
• Who founded PlayBlue?
  PlayBlue was founded in 2025 by Satyam Trivedi and Jayam Vora. Trivedi previously led GMR Sports and held senior roles at RPSG Sports and Adani Sportsline, while Vora co-founded Fitternity and later worked across Gold’s Gym India and Cult.fit’s gym network.
• What market is PlayBlue targeting in India?
  PlayBlue is targeting India’s sports and active lifestyle retail market, which sits at the intersection of sporting goods, fitness commerce, and athleisure. The wider sports market in India is projected to reach $130 Bn by FY30, which is why startups and investors are now treating sports retail as a serious consumer category rather than a side niche.

Age Care Labs runs elder care services across home-based support and assisted living. It has now raised ₹85 crore in a Series B1 round to push deeper into senior living. The company is betting that Indian families don’t just need emergency help for ageing parents — they need a full care continuum that can stretch from at-home monitoring to residential support and independent living. Founded in 2019 by Saumyajit Roy, Age Care Labs operates through Emoha and Epoch Elder Care, with Epoch led by co-founder Neha Sinha. That mix makes this round more interesting than a standard healthcare funding headline.

What does Age Care Labs do and how does it work?

At a basic level, Age Care Labs sells organised elder care in three layers. Emoha handles ageing at home. Epoch handles assisted living and higher-acuity residential care. The new Shremoha venture is meant for premium independent senior living. That means one company can now meet seniors when they’re still living on their own, when they need structured help, and when they want a purpose-built community instead of a standard apartment block.

For an Emoha customer, the workflow is specific. A care specialist assesses the senior’s health, mobility, medical history, and day-to-day needs. Then they map those needs to a plan with digital medical records, scheduled monitoring, and emergency coordination. Depending on the plan, the service can include doctor teleconsults, ambulance evacuation, lab tests, physiotherapy access, home safety assessments, medicine support, and hospital or appointment accompaniment.

What stands out is the attempt to remove a lot of invisible family labor. Emoha uses recurring check-in calls — branded in some plans as support from an “Emoha Daughter” — to keep tabs on medicines, tests, appointments, and chronic-condition management. For urban professionals living away from parents, that’s the actual product. Not just medical care, but a system that absorbs coordination work families usually do in panic mode.

Epoch is the heavier-care side of the business. It runs elder care homes for seniors who need help with activities of daily living. It offers 24×7 assisted living, dementia care, Parkinson’s care, palliative care, rehabilitation, and skilled nursing. So Age Care Labs isn’t pitching a single app. It’s building a care ladder.

Who founded Age Care Labs and why are they credible?

The founding story

Roy didn’t come into this category by accident. He built Age Care Labs around the idea that older adults should be able to stay independent for as long as possible, with structured help wrapped around them rather than dumped on family members. Epoch came from a different starting point — more clinical, more residential, more focused on dementia and long-term elder support. That gives the combined platform a wider operating base than most single-format elder care brands.

Founder market fit

Roy’s background fits the category unusually well. Before Emoha, he worked at Antara Senior Living, founded Ignox Labs, and spent time at Jones Lang LaSalle in social infrastructure. He studied planning at the School of Planning and Architecture in New Delhi and later earned an MBA from the Indian School of Business. In plain English: he understands care, housing, and how to build service businesses around both.

Sinha brings the clinical depth. She’s a clinical psychologist and dementia specialist who started her career with Sanjivini Society for Mental Health, worked in psychiatric rehabilitation, and later helped shape Epoch from a home-care provider into an assisted-living operator. She’s also trained in palliative care. That matters because dementia and end-of-life care aren’t side services here — they’re core operating disciplines.

Traction, fundraising, and competition

The company already has some scale. Roy said Age Care Labs is serving around 300,000 seniors across 40 Tier I and II cities. Epoch now has 6 assisted living homes across Gurgaon and Pune with about 200 rooms, and the broader platform has raised $29 million to date while following an asset-light, technology-first model.

This latest cheque is ₹85 crore, or about $9 million, in a Series B1 round. Shrem Group led it, with participation from Rainmatter, Pegasus Finvest, and family offices. The round sits inside a larger planned Series B raise of ₹250 crore that the company expects to complete in Q1 2027. Age Care Labs had already drawn backing from Lumis Partners, Rainmatter, Gruhas, and KOIS Invest before this round.

Competition is fragmented, which is both good and messy. On the home-care side, organised players include Samarth, Yodda, and Portea. In residential senior care and assisted living, Antara, Athulya, and Primus are among the better-known names. Age Care Labs’ pitch is that most rivals specialise in one slice, while it wants to own the journey from home monitoring to assisted living and now independent senior communities through Shremoha. It’s a stronger story — if execution holds.

Why are investors backing Age Care Labs now?

Because this round changes the shape of the business.

Age Care Labs wasn’t just raising growth capital. It also signed a strategic partnership with Shrem Group to launch Shremoha, a premium senior independent living platform. That matters because residential senior living needs real-estate and hospitality muscle as much as care expertise, and Shrem brings exactly that. Roy called the new venture “a natural extension” of the company’s existing experience, adding, “Our ambition is to build communities where seniors are not just cared for but are active, connected, and fully alive.”

The funding will go into service expansion and technology. It will also support stronger healthcare capabilities and broader growth across India. Read between the lines and the strategy is obvious: Age Care Labs wants tighter control over the elder care stack, from remote monitoring and coordination to premium physical communities. That’s ambitious. It won’t be cheap, but it’s more defensible than staying a light-touch concierge brand forever.

Shrem Group’s thesis also sounds direct. Founder and managing director Nitan Chhatwal said India’s next generation of seniors is more independent and more focused on quality of life, and that Shremoha is meant to match that expectation with real estate, hospitality, preventive healthcare, wellness, emergency response, and coordinated care. Investors aren’t just backing elder care demand here. They’re backing the rise of senior lifestyle infrastructure.

How big is India’s senior living market?

The demographic case is huge. The source article cites a CareEdge Ratings estimate that India’s 60-plus population will rise to about 231 million by 2036 from roughly 142 million in 2021, creating a specialised senior care market worth around $35 billion a year. That’s already enough to explain why capital keeps showing up. It still probably understates how much demand sits outside organised providers.

The housing side is also getting bigger. Grand View Research estimates India’s senior housing market at $2.06 billion in 2024 and projects it will reach $3.23 billion by 2030, growing at a 7.78% CAGR. Its report also points to the same forces operators keep talking about: nuclear families, greater mobility, rising acceptance of senior living, and older Indians wanting better housing rather than just medical fallback options.

The market isn’t just about old-school retirement towns anymore. Developers are increasingly building in or near major cities because wealthier retirees want to stay close to family, hospitals, and city amenities. Grand View also notes that returning NRIs are part of the demand story, especially for higher-quality communities with hospitality and healthcare built in. That urban shift lines up neatly with what Age Care Labs and Shrem are trying to build.

What happens after Age Care Labs funding?

Age Care Labs now has a chance to become more than an elder care operator.

If Shremoha launches well and the rest of the ₹250 crore Series B closes on schedule in Q1 2027, the company could end up owning one of the more complete senior care models in India — home care, assisted living, and independent living under one umbrella. That’s the upside. The harder part will be keeping service quality high while stitching together healthcare operations, hospitality standards, and real-estate execution.

Read how Venice AI raised a $65M Series A led by Dragonfly to build a privacy-first AI platform that gives users and developers access to hundreds of AI models without storing prompts or conversation history.

FAQ

• What is the Age Care Labs funding round about? Age Care Labs has raised ₹85 crore in a Series B1 round led by Shrem Group, with participation from Rainmatter, Pegasus Finvest, and family offices. The round is part of a larger planned ₹250 crore Series B that the company expects to complete in Q1 2027, and the money is meant to support expansion across services, healthcare capabilities, and senior living.
• How does Age Care Labs work for seniors and their families? It works as a multi-format elder care platform. Emoha supports seniors at home with monitoring, emergency coordination, teleconsults, records, and appointment help. Epoch offers 24×7 assisted living, dementia care, palliative care, rehabilitation, and nursing for seniors who need more intensive support.
• Who founded Age Care Labs and what is their background? Age Care Labs was founded in 2019 by Saumyajit Roy, who previously worked at Antara Senior Living and Jones Lang LaSalle and also founded Ignox Labs. The platform’s residential and dementia-care depth comes from Epoch leader Neha Sinha, a clinical psychologist and dementia specialist with palliative-care training and years of operating experience in elder care.
• Is Age Care Labs a healthtech company or a senior living company? It’s both, and that’s the point. Age Care Labs sits in the organised elder care category, combining tech-enabled home care with assisted living and now independent senior living through Shremoha, which puts it somewhere between a healthcare services company and a senior housing operator.

Venice AI is a privacy-first platform that gives people and developers access to hundreds of AI models without keeping their prompts and conversation history on company servers. This week, Venice AI raised a $65 million Series A at a $1 billion valuation, led by Dragonfly, as demand grows for AI tools that feel less monitored and less locked down than the big mainstream assistants. The company was founded in 2024 by Erik Voorhees, with Teana Baker-Taylor joining the launch team as COO, and it’s chasing a clear problem: lots of users want powerful AI, but they don’t want to trade away privacy or accept heavy-handed moderation to get it.

What is Venice AI and how does it work?

At the product level, Venice AI is a multi-model AI layer with privacy controls built into the user experience. It offers OpenAI-compatible chat, image, audio, video, and embedding access behind one API key. The consumer app lets users switch among models and outputs without juggling a pile of separate subscriptions or accounts. The company hosts open-source models itself and routes requests to some closed-source models from providers like OpenAI and Anthropic.

The workflow is more specific than the usual “private AI” pitch. A user picks a model and chooses a privacy mode for that conversation. Then the request goes through Venice’s relay, and the result comes back without Venice storing the chat on its own servers. Conversation history stays on the user’s device. For people who care most about speed or model choice, there are lighter privacy modes. For Pro users, there are TEE and end-to-end encrypted modes, where prompts are encrypted on-device and only decrypted inside a verified secure environment.

It’s not just text chat. Venice supports image generation and image editing. It also handles upscaling, background removal, text-to-speech, transcription, text-to-video, image-to-video, and reference-to-video. It has customizable AI characters, plus an API aimed at developers who want tool use and streaming. Vision support and function-calling are included in a format that works with existing agent stacks.

Here’s where it gets practical. Instead of hopping between one model for chat, another for images, and a third for coding or agents, a user can stay in one interface and choose how much privacy, censorship, and model variety they want. The trade-off is obvious. The strongest privacy modes can limit features like memory or web search and may run slower. Venice isn’t pretending otherwise.

Who founded Venice AI and why now?

The founding story

Venice launched publicly in 2024 with a very crypto-coded thesis: sovereignty shouldn’t stop at money. It should extend to AI, too. Voorhees has framed the company around private-by-default use and open-source foundations. He’s also pushed for fewer ideological filters than the large commercial labs tend to impose. Baker-Taylor made a similar case at launch, arguing that the same questions people asked in crypto about ownership and control were starting to show up around data and AI usage.

Why these founders make sense for this bet

Voorhees didn’t come out of nowhere. He was an early Bitcoin advocate, founded Satoshi Dice, then built ShapeShift into one of crypto’s better-known exchanges. Across those ventures, he pushed a consistent privacy-first and anti-surveillance worldview — sometimes productively, sometimes controversially. That worldview now sits at the center of Venice. He has described the service as a “neutral tool” and argued that over-monitoring AI use could be more dangerous than letting adults ask uncomfortable questions.

Baker-Taylor adds a different kind of credibility. Before Venice, she was Circle’s vice president of policy and regulatory strategy. She also worked in senior roles at Binance, Crypto.com, HSBC, and Citigroup. That mix matters. Venice isn’t just an AI app; it sits where consumer AI, privacy, and crypto culture overlap, which means operational and regulatory instincts matter a lot.

Traction, fundraising, and how Venice AI compares

The early numbers are real. Venice has more than 850,000 unique website visitors, over 3 million active users, and about 1.7 million API calls per day. It’s already profitable, with annualized run-rate revenue above $70 million. That’s not normal for a 2-year-old AI startup, especially one that hadn’t raised outside capital before this round.

The company’s monetization is a little unusual, which fits the founders. Alongside subscriptions, Venice has 2 crypto tokens tied to usage: VVV, launched in January 2026, and DIEM, added in August 2025. Users can stake VVV to mint DIEM, which generates $1 a day in Venice credits, though only about 8% of users currently pay with crypto. That’s a differentiator. The bigger story is that Venice has moved much closer to feature parity with ChatGPT while holding onto its privacy pitch.

On competition, Venice is threading a middle path. ChatGPT and Claude are still the default mainstream assistants, but they’re single-vendor experiences with their own rules and retention models. Poe is the cleaner consumer comparison. It offers one place to access many models, images, video, audio, and user-built bots. OpenRouter is the developer-side comparison. It offers a unified API for hundreds of models with strong routing and filtering controls. Venice’s angle is different from both: it combines multi-model access with local-only history and selectable privacy modes. It also offers hosted open models, customizable characters, and a more openly “uncensored” brand. That’s what Dragonfly and the other investors are backing — not just another chatbot, but a branded trust layer for people who think mainstream AI is too restrictive.

Why are investors backing Venice AI now?

The timing matters because this doesn’t look like rescue financing. Venice was already profitable before taking its first outside round, which makes the Series A look more like acceleration capital than survival money. That changes the investor story. Dragonfly and the rest aren’t funding a speculative prototype; they’re paying up for traction, margins, and a product that already found a loyal use case.

The use of funds is also telling. Venice wants to stop leasing so much compute, start buying GPUs, and build its own data centers. That’s expensive and a little risky — hardware ownership always is — but it’s also the straightest path to better gross margins and tighter control over the models it hosts itself. If privacy and unrestricted access are the brand promise, owning more of the underlying infrastructure makes that promise easier to defend.

There’s an ideological signal here, too. Investors are betting that a meaningful slice of the AI market wants something less paternalistic than the default lab products. That bet could age well. Or it could run into the same criticism privacy-maximalist platforms always face when bad actors show up. Either way, the round says demand is now big enough to finance at infrastructure scale.

What does the AI market say about private model platforms?

Gartner forecasts worldwide AI spending will reach $2.59 trillion in 2026, up 47% from the prior year. More than 45% of that spending is expected to land in infrastructure categories like AI-optimized cloud, servers, network fabric, and semiconductors. That’s a huge clue about why Venice is trying to own more compute instead of staying purely asset-light. The money in AI isn’t just in the interface anymore. It’s in the stack underneath it.

A second shift helps Venice. As model access gets cheaper and more modular, users care less about pledging loyalty to a single lab and more about getting the right model, the right workflow, and the right trust assumptions. That’s why multi-model products keep showing up in both consumer and developer form. Venice is riding that same structural wave, using privacy and looser moderation as the wedge rather than price or convenience alone.

Can Venice AI turn privacy into infrastructure?

Venice AI has already proven there’s a real market for private, multi-model AI that feels less supervised than the mainstream options. The bigger test starts now. Raising $65 million is the easy part compared with owning GPUs, operating data centers, and defending an uncensored brand once the platform gets even larger.

Read how Supply6 raised ₹48 crore in funding led by Unilever Ventures to expand its daily nutrition product lineup, strengthen research and supply chains, and scale its omnichannel wellness brand across India.

FAQ

• What funding did Venice AI raise? Venice AI raised a $65 million Series A on July 1, 2026, at a $1 billion valuation. Dragonfly led the round, with participation from Coinbase Ventures, North Island Ventures, and other investors, and it was the company’s first outside fundraise.
• How does Venice AI work for users and developers? Venice AI gives users one place to access text, image, audio, video, and other AI models with selectable privacy modes for each conversation. For developers, it offers an OpenAI-compatible API with support for streaming and tool use. It also supports multimodal generation and agent integrations, while keeping chat history on the user’s device rather than on Venice servers.
• Who founded Venice AI? Venice AI was founded in 2024 by Erik Voorhees, the longtime crypto entrepreneur behind ShapeShift and Satoshi Dice. Teana Baker-Taylor, formerly Circle’s VP of policy and regulatory strategy, joined the launch effort as COO and brought deep experience from crypto, banking, and regulation.
• Is Venice AI a chatbot company or AI infrastructure company? It’s both, which is part of why the company is interesting. Consumers can use it like a private chatbot and media-generation app. The API, agent tooling, privacy architecture, and new plan to buy GPUs and build data centers also push Venice toward becoming an infrastructure layer for private AI access.

Supply6 is a Bengaluru D2C company that sells daily nutrition supplements for people who want vitamins, hydration, fibre, and gut support in a simpler format than juggling multiple products. The Supply6 nutrition brand has raised ₹48 crore in fresh funding led by Unilever Ventures, with participation from existing investor Zeropearl VC and actor Kriti Sanon. The core bet is straightforward: a lot of Indian consumers want preventive health products that are quick to buy and easy to use, without turning every morning into a chemistry project. Founded in 2019 by Vaibhav Bhandari and Rahul Gupta, Supply6 is operating at an annualised revenue run rate of ₹75 crore and expects to touch ₹100 crore in the next 3 to 4 months.

That’s not a small jump.

And it explains why this round matters more than the headline number.

What does the Supply6 nutrition brand actually sell?

The flagship product, Supply6 360, is a single-serve daily nutrition sachet meant to be mixed into water and consumed once a day. One serving is built around vitamins, minerals, probiotics, prebiotics, digestive enzymes, adaptogens, and plant-based whole-food ingredients. The formula is positioned as an all-in-one supplement rather than a narrow single-benefit product. On the product side, that matters because the brand isn’t asking customers to assemble separate gut-health and immunity routines. Micronutrients are covered too.

The use flow is about as low-friction as these products get. A customer tears open a sachet, mixes it with about 120 ml of water, and drinks it. Supply6 says it works best with water rather than milk and advises against hot water because heat can reduce the effectiveness of some nutrients. That sounds basic. But the convenience is as much the product as the ingredient list.

Under the hood, the formula is fairly dense. Supply6 360 carries 63+ superfoods, vitamins, minerals, and related nutrients per daily serving, along with 3 billion CFU probiotics. The ingredient architecture spans adaptogens like panax ginseng and maca. It also includes greens such as beetroot and kale, plus seeds including flax and chia. Prebiotics like inulin and FOS are in the mix, along with digestive enzymes such as amylase, protease, cellulase, lipase, and lactase. Supply6 also says a serving provides about 95% of daily vitamin B12 needs and 83% of daily vitamin D.

That product design tells you what the founders are chasing.

Not hardcore sports nutrition. Not medical nutrition either.

It’s closer to a daily-use wellness habit for busy consumers who want broad nutritional coverage in one step.

Who built Supply6 and how far has it come?

The founding story

Supply6 started in Bengaluru in 2019, built by Vaibhav Bhandari and Rahul Gupta around a simple consumer insight: plenty of people don’t eat especially well, but they still want a practical way to cover recurring nutrient gaps. The company’s brand story is wrapped around the “six” in Supply6 — protein, carbohydrates, fats, vitamins, minerals, and fibre — which gives the business a cleaner identity than a lot of wellness brands that keep piling on claims without a clear core.

That focus has helped the company stay legible. Instead of trying to be everything to everyone from day one, Supply6 built around foundational daily nutrition and then widened into adjacent categories across vitamins, hydration, and fibre. It’s a sharper pitch than the usual supplement-brand sprawl.

Traction, distribution, and fundraising

The latest round brings in ₹48 crore, or about $5 million, led by Unilever Ventures. Zeropearl VC joined again, and Kriti Sanon — who came on board as an investor and brand ambassador in December 2025 — also participated. With this raise, Supply6 has now brought in more than $6 million in total funding.

Its earlier round was a $1.1 million pre-seed raise in 2025 from Zeropearl VC, Kunal Shah, Renee Cosmetics cofounders Ashutosh Valani and Priyank Shah, and XYXX founder Yogesh Kabra.

The business already sells through its own website, Amazon, and quick commerce platforms including Blinkit. That mix matters because wellness discovery increasingly happens across marketplaces and impulse channels, not just on brand-owned stores. Supply6 says its annualised revenue run rate is now ₹75 crore, with a target of ₹100 crore within months. Ambitious, yes, but not absurd if quick commerce conversion keeps improving.

Competition and positioning

Supply6 isn’t entering an empty category. It’s up against Marico-owned Plix, HUL-owned Oziva, Kapiva, and BeastLife, among others. That’s a tough set. Some rivals are stronger in herbal or Ayurvedic positioning. Some are better known in mainstream urban wellness. Others win on celebrity pull and broad SKU depth.

Supply6’s angle is different enough to stand out. The brand focuses on clinically backed daily nutrition and a simplified one-sachet format. Broad omnichannel availability across D2C, marketplaces, and quick commerce also helps. In a crowded dietary supplements market, that combination of convenience and routine-building is probably what Unilever Ventures is buying into.

Why does this Supply6 nutrition brand round matter?

Because this isn’t just expansion capital.

It’s operating capital for a company trying to turn a single-product habit into a broader consumer brand.

Supply6 says the new money will be used to expand its product portfolio, invest in clinical research and engineering, strengthen the supply chain, and improve digital capabilities. Some of the capital is also earmarked for entering new markets. The company also plans to build marketing and partnership muscle, hire across functions, and widen its reach across D2C, marketplaces, and quick commerce channels.

That list tells you where management thinks the next bottlenecks are. Not awareness alone. Not just distribution. It’s product depth, operational reliability, and channel execution at the same time.

Unilever Ventures leading the round adds another signal. Consumer investors don’t back these businesses only for top-line growth. They back them when they think repeat purchase behavior and brand recall can compound. Category tailwinds matter too.

How big is India’s nutrition and wellness market?

Pretty big. And still getting bigger.

Supply6 operates inside India’s dietary supplements market, which is expected to reach $62 billion by 2033, growing at a 13% CAGR from 2024, based on the market estimate referenced in the source article. That’s the kind of number investors like because it supports multiple large brands, not just one breakout winner.

The demand drivers are easy to spot. Preventive healthcare is becoming more mainstream. Consumers are spending more on functional foods and daily wellness routines. Lifestyle-related conditions such as obesity, diabetes, and cardiovascular issues are pushing more people toward supplements aimed at immunity, weight management, hydration, digestion, and general wellbeing.

Quick commerce is part of the story too. So is the shift toward clinically backed products rather than vague wellness promises. That’s why this category keeps pulling capital even when investors are more selective elsewhere.

Can the Supply6 nutrition brand hit ₹100 Cr next?

It can.

But the next stretch won’t be won by branding alone.

Supply6 already has the ingredients investors usually want to see in a D2C nutrition startup: a focused hero product, a visible celebrity backer, repeat-use potential, and growing omnichannel distribution. The harder part now is turning that into durable scale without getting buried under customer acquisition costs or lost in a market where every second brand is selling “daily wellness.”

Read how Spense raised a $2.8M seed round led by Arkam Ventures to help banks launch secured credit cards and UPI credit lines backed by customer assets without replacing their core banking systems.

FAQ

• What is the latest Supply6 funding round?
  Supply6 has raised ₹48 crore in a new round led by Unilever Ventures. Zeropearl VC joined the round again, and Kriti Sanon also participated after coming on board as an investor and brand ambassador in December 2025. The raise takes the company’s total funding to more than $6 million.
• How does Supply6 360 work?
  Supply6 360 is a once-daily nutrition sachet that you mix with water and drink. It combines 63+ ingredients in one serving, including probiotics, prebiotics, vitamins, minerals, adaptogens, and digestive enzymes. The product is built as a broad daily supplement rather than a single-purpose pill or powder.
• Who founded Supply6?
  Supply6 was founded in Bengaluru in 2019 by Vaibhav Bhandari and Rahul Gupta. The company was built around the idea that modern consumers want a simpler way to cover everyday nutrition needs without stacking multiple wellness products.
• Is Supply6 a D2C supplements company or a wellness brand?
  It’s both, but the cleaner label is a D2C nutrition and wellness brand. Supply6 sells dietary supplements directly to consumers while also using marketplaces and quick commerce, which puts it in the same broad category as brands like Plix, Oziva, Kapiva, and BeastLife.