Author: Woodenscale AI

Aina builds Aina AI hardware for people who want faster ways to trigger AI actions across their laptop and phone. The Bengaluru- and San Francisco-based startup has raised $5.5 million in its first round as it chases a problem a lot of AI users now feel every day: the models keep getting better, but the ways we control them still feel clumsy. Founded in 2025 by former Ultrahuman hardware executive Apoorv Shankar, the company is starting with a tiny keypad called Dune and using it as a live test for a much bigger bet on AI interfaces.

Shankar’s pitch is pretty direct. He isn’t trying to build another gadget that just listens, records, and summarizes your life. He wants hardware that helps you do things — join a call, mute yourself, run a script, trigger an agent, approve a pull request, or fire off a workflow without hunting through tabs and shortcuts.

What is Aina AI hardware and how does Dune work?

Dune is a 3-key, context-aware macOS keypad that plugs in over USB-C and changes what each button does based on the app you’re using. If you’re in a meeting, it can surface the right call controls. If you’re in a developer tool, it can swap to coding actions and if you’re in Notion, Figma, or Excel, it can trigger common shortcuts without making you remember them. That’s the core of Aina AI hardware right now: fewer menus, fewer keyboard gymnastics. More one-tap actions.

The meeting workflow is more specific than the source article suggested. Dune syncs with your calendar and surfaces a meeting link 2 minutes before a call. One key joins the meeting. Another can send a “running late” email. Once the meeting starts, the keys can become physical mic and camera toggles. One press can also pull the meeting window to the front if it’s buried under tabs.

For developers and heavy desktop users, Dune is basically a programmable control surface that keeps remapping itself. The device detects whether you’re in GitHub, VS Code, Claude, or another supported app and updates the keys in real time. Users can open URLs and run scripts. They can also install workflows from a Dune marketplace. Users can even configure the setup through a chat interface with Claude instead of digging through settings. It ships as a CNC-machined anodized aluminum accessory, weighs 50g, and runs without a battery.

That matters because most macro pads still assume the user will do the hard part. You program them. You remember the layers and you remember the shortcuts. Dune is trying to remove that setup tax.

Who founded Aina and why did Apoorv Shankar start it?

The founding story

Aina — “mirror” in Hindi — was incorporated in May 2025 and spent its first stretch in stealth under the name Project Mirage. The company has been operating like an HCI lab, testing different forms of AI-native hardware before deciding what deserves a real launch. That’s how it ended up with 3 experimental products instead of just 1.

Shankar has been blunt about why he left Ultrahuman. “I left Ultrahuman last year because I was just super curious about the space of AI interfaces,” he said. “Devices like Rabbit and Humane Pin had launched, and I had my own disappointments with them.” He liked the idea of new interfaces. He just didn’t like the first batch enough to stop there.

Why Shankar looks credible here

This isn’t a software founder dabbling in hardware for fun. Shankar is an engineer-turned-product designer who spent years building consumer devices, and he was previously VP of Hardware at Ultrahuman. Before that, he completed an MDes at the Indian Institute of Science and built products through LazyCo, a startup focused on interface hardware. His own posts show he spent 3.5 years at Ultrahuman working on hard manufacturing problems, including scaling production of the Ring Air.

That background matters more than the buzzwords. Small hardware is unforgiving. So are supply chains. A founder who has already shipped miniaturized devices has a much better shot than someone still treating prototypes like product-market fit.

Past ventures and execution record

LazyCo is the clearest proof point. The startup built the Aina Ring, a wearable that let users control smartphone actions from a ring, and its Kickstarter campaign brought in more than $36,000. LazyCo was founded in 2017, and Ultrahuman later acquired it — which is how Shankar moved in-house before eventually heading back out on his own.

There’s a clear through-line here. Years ago, he was already trying to reduce touchscreen friction with a ring. Now he’s revisiting the same instinct in the age of agents.

Product signals, funding, and where Aina sits in the crowd

Aina has already built 3 devices: Dune, Radiance, and Shift. Radiance is a tabletop video-call remote with a volume dial plus buttons for mic, camera, AI notetaking, voice modulation, and joining meetings. Shift is a single-tap “agentic” button that connects to a phone and kicks off repeated tasks. Early testing showed Dune was the breakout, so Aina decided to ship that first and fold lessons from the others into later devices. A small group of users will begin testing the next product in the coming weeks.

Redstart Labs and 360 ONE led the funding round, with participation from MIXI Global Investments, Antler, and Blume Founders Fund. Angel backers include newly appointed WhatsApp head Kunal Shah, Razorpay co-founders Harshil Mathur and Shashank Kumar, and Scribd founder Tikhon Bernstam. The amount is $5.5 million. For a hardware startup still early in market formation, it’s a meaningful first pool of capital.

Competition is crowded, but not all of it is direct. Plaud is pushing AI note-taking devices and has sold more than 1.5 million units. Rabbit’s R1 went the handheld route at $199. Humane’s AI Pin tried to replace the phone and then collapsed fast enough that HP bought most of its assets for $116 million in February 2025 and shut the product down. Meta Ray-Bans, Bee, Friend, and smart-glasses startups all sit somewhere in the same messy category. Aina’s distinction is simpler: it isn’t betting that people want yet another passive recorder on their body. It’s betting they want fast, intentional controls for agents and workflows.

Why does Aina AI hardware’s $5.5M round matter?

This round gives Aina room to do something a lot of AI hardware companies never get to do properly: test behavior before locking the form factor.

Dune isn’t being sold as the final answer. It’s a probe. A live experiment. The company wants to learn which actions users actually repeat often enough to deserve a dedicated control surface, and which ones sound clever in a demo but don’t survive daily use. That’s a much healthier posture than launching a grand “phone killer” and hoping the internet fills in the gaps.

The investor thesis comes through here too. Backers aren’t just funding another gadget. They’re funding a founder with a manufacturing record, a clear skepticism about passive AI wearables, and a product direction that matches how AI is getting used right now — inside work, across apps, in quick bursts, with a lot of repetitive prompts and approvals.

What market is Aina AI hardware targeting?

The broad category is wearable and interface hardware for AI, and it’s getting big fast. Grand View Research estimates the global wearable AI market was worth $43.6 billion in 2025 and projects it will reach $310.6 billion by 2033, a 27.8% CAGR. On-device AI accounted for 59.1% of the market in 2025. That helps explain why founders keep trying new formats even after some very public flops.

But the more interesting shift isn’t just “wearable AI.” It’s the move from asking AI questions to assigning AI tasks. As developers and knowledge workers spend more time in Claude Code, OpenAI Codex, and meeting assistants, the friction moves from intelligence to control. This week’s custom Codex keypad from OpenAI and Work Louder fits that same pattern. So do reports that OpenAI is exploring a smart speaker, Rabbit’s agent-focused pitch, and Qualcomm’s claim that it’s experimenting with more than 40 AI interaction devices. The category is still undecided.

Conclusion: Aina AI hardware has a narrower, smarter bet

A lot of AI gadgets have tried to replace the phone. That’s usually where the pitch starts going off the rails.

Aina is taking a narrower bet with Aina AI hardware: don’t replace the computer, don’t record everything, just make high-frequency AI actions easier to trigger. That’s a more grounded idea. The next thing to watch is whether Dune’s real-world usage teaches Aina that people want a desk accessory, a portable button, or something stranger that only makes sense once agents become normal.

Read how Vorflux raised $15M in seed funding to build an AI software engineering platform that automates planning, coding, testing, review, and deployment from a single prompt.

FAQ

• What funding did Aina raise?
  Aina raised $5.5 million in its first round. Redstart Labs and 360 ONE co-led the financing, with MIXI Global Investments, Antler, and Blume Founders Fund joining in, alongside angels including Kunal Shah, Harshil Mathur, Shashank Kumar, and Tikhon Bernstam.
• How does Dune work?
  Dune is a 3-button macOS keypad that changes functions depending on the app you’re using. It can pull up meeting actions and run scripts. It can also trigger shortcuts and launch agent workflows, which makes it closer to a context-aware control device than a normal macro pad.
• Who is Apoorv Shankar?
  Apoorv Shankar is Aina’s founder and a former VP of Hardware at Ultrahuman. Before that, he founded LazyCo in 2017 after completing his MDes at IISc, and LazyCo’s Aina Ring crowdfunding campaign brought in more than $36,000 before the company was later acquired by Ultrahuman.
• What market category is Aina in?
  Aina sits in the emerging AI interface hardware category, which overlaps with human-computer interaction devices, macro controllers, wearables, and agent-control accessories. It’s competing less with traditional laptops and more with the growing pile of AI-first gadgets trying to answer the same question: what should the control layer for AI actually look like?

Vorflux is a new AI software engineering company that wants to automate far more than code generation. The Vorflux AI startup has raised $15 million in seed funding as it goes after a gap in modern development: teams may have AI copilots, but engineers still end up doing the planning, testing, review, and deployment work themselves. Founder Prasanna Sankar launched Vorflux in July 2026 after previously co-founding Rippling in 2016 and serving as its CTO until July 2020. That history matters. This isn’t a first-time founder pitching a vague AI dream. It’s a repeat builder trying to productize engineering judgment at enterprise scale.

What does the Vorflux AI startup actually do?

Vorflux sells what is basically an AI-operated software engineering workflow. A team connects its repos, databases, CI/CD tools, observability stack, and work apps. Then it feeds the system an input like a GitHub issue, a Slack message, a Linear ticket, a Loom, or plain text. From there, Vorflux explores the codebase and surrounding context, drafts a plan, and breaks work into sub-tasks. It builds the change, reviews it, tests it in a browser, and returns a production-ready pull request with evidence attached.

The interesting bit isn’t that it writes code. Tons of tools do that now. Vorflux is trying to own the full path from intent to merged PR by using different models for different jobs. Its planner and reviewer can be separate models with separate context windows. The system also runs what it calls adversarial review, so one model isn’t just blessing its own output. That’s a real complaint with current AI coding products.

Its infrastructure pitch is also more serious than the usual chatbot wrapper. Vorflux runs sessions on dedicated EC2 machines with a company’s codebase, Docker setup, and local infrastructure cloned into place. QA agents can open the app in a real browser, click through flows, record a video, and attach that proof to the PR. That matters.

And there’s a practical layer on top. Vorflux has a Chrome extension that lets users annotate elements on a live web page, capture screenshots, and bundle those comments into one session. Then they can send them straight to the agent. So instead of writing a fuzzy ticket about a broken pricing card, a team can point at the exact button, the exact section, and the exact visual issue. That’s not glamorous. It is useful.

Who is building the Vorflux AI startup?

Sankar’s founder-market fit is unusually strong

Prasanna Sankar isn’t coming in as an outsider. He co-founded Rippling with Parker Conrad in 2016 and helped build it through its early years as CTO. Before that, he was a director of engineering at Zenefits. Earlier, he founded LikeALittle, worked as a software developer at Microsoft, interned at Google, and studied computer science at NIT Trichy. He also has the kind of programming-contest résumé that means something in this category—ranked No. 1 in India on TopCoder while in college, plus 2 appearances each as a Google Code Jam and ACM ICPC world finalist.

The company story is really about a second swing

Vorflux comes after 0xPPL, Sankar’s crypto-focused startup, shut down. That matters less as a black mark than as a signal of how quickly he’s pivoted back toward enterprise software—an area where he’s more proven. The through-line across Rippling and now Vorflux is workflow compression: remove fragmented manual steps, then wrap opinionated software around the mess.

Early signals, round details, and where the money came from

Vorflux is already live enough to be taking sign-ups and sales conversations, and its site frames the product as a launch-stage cloud agent for teams rather than a research demo. Sankar said the startup raised a $15 million seed round backed by Y Combinator, Peak XV Partners, Powerset, Alliance, and angel investors including Parker Conrad, Immad Akhund, and Balaji Srinivasan. That mix is telling. Operator angels who know software orgs are in, along with investors willing to back an ambitious infrastructure-heavy AI product before it has years of market proof.

Who Vorflux is up against

This market is already crowded, and not with weak players. Cognition has pushed Devin as an AI software engineer and says it has raised more than $1 billion. Factory’s whole pitch is “autonomy to software engineering.” Cursor has raised $900 million to keep extending from AI code editor toward broader programming workflow control. The old baseline is still GitHub Copilot-style assistance, where a human stays in the loop for almost everything that happens after the first draft. Vorflux is betting companies want something more opinionated and more operational—an agent system that plans, runs, tests, and ships on cloud infrastructure instead of stopping at autocomplete.

Why did investors back the Vorflux AI startup now?

Because Sankar is selling a bigger idea than “better code suggestions.” He’s arguing that the expensive bottleneck in software teams is no longer typing code, but everything around it—coordination, review, verification, handoff friction, and the random backlog work nobody gets to. If Vorflux can compress those steps into one system, the pitch to buyers shifts from developer productivity software to engineering capacity software. That’s a much bigger budget line.

There’s also a founder thesis here. Rippling’s early reputation came from building opinionated systems that absorbed ugly operational workflows and made them feel simple on the front end. Vorflux is trying the same thing for engineering organizations. And because the product is model-agnostic rather than tied to one foundation model vendor, investors may be betting that the orchestration layer—not the underlying LLM—ends up being where durable value sits.

How big is the AI software engineering market?

It’s already large, and it’s growing fast enough to attract serious capital. Grand View Research estimates the global AI code tools market was worth $4.9 billion in 2023 and projects it will reach $26 billion by 2030. That’s the macro reason seed rounds like this keep getting done even when the category still feels noisy and unfinished.

Developer behavior is moving in the same direction, even if trust hasn’t caught up. Stack Overflow’s 2024 developer survey says 76% of developers are using or planning to use AI coding tools, while GitHub has reported that 92% of U.S.-based developers at large companies use an AI coding tool at work or personally. But Stack Overflow also found accuracy and trust are major concerns. That’s why startups like Vorflux are leaning so hard into review layers, testing, and proof of execution instead of just faster code generation.

Can Vorflux become more than another AI coding tool?

Vorflux has the founder, the story, and now the capital. What it doesn’t have yet is years of public proof that enterprises will hand critical engineering workflows to an automated system and trust the output enough to let it ship widely. The Vorflux AI startup looks more thoughtful than the average “agentic” launch because it’s attacking the boring hard parts—planning, orchestration, testing, and review—instead of pretending code completion was the whole job. The next thing to watch is simple: does it become a real enterprise workflow, or just another impressive demo for engineering Twitter?

Read how Reo.Dev raised $11.3M in Series A funding to help software vendors identify developer buying intent from GitHub activity, product usage, and AI-driven evaluation signals before sales gets involved.

FAQ

• What is the funding round for Vorflux? Vorflux raised a $15 million seed round in July 2026. The backers include Y Combinator, Peak XV Partners, Powerset, Alliance, and angels such as Parker Conrad, Immad Akhund, and Balaji Srinivasan, which gives the company a heavyweight early cap table.
• How does Vorflux work for software teams? Vorflux works by connecting to a team’s engineering stack and turning prompts, tickets, or visual annotations into a full delivery flow. It plans the work and assigns sub-agents. It runs on dedicated cloud machines, tests in a browser, and returns a mergeable PR with context and proof. That’s a lot closer to an autonomous SDLC layer than a normal coding assistant.
• Who is Prasanna Sankar? Prasanna Sankar is the co-founder and former CTO of Rippling, where he worked from the 2016 founding through July 2020. Before Vorflux, he also worked at Zenefits, founded LikeALittle, spent time at Microsoft, interned at Google, and built a reputation as a top competitive programmer from NIT Trichy.
• Is Vorflux part of the AI coding assistant market or something else? It’s in the AI coding tools market, but it’s aiming at the more aggressive end of that category. Rather than acting like an autocomplete layer, Vorflux is trying to automate the broader software development lifecycle, which fits with a market that Grand View Research expects to grow to $26 billion by 2030 as developer adoption keeps rising.

Reo.Dev sells software that helps tech vendors spot which engineering teams are actively evaluating their products. It has now raised $11.3 million in Series A funding led by Elevation Capital, a big vote for a developer intent platform built around a problem most sales teams still handle badly: developers often shape software purchases long before any rep gets a meeting. Founded in 2023, the Bengaluru-headquartered startup is led by co-founder and CEO Achintya Gupta, who started the company after dealing firsthand with the mess of selling to technical buyers.

That timing matters.

Software buyers increasingly want to research on their own, and a lot of that evaluation now happens in docs, GitHub repos, package installs, product trials, and community threads instead of demo requests. Reo.Dev is trying to turn that messy trail into something sales and marketing teams can use.

What is Reo.Dev’s developer intent platform and how does it work?

At a basic level, Reo.Dev watches for technical buying signals and ties them back to real accounts and developers. It also maps likely buyers. Its system pulls in activity from sources like GitHub and package managers such as npm, pip, and Helm. It also uses open-source telemetry, cloud sign-ups, technical docs, and other developer touchpoints, then converts that behavior into ranked leads for go-to-market teams.

Here’s the practical workflow. A devtools company connects its data sources and sets up the metrics that matter to its sales motion. Then it lets Reo.Dev score activity by intent level. The platform can weight actions as high, medium, or low intent, then surface them in account and developer timelines. Teams can build segments from those signals. They can push them into HubSpot or other systems, and trigger alerts in Slack or external tools through webhooks.

That removes a lot of tedious work. Instead of manually checking docs traffic and GitHub stars, plus trial logins or random community activity, a sales or RevOps team gets structured signals tied to account stages, activity scores, tags, and buyer recommendations. Reo.Dev also lets users define custom buyer personas so they can move from “some engineers at this company are active” to “this is probably the VP Engineering or platform lead who matters.”

There’s also a newer twist: agent behavior. Reo.Dev’s Agent Intent Gateway is built for a world where AI agents, not just humans, are researching software and querying docs. They’re also calling MCP tools and testing workflows. The pitch is simple: if evaluation is shifting into agent activity buried in logs, vendors need a way to see those signals before they disappear into the background.

Who founded Reo.Dev and what traction does it have?

The founding story

Reo.Dev was founded in March 2023 by Achintya Gupta, Gaurav Jain, and Piyush Agarwal. Gupta has tied the company’s origin directly to his time leading revenue at Phyllo, where he ran into the same issue a lot of devtools startups face — developers were clearly evaluating products, but the commercial team had poor visibility into who they were, what they were doing, and whether that activity would turn into pipeline.

Why this team fits the problem

This isn’t a first-time founder trio. Reo.Dev has described all 3 founders as second-time entrepreneurs. Piyush previously built an AI edtech startup that was acquired by Byju’s. Gupta had already co-founded a devtools company. Gaurav Jain had been co-founder and CTO of a fintech startup. That founder-market fit matters here because Reo.Dev isn’t selling generic sales software — it’s trying to interpret highly technical behavior well enough to help software companies sell to engineers without annoying them.

Traction and early signals

Reo.Dev now serves more than 200 customers through its AI-powered GTM platform. Named customers include NVIDIA, LangChain, ElevenLabs, Couchbase, and Temporal. That’s a useful signal because these are teams selling to serious technical audiences, not companies buying vanity prospecting software.

It also says its Developer Knowledge Graph includes more than 100 million engineer profiles across over 3,000 technologies. The idea is that title-based prospecting isn’t enough when “engineer” could mean infrastructure, security, platform, AI, or developer experience. Those are very different buying contexts. On top of that graph, the startup is tracking hundreds of millions of developer activity signals to decide who’s actually in market.

The funding round

This new round brings Reo.Dev’s total capital raised to $15.3 million. Elevation Capital led the $11.3 million Series A, with Heavybit, India Quotient, Foster Ventures, and new investor Uncorrelated Ventures also participating. The round lands just 8 months after the startup announced its seed financing, which is quick by any standard.

Management says the money will go into frontier AI capabilities and faster development of AI agents. It’ll also fund global expansion. That lines up with the product direction: the company isn’t just selling better lead lists anymore; it’s trying to build a system that understands technical buying behavior before a seller is invited in.

How does Reo.Dev compare with Common Room and Demandbase?

The clearest direct comparison is with signal-heavy go-to-market software. Common Room positions itself as a broader customer intelligence platform that combines enrichment and workflow automation. It also includes CRM orchestration and AI agents in one system. Demandbase comes from the older account-intelligence and ABM side, focused on firmographic data and intent signals. It also offers account profiles and buying-committee discovery.

Reo.Dev is narrower. But that’s the point.

Instead of starting with generic account intent, it starts with developer behavior — code interactions and package installs, plus docs usage, community activity, product telemetry, and technical persona mapping. That gives it a tighter use case for devtools and infrastructure vendors, especially those selling to engineering teams where the user, evaluator, and budget owner are rarely the same person.

The trade-off is obvious too. A focused product can look smarter than a horizontal platform in its niche, but it also has to prove that niche is big enough and defensible enough to support venture-scale growth.

Why are investors backing this developer intent platform now?

Because the buying journey has shifted, and Reo.Dev is building for that shift instead of pretending outbound still starts with a job title and a cold email.

Gupta’s core argument is that software vendors need visibility into how developers evaluate products before sales ever enters the picture. Elevation’s thesis seems close to that: Reo.Dev has built a differentiated stack by combining a proprietary data layer with AI, then pointing it at one very specific problem — customer acquisition for software vendors selling into technical teams.

The new round also matters because it should push the company past “signal collection” and deeper into execution. The plan to invest in frontier AI and agent development suggests Reo.Dev wants to become more than a dashboard. If it can reliably catch both human and agent-led evaluation, then route that insight into CRM, alerts, audiences, and outreach, it starts to look less like a data vendor and more like infrastructure for technical GTM.

What market trends are pushing developer intent platforms higher?

The market backdrop is real. Grand View Research estimates the global sales intelligence market will reach $6.68 billion by 2030, growing at a 10.8% CAGR from 2023 to 2030. Reo.Dev sits inside that broader category, but with a more specialized focus on technical buying signals and enterprise software demand generation.

Buyer behavior is shifting in the same direction. Gartner said in June 2025 that 61% of B2B buyers prefer an overall rep-free buying experience, and 73% actively avoid irrelevant supplier outreach. That’s brutal if your pipeline model still depends on spraying messages at accounts with weak context. It’s a lot better if you can tell which engineering org is already testing, reading, installing, or troubleshooting around your product.

Reo.Dev is ambitious. The company is betting that the next big sales signal won’t come from a form fill. It’ll come from product evaluation happening in the background — by humans, and now by agents.

If that bet is right, this developer intent platform could become a lot more important than its funding round alone suggests.

Read how SwitchOn raised $8M in pre-Series B funding to expand DeepInspect, its AI-powered vision platform that helps factories detect defects in real time and automate quality inspection.

FAQ

• What funding did Reo.Dev raise in its latest round? Reo.Dev raised $11.3 million in a Series A round led by Elevation Capital. The financing took total funding to $15.3 million and came just 8 months after the company’s seed round.
• How does Reo.Dev’s developer intent platform work? It works by collecting developer activity from sources like GitHub and package managers, plus technical docs, product usage, and communities, then linking those signals to accounts and likely buyers. Teams can score intent and build segments. They can also sync data into CRM systems like HubSpot, and trigger automations in Slack or through webhooks.
• Who founded Reo.Dev? Reo.Dev was founded in 2023 by Achintya Gupta, Gaurav Jain, and Piyush Agarwal. Gupta had previously worked on revenue at Phyllo, Jain had fintech founder-CTO experience, and Agarwal previously built an AI edtech startup that was acquired by Byju’s.
• What market is Reo.Dev selling into? Reo.Dev sits in the sales intelligence and revenue intelligence market, but it targets a more specific slice: software vendors selling to engineers and technical teams. That niche is getting more important as B2B buyers do more self-serve research and as AI agents start participating in software evaluation workflows.

SwitchOn builds AI-powered vision systems that help factories catch defects on production lines, and the Bengaluru startup has now raised $8 million in fresh SwitchOn funding to push that bet further. Bad quality checks are still a stubborn factory problem. A lot of inspection work remains manual, inconsistent, and expensive even in highly automated plants. Founded in 2018 by Aniruddha Banerjee and Avra Banerjee, the company will use this pre-Series B round to expand overseas, invest more in R&D, and scale sales across manufacturing sectors. SwitchOn isn’t selling a generic AI tool. It’s trying to become part of the production line itself.

What does SwitchOn build for factories?

SwitchOn’s main product is DeepInspect, an AI visual inspection system built for manufacturing lines. In practice, industrial cameras capture product images on the line. DeepInspect runs defect detection models at the edge, then sends a pass-fail output back into factory controls so manufacturers can reject bad units in real time instead of spotting issues later. It’s built for shop-floor use, not just for a lab demo.

The technical setup is more specific than the source article suggested. DeepInspect supports up to 8 industrial cameras in one application and works with 1.3 to 20 megapixel cameras. It can inspect at speeds above 1000 parts per minute depending on the product and line conditions. It also integrates with industrial I/O systems from vendors like Siemens, Delta, Omron, and Mitsubishi. That matters because factory tech lives or dies on whether it plugs into what plants already run.

And this isn’t just “AI sees defect, done.” SwitchOn has built workflow pieces around the vision layer. There’s no-code setup for new SKUs. It also supports automatic SKU switching based on external triggers, along with traceability through stored inspection images and on-device analytics that let operators track rejection ratios and investigate production issues. One product update added up to 1 year of edge data retention without needing internet or cloud access, plus comparisons across lines and plants. Factory customers pay for that.

Before software like this, a lot of inspection depended on human sampling, fixed-rule machine vision, or both. After deployment, the job shifts toward 100% inspection and stored image trails. Root-cause analysis also gets faster. That doesn’t eliminate people. It changes what they do. Operators spend less time staring at repetitive defect checks and more time fixing the process behind those defects.

Who founded SwitchOn and how did it get here?

SwitchOn started in Bengaluru in 2018 after its founders saw a weird mismatch on factory floors: automation had advanced across production, but quality assurance still leaned heavily on people, sampling, and brittle rules. The company’s history frames the opening pretty bluntly. QA was still manual and error-prone, and that gap was costly enough to build a company around.

The founding story

Aniruddha Banerjee and Avra Banerjee co-founded the company and still lead it. Their focus from the beginning was manufacturing quality inspection, not a broad “AI for industry” pitch. That matters. A lot of industrial startups start wide, then hunt for a use case. SwitchOn did the opposite and picked a narrow problem first.

Why the founders fit this market

The founder profiles are unusually relevant for this category. Aniruddha Banerjee leads business and strategy, with 9+ years working on AI application architecture across Nvidia, Samsung, and Broadcom, plus 3+ patents in India and the US. Avra Banerjee leads product and technology, with 8+ years building aerospace products at Team Indus and product-development experience at Schneider Electric. That mix — enterprise tech and industrial systems — makes more sense here than a pure software background would.

Traction before this round

The company is far past pilot mode. SwitchOn serves manufacturers in consumer goods, electronics, automotive, and pharmaceuticals, and its customer list includes Unilever, Bosch, Maruti Suzuki, and ALPA. It has been deployed across more than 170 production lines in over 60 manufacturing facilities spanning 4 continents. Official materials also show the platform evolving into a hardware-agnostic system and point to 3x revenue growth during its expansion phase.

How SwitchOn is positioned against competitors

This is a real category now, not an empty niche. Global peers include Landing AI, Instrumental, and Robovision. Each approaches AI inspection a bit differently. Instrumental leans hard into cloud-based failure analysis and correlation across visual, test, and process data, especially in electronics. Robovision positions itself as a hardware-agnostic, no-code Vision AI infrastructure layer for machinery companies and manufacturers.

Legacy competition still matters too. Many plants still rely on manual inspection, random sampling, or conventional rules-based automated optical inspection systems from established machine-vision vendors. SwitchOn’s angle is that it sits closer to the line and runs at the edge. It also handles high-speed inspection and makes model setup easier for plants that don’t have in-house AI teams. That’s likely what investors are backing here: tighter integration between software and factory hardware.

What does the SwitchOn funding round say about its market?

The round itself is straightforward. IvyCap Ventures led SwitchOn’s $8 million pre-Series B round, with SIG Tattva and Trifecta Capital also participating. It follows $1.1 million in seed funding and a $4.2 million Series A, making this the company’s third major fundraise.

The money is earmarked for 3 things: international expansion, stronger research and development, and a bigger go-to-market push across manufacturing verticals. That allocation makes sense. Industrial inspection companies don’t scale just by hiring more salespeople. They need deployment tooling and line integrations. They also need model reliability and support teams that can handle very different factory environments.

Banerjee’s framing is clear: the goal is AI-driven quality systems that move factories closer to zero-defect manufacturing. It’s an ambitious line. But it’s also the only pitch that really works in this market. Nobody buys defect-detection software because it sounds futuristic. They buy it because scrap, rework, recalls, and compliance failures hurt.

There’s also a timing signal here. SwitchOn’s raise lands as physical AI keeps attracting capital, with recent activity including Hakimo’s $12 million round, Human Archive’s $8.2 million seed financing, Mowito’s $3 million pre-seed round led by Version One Ventures, and Neocambrian AI’s launch of an India-focused robotics data factory. That doesn’t mean every “physical AI” startup wins. But it does show investors are warming to startups that connect AI models to hardware, operations, and messy workflows.

Why SwitchOn funding matters for customers and investors

For customers, this round should mean a more mature product and wider support footprint. International expansion isn’t just a geography story. It usually forces a startup to harden its deployment process and document integrations better. It also pushes teams to build repeatable support models. If SwitchOn wants to sell deeper into global automotive, pharma, and electronics accounts, it won’t get away with being a clever India startup. It has to behave like industrial infrastructure.

For the product roadmap, more R&D matters because quality inspection breaks in very specific ways. New packaging reflects light differently. Camera positions shift. Defect patterns change across plants. A model that works beautifully on one line can get noisy on another. So when SwitchOn says it’s putting money into R&D, that isn’t vague. It usually means better reliability, faster setup, and fewer false positives in production.

For investors, the appeal is obvious. Inspection software sits close to measurable ROI. If a platform catches more defects and reduces manual checks, the case gets easier. Better traceability and integration with existing controls help too. A manufacturer can justify the spend without waiting years for a transformation story. That’s a cleaner thesis than a lot of industrial AI pitches.

How big is the market behind SwitchOn funding?

The macro tailwind is big enough to matter. Grand View Research projects the global AI in manufacturing market will reach $47.88 billion by 2030, growing at a 46.5% CAGR from 2025 to 2030. The same broad trend shows up in machine vision too. One 2025 market forecast pegs the global machine vision market at $15.83 billion in 2025, rising to $23.63 billion by 2030 at an 8.3% CAGR.

Why now? Factories finally have the mix of ingredients these systems need: better cameras, more connected equipment, cheaper compute at the edge, and a stronger push toward industrial automation. AI inspection also fits neatly into Industry 4.0 budgets because the pitch is concrete. Catch defects earlier. Waste less. Keep lines moving.

The latest SwitchOn funding round doesn’t guarantee the company becomes a global category leader. But it does give SwitchOn a shot at turning a proven Indian industrial product into a repeatable international business. The next test won’t be fundraising. It’ll be whether DeepInspect becomes the default quality layer on more factory lines outside India.

Read how Naturis Cosmetics raised ₹100 crore in its first institutional round to expand its beauty CDMO platform and help brands develop, manufacture, and launch products faster.

FAQ

• What is the latest SwitchOn funding round? SwitchOn has raised $8 million in a pre-Series B round led by IvyCap Ventures, with participation from SIG Tattva and Trifecta Capital. It’s the company’s third major round after $1.1 million in seed funding and $4.2 million in Series A. The new capital is meant to support overseas expansion, R&D, and broader commercial rollout across manufacturing sectors.
• How does SwitchOn’s DeepInspect product work? DeepInspect is an edge-based AI visual inspection system that uses industrial cameras and machine-learning models to detect defects directly on production lines. It can support up to 8 cameras in a single application and inspect at more than 1000 parts per minute in some setups. It also stores inspection data for traceability and analytics. That makes it useful for plants that need real-time pass-fail decisions instead of delayed quality checks.
• Who founded SwitchOn? SwitchOn was founded in 2018 by Aniruddha Banerjee and Avra Banerjee. Aniruddha’s background includes AI architecture work across Nvidia, Samsung, and Broadcom, while Avra brings experience from Team Indus and Schneider Electric, where she worked on engineering and product development. That founder mix fits industrial software that has to work in factory environments, not just in demos.
• Is SwitchOn a manufacturing AI company or a physical AI startup? It’s both, but “manufacturing AI” is the cleaner label. SwitchOn builds AI-powered quality inspection systems for factories, and because that software is integrated into cameras, controls, and production equipment, it also fits the newer physical AI bucket investors are paying attention to. That category is gaining momentum as manufacturers spend more on machine vision, industrial automation, and AI tools tied to operations.

Naturis Cosmetics makes beauty and personal care products for brands that don’t want to build their own factories, labs, and formulation teams from scratch. The company has raised ₹100 crore in its first institutional funding round, led by Sharrp Ventures, at a time when brands want faster launches but product development and manufacturing are still the bottlenecks. Founded in 2011 and led by cofounder and CEO Rahul Tandon, Naturis sits in the less glamorous part of beauty — the back end. That’s why this round matters.

What does Naturis Cosmetics actually do?

Naturis Cosmetics is a B2B product development and contract manufacturing company for skincare, haircare, fragrance, color cosmetics, body care, and personal care brands. It offers private label, white label, and OEM/ODM services. A customer can come in with a rough idea, an existing SKU that needs reworking, or a full brand brief and get support from formulation to launch.

The workflow is pretty hands-on. Naturis sources and tests raw materials. It helps choose and test packaging, develops products around market needs, runs stability and shelf-life studies, checks whether a formula meets regulatory requirements, and then supports scale-up into manufacturing. It also does the unsexy but useful work many young brands struggle with — reverse engineering, replication, and modification of existing products when a founder wants a better texture, lower cost, or faster turnaround.

That product engine is built around a 5,000 sq. ft. lab and a 20-member R&D team. Naturis works with a wide range of active ingredients, from niacinamide and hyaluronic acid to retinol, ceramides, AHAs/BHAs, peptides, and biotech-led actives. It also develops clean, vegan, cruelty-free, dermatologically tested products that comply with standards such as IFRA and EU allergen requirements.

For a customer, the difference is simple. Before a partner like this, a brand usually juggles formulators, packaging vendors, compliance consultants, and a third-party plant that may or may not care about development speed. With Naturis, that process gets pulled under one roof. Documentation, SKU planning, and manufacturing support come bundled into one operating relationship.

Who founded Naturis Cosmetics and how did it scale?

Naturis Cosmetics started in Jammu, not Mumbai hype circles

Naturis was founded in 2011 in Jammu City, Jammu & Kashmir, long before “beauty backend” became an investor theme. The company grew around a 100,000 sq. ft. manufacturing setup that includes production, R&D, QA/QC, its corporate office, and a showroom. Today, it presents itself as a Mumbai-headquartered business, with its manufacturing base still tied to Jammu — a useful mix if it wants industrial scale and closer access to beauty brands, suppliers, and investors.

Rahul Tandon brings operator DNA to Naturis Cosmetics

Rahul Tandon is the cofounder and CEO most closely associated with Naturis Cosmetics. His background is more operator than influencer — he studied at IIT Delhi, has experience in business development and operations, and worked earlier at Schlumberger. That helps explain why Naturis talks so much about process, throughput, and execution rather than trend-led branding. The wider founding group has described itself as combining 30+ years of manufacturing experience with promoters from IITs and global MNCs.

Traction, fundraising, and where Naturis sits against rivals

Naturis works with more than 50 beauty and personal care brands, including Nykaa, Pilgrim, Purplle, Colorbar, Bare Anatomy, Kay Beauty, and Asaya. It also supplies OTC and cosmeceutical products to Glenmark and Dr. Reddy’s Laboratories. On the numbers, operating revenue rose about 40% to ₹154 crore in FY25 from ₹110 crore a year earlier, while profit came in at ₹12 crore. The company has also compounded revenue at more than 50% annually over the last 4 years while staying profitable.

Sharrp Ventures led the ₹100 crore round, Naturis’ first institutional fundraise. Participants included Mirabilis Investment Trust — the family office of Infosys cofounder K. Dinesh — along with Anicut Capital, Niveshaay, Hyperscale Ventures founder Suyash Saraf, Yogesh Kabra, and angels from pharma and specialty chemicals. Entrackr reported the development earlier. Naturis plans to use the capital for a new manufacturing facility in Vapi, an experience centre in NCR, an R&D hub in Mumbai, and expansion into more beauty, personal care, and OTC categories. Tandon said the money will help Naturis “strengthen its R&D capabilities, expand manufacturing capacity” and push its broader manufacturing-platform ambition.

Competition is real, and it’s fragmented. On one side are Indian contract manufacturers like HCP Wellness, Vive Cosmetics, and NG Electro Products that also sell private-label development, custom formulation, and large-batch production. On the other side is the old-school alternative: brands piecing together separate formulators, packaging vendors, and manufacturing contractors on their own. Naturis is betting that the winning offer isn’t just cheap capacity. It’s faster formulation, broader category coverage, OTC know-how, and a tighter concept-to-counter workflow.

Why Naturis Cosmetics funding matters

This round matters because it looks like growth capital, not rescue capital. Naturis is already profitable, already supplying known brands, and already operating at meaningful revenue scale. So the new money is less about proving demand and more about expanding the machine behind it.

The Vapi facility is the clearest sign of intent. A new plant in western India can improve proximity to suppliers and customers, lift capacity, and reduce some geographic concentration around its older base. The NCR experience centre is also more important than it sounds. Beauty buyers want to test textures, packaging, fragrance direction, and sample iterations in person, not just over email and courier boxes.

The Mumbai R&D hub fits the same logic. Naturis is trying to become more than a quiet third-party manufacturer and get closer to an ODM platform that shapes product briefs earlier in the cycle. That’s where margins can improve and client stickiness can deepen. The hard part is execution. Adding buildings is easy to announce. Keeping quality, timelines, and profitability intact while adding categories is harder.

How big is the Naturis Cosmetics market opportunity?

India’s cosmetics market is already large and still expanding. One recent estimate put it at $23.86 billion in 2024, with growth to $44.63 billion by 2032 at an 8.28% CAGR. Skincare alone accounted for about 32.39% of the market in 2024, which matters because that’s one of the deepest categories for contract development and repeat formulation work.

The online channel is also changing how fast products have to be built. Online beauty and personal care is projected to grow at a 10.25% CAGR in India through 2032, while another estimate pegs the online beauty and personal care market at $6 billion in FY25 and $13 billion by FY30. That kind of growth usually benefits the brands you see on apps and marketplaces. It also benefits the factories, labs, and regulatory teams underneath them, especially when trend cycles get shorter and founders want new SKUs out yesterday.

Consumer taste is shifting, too. Clean beauty, herbal positioning, natural ingredients, and clinically backed actives are all gaining traction in India at the same time. That creates a weird but lucrative mix for manufacturers: brands want nature-led storytelling, but they also want modern efficacy claims, tested stability, safe packaging, and regulatory compliance. Companies like Naturis get pulled into that complexity by default.

Can Naturis Cosmetics become India’s beauty manufacturing winner?

Naturis Cosmetics isn’t the flashiest company in Indian beauty. That may be the point.

It already has customers, profits, and a clear use for the capital it just raised. If it can turn Vapi, NCR, and Mumbai into a tighter product engine without losing margin discipline, Naturis Cosmetics could end up being more valuable than a lot of the brands it manufactures for.

Read how Mandrake Bio raised ₹16 crore in a pre-seed round to build AI-designed gene-editing enzymes from scratch for agriculture and therapeutics instead of relying on traditional CRISPR tools.

FAQ

• What is the Naturis Cosmetics funding round? Naturis Cosmetics raised ₹100 crore in its first institutional funding round in July 2026. Sharrp Ventures led the round, and the investor list included Mirabilis Investment Trust, Anicut Capital, Niveshaay, Suyash Saraf, Yogesh Kabra, and sector-focused angels.
• How does Naturis Cosmetics work as a beauty CDMO? Naturis works as a contract development and manufacturing partner for beauty and personal care brands that want help from idea to finished product. It handles formulation, raw-material and packaging testing, stability studies, compliance work, and production across categories like skincare, haircare, fragrance, and color cosmetics.
• Who is Rahul Tandon of Naturis Cosmetics? Rahul Tandon is the cofounder and CEO of Naturis Cosmetics. He studied at IIT Delhi, has an operations-heavy profile, and previously worked at Schlumberger, which lines up with Naturis’ manufacturing-first approach.
• Is Naturis Cosmetics a D2C beauty brand? No, Naturis Cosmetics is not a consumer-facing D2C beauty label. It’s a B2B manufacturer and product-development partner that supplies brands such as Nykaa, Pilgrim, Purplle, Colorbar, Kay Beauty, and pharma companies including Glenmark and Dr. Reddy’s in OTC and cosmeceuticals.

Mandrake Bio builds AI-designed gene-editing enzymes for agriculture and therapeutics. The Bengaluru startup has now raised ₹16 crore in a pre-seed round co-led by Activate and Antler, betting that better gene editors won’t come from endlessly tweaking old CRISPR tools but from designing new proteins from scratch. That matters because a lot of today’s gene-editing work still starts with enzymes nature happened to make first, even when those tools are too large, too rigid, or awkward to deliver for crop and medical use. Founded in 2025 by Tanay Lohia and Dr. Kutubuddin Molla, Mandrake Bio is still pre-revenue. It’s already trying to build the kind of AI-plus-wet-lab loop most Indian biotech startups only talk about.

What does Mandrake Bio actually build?

Mandrake Bio is building a full-stack protein-design platform for gene editing. The workflow is pretty specific: it starts with a biological design brief — things like cell type, delivery route, edit precision, and compact size. It then runs those constraints through its internal data layer, called Mandrake Terrabase, and through sequence- and structure-aware models that generate editor candidates. Those candidates are then tested in wet-lab assays. The results feed back into the next design cycle.

That’s a very different pitch from classic CRISPR engineering. Instead of beginning with a natural enzyme and shaving off limitations later, Mandrake wants the desired function built in from day 1. The platform is “function-aware,” which means the model isn’t just throwing out protein sequences at random and hoping a few survive. It’s trained around the biological job the editor needs to do.

The company has also built the surrounding research infrastructure that makes those models useful in practice. Terrabase is its interconnected DNA-protein data system. The wet-lab side validates designed proteins in-house and through partners. That matters because protein design startups live or die on whether computation survives contact with biology. As Lohia put it, “Everybody else starts with an enzyme found in nature and then modifies it. We are building models to design these enzymes from scratch.”

Mandrake also isn’t chasing one narrow use case. Its site points to 2 early application tracks: tissue-culture-free editing of elite crops, which could cut gene-editing timelines by up to 80%, and in vivo gene therapies designed around delivery constraints from the start, with the aim of using lower doses and simpler delivery methods. That’s ambitious. It fits the company’s thesis that compact, programmable editors can outperform inherited CRISPR-era defaults.

Who founded Mandrake Bio and how far along is it?

Founded in 2025 with an AI-meets-biology thesis

Mandrake Bio was founded in 2025 by Tanay Lohia and Dr. Kutubuddin Molla. Lohia is the founder and CEO, while Molla brings the deeper biology expertise as a plant genome engineer and CRISPR scientist who guides the startup’s agricultural applications and wet-lab strategy. That split makes sense. One founder is pushing the computational and company-building side. The other understands how gene-editing tools have to behave in real plant systems, not just in a model.

Lohia’s own bio is unusually blunt for a startup website. He describes himself as a “curious generalist” who fell hard into the rabbit hole of gene editing and proteins, then started Mandrake to build hypercompact editors from scratch. It’s casual language, sure. But it explains the company’s angle. This isn’t a traditional discovery biotech trying to bolt AI onto an old workflow. It’s an AI-native protein design lab trying to rebuild the workflow itself.

Why the founders fit this problem

Molla is probably the clearer signal for market fit. His expertise is in plant genome engineering and CRISPR, which lines up directly with Mandrake’s agriculture-first push. That matters because the first commercial buyers Lohia is targeting are seed companies, not just drug developers. If Mandrake can design smaller editors that work directly in elite crop tissue, that could make plant editing faster and more usable outside research settings.

The broader team also shows what kind of company this is becoming. The roster spans computational biology and structural biology. It also covers CRISPR-Cas systems, metagenomics, AI infrastructure, and wet-lab assay development. That’s the right mix for a startup that needs model quality, biological context, and lab proof all at once.

Where the company stands today

At the time of the round, Mandrake Bio was pre-revenue and had a team of 8 employees. It plans to validate its first set of enzymes in the lab within the next 2 months — which means by September 2026 if it sticks to the stated timeline — before moving into commercial partnerships. Lohia said the first customers should be seed companies and therapeutic companies, with licensing fees forming the basic business model.

Funding, hiring, and the next milestone

Activate and Antler co-led the ₹16 crore pre-seed round, with participation from Spectrum Impact, DeVC, and angel investors Vijay Chandru, Paras Chopra, Sanjiv Rangrass, and Vatsal Dusad. The money will go into expanding Mandrake’s AI protein-design platform. It will also fund hiring across AI and wet-lab research, along with the compute and experimental work needed to validate its proteins. Lohia put it plainly: “A lot of what we build has to be tested in real lab settings.”

The next financing step is already mapped out. Mandrake plans to raise a larger round after it has initial validation data, then use that to set up its own lab and run experiments at greater scale. It’s a sensible sequence. In this kind of biotech, capital gets cheaper once the science stops being hypothetical.

How does Mandrake Bio compare with CRISPR-first rivals?

Most legacy gene-editing companies still begin with natural enzymes — usually CRISPR-derived systems or other naturally occurring nucleases — and engineer from there. Mandrake’s argument is that this approach carries too much biological baggage. Natural editors evolved for microbial survival, not for neat delivery into crop tissue or human therapeutic settings. So the startup is trying to design the editor around the application, not the other way around.

A close global peer is Profluent in the US, which is also building AI-designed gene editors and has pushed that thesis far enough to land a major collaboration with Eli Lilly. That’s useful context because it shows investors are already backing the broader idea that gene editors can be generated computationally rather than merely discovered in nature. Mandrake’s difference is more specific: it’s starting with compact enzymes and agriculture-first use cases. It plans to license into seed and therapeutic companies instead of trying to become a full drug developer itself.

Why are investors backing Mandrake Bio now?

Because this round is really about turning a thesis into data.

Mandrake doesn’t need growth capital yet. It needs proof capital. The money is going into compute infrastructure and wet-lab validation because that’s the only way to show its models can produce enzymes that actually work, not just nice-looking sequences. For early investors, that’s the inflection point worth paying for.

There’s also a practical business reason the round matters. Licensing enzymes to seed and therapeutic companies is a cleaner model than trying to build entire downstream products alone. If Mandrake can validate a first wave of editors by September 2026, it gives potential partners something concrete to evaluate. It also gives the company a much stronger case for the larger round it already expects to raise after the first lab data lands.

How big is the gene editing market Mandrake Bio wants?

It’s not a tiny niche. Grand View Research estimates the global genome editing market could reach $25 billion by 2030, and a newer forecast pegs the broader gene editing market at $39.8 billion by 2033. That kind of growth attracts a lot of startups. It also explains why investors are willing to fund infrastructure bets before revenue shows up. If better editors improve delivery, precision, or cost, they can matter across a huge stack of therapeutic and research workflows.

The agriculture side is big enough on its own to justify Mandrake’s early focus. Grand View pegs the agricultural biotechnology market at $151.23 billion in 2024, with a projected rise to $212.57 billion by 2030. The trend underneath that number is straightforward: crop developers are under pressure to produce plants that are tougher, higher-yielding, and less dependent on pesticide and fertiliser inputs. Gene editing fits that demand. What’s still missing, in many cases, are tools compact and flexible enough to make deployment easier.

Mandrake Bio isn’t being funded because it already won. It’s being funded because the next 2 months could show whether its core claim survives the lab.

Read how Fora Travel raised a $60M Series D at a $1B valuation to expand Via, its AI travel advisor platform, and modernize how independent travel advisors research, book, and manage trips.

FAQ

• What is Mandrake Bio and what does it build?
  Mandrake Bio is a Bengaluru biotech startup building programmable gene-editing enzymes with AI and protein design. It uses a workflow that starts with design constraints such as cell type and delivery route, runs those through its internal platform, and then validates candidate proteins in wet-lab assays.
• How much funding did Mandrake Bio raise?
  Mandrake Bio raised ₹16 crore in a pre-seed round announced on July 16, 2026. Activate and Antler co-led the round, with Spectrum Impact, DeVC, and angels including Vijay Chandru, Paras Chopra, Sanjiv Rangrass, and Vatsal Dusad also joining in.
• Who founded Mandrake Bio?
  Mandrake Bio was founded in 2025 by Tanay Lohia and Dr. Kutubuddin Molla. Lohia leads the company, while Molla brings plant genome engineering and CRISPR expertise that directly supports Mandrake’s early agriculture push and wet-lab strategy.
• Is Mandrake Bio an agriculture biotech company or a therapeutics startup?
  It’s both, but agriculture comes first. The company’s enzymes are being built for seed companies and therapeutic companies, though its initial commercial focus is on crop applications such as developing plants that need fewer chemical inputs or handle climate stress better.

Fora Travel is a New York startup that turns would-be travel agents into travel advisors through a software-heavy host-agency platform. That matters because the old path into travel advising is still messy. Advisors deal with disconnected tools, supplier paperwork, and too much admin instead of planning trips. Now Fora Travel has raised $60 million in a Series D led by Forerunner and Tactile Ventures at a $1 billion valuation. Founded in 2021 by Henley Vazquez, Evan Frank, and Jake Peters, the fresh capital will fund Via, its AI assistant, while also supporting hiring and expansion into cruises and flights.

What is Fora Travel and how does it work?

Fora Travel is a modern host agency. New advisors join the platform and operate as independent contractors under Fora’s umbrella. They use its industry credentials and supplier relationships, and book trips for clients through a shared infrastructure instead of building an agency from scratch. Travelers, on the other side, can work with a Fora advisor for everything from a quick hotel stay to a honeymoon or a group trip.

The workflow is concrete. Advisors search by destination or travel partner inside Fora’s booking platform and compare rates with expected commissions. They pull in client payment and loyalty details from a storage tool called The Vault, then generate itineraries or proposals they can send out in a few clicks. After that, they manage the booking inside the same portal through confirmation and trip completion. Fora says more than 180,000 hotels can be booked directly on the platform.

The research layer is where the product starts to look less like an old-school agency back office and more like vertical software. Advisors get top-booked hotel data from the broader community and price-drop alerts. They can also save lists for different client types and read first-hand advisor reviews. Fora also bundles training, live support, community access, and preferred partner relationships into the same stack. That matters in a category where people often juggle separate systems for education, quoting, supplier access, and commission tracking.

And then there’s AI. Fora’s earlier assistant, Sidekick, is a GPT-4 chatbot embedded in the advisor portal and trained on Fora’s internal resources, including hundreds of training videos, help-center articles, and partner information. The new Series D pitch centers on Via, a broader AI operating layer in beta that can handle destination research and supplier knowledge. It also helps with itineraries and proposal generation. Via appears meant to turn the earlier answer engine into something closer to workflow automation.

Who founded Fora Travel and how far has it gotten?

The founding story

Fora started in 2021 after its founders zeroed in on a simple problem: travel advising can be rewarding, but the industry makes it weirdly hard for newcomers to get in. Too many talented people wanted flexible travel work but were blocked by outdated systems and closed networks. That’s the opening Fora went after.

Why the founders fit this market

Henley Vazquez brought the travel-insider credibility. Before Fora, she worked on the founding teams of 2 Virtuoso travel agencies, served on the editorial team at Town & Country, and built a reputation as a top travel advisor with industry recognition from Condé Nast Traveler and Travel + Leisure. She’s not an outsider trying to fix travel from a slide deck.

Evan Frank brought startup and marketplace experience. He previously co-founded onefinestay, the luxury home-sharing business that Accor Hotels acquired, and later became CEO of Context Travel. Jake Peters, Fora’s CTO and CPO, came in from the product side. He previously co-founded PayPerks, which SMI acquired in 2021, and had earlier leadership roles at Blink and Infosys Consulting. It’s a credible mix.

Traction, fundraising, and competition

The company is no longer in the interesting-concept stage. Fora says its advisors have now booked more than $3 billion in travel, and the growth curve is speeding up: the first $1 billion took 3 years, the second took 8 months, and the third took only 5 months. It also says it has more than 15,000 active advisors. 97% of them are new to the profession.

On fundraising, the headline is straightforward: $60 million in Series D financing, led by Forerunner and Tactile Ventures, with Insight Partners and Thrive Capital also in the round. The deal values Fora at $1 billion and brings total funding to $138.5 million. Management says the money will deepen Via’s AI capabilities, support hiring, expand into new markets, and build out categories including cruises, flights, and enterprise investment.

Competition is where Fora gets more interesting. It isn’t really fighting Expedia head-on. It’s fighting the older host-agency model — the world of fragmented advisor tools, separate training systems, commission back offices, and consortium-dependent supplier access. Legacy hosts and advisor groups still matter a lot, especially those tied to networks like Virtuoso, Signature Travel Network, Travel Leaders Network, and Ensemble. But Fora’s pitch is that one subscription gets you the portal and training. It also includes support, community, industry credentials, and preferred partner access in one place, with a starting 70/30 split that can move to 80/20 and 90/10 as bookings grow. That’s a cleaner offer than the category’s usual patchwork — and cheaper than setups that can charge thousands just for training.

Why the Fora Travel Series D matters

This round matters because it gives Fora room to push deeper into the one part of its product thesis that could actually widen the moat: reducing advisor labor without removing the advisor. If Via can reliably handle research, supplier recall, itinerary building, and proposal drafting inside the same workflow, Fora doesn’t just save time. It makes the economics of being an advisor better, especially for people who are part-time or still building a client book.

The category expansion also matters. Cruises and flights are messy products. They involve more edge cases and more support needs. They also create more operational drag than a straightforward hotel booking. If Fora can bring those into the same software stack, it becomes more valuable to serious advisors and harder to replace with a lighter-weight host. That’s probably the real investor thesis here — not AI in travel as a buzzword, but software that makes a human service business scale better.

How big is the market behind Fora Travel?

The macro case is easy to see. U.S. travel spending reached $1.4 trillion in 2025 and generated $3.0 trillion in economic output, according to U.S. Travel. WTTC also said the United States remained the largest travel and tourism market in the world in 2025, with the sector contributing $2.63 trillion to GDP and supporting 20.4 million jobs. Fora doesn’t need to own all of that. It just needs a meaningful slice of the booking and advisor workflow layered on top of it.

The timing also isn’t random. Domestic travel spending in the U.S. stayed strong at $1.54 trillion in 2025 even as inbound visitor numbers softened, which tells you the core trip-planning economy is still huge. And on the labor side, LinkedIn ranked travel advisor as the 5th-fastest-growing job in the U.S. in 2025. That’s a helpful setup for a company trying to recruit and enable new advisors.

What to watch after Fora Travel’s $60M round

Fora Travel has already proved there’s demand for a more modern way to become a travel advisor. The next test is harder. It has to show that Via can move from beta feature to real operating system for advisors — and that categories like cruises and flights can plug into the same product without creating the old mess all over again.

Read how Rime raised a $24M Series A to build enterprise voice AI that replaces robotic IVR systems with natural-sounding, real-time conversational speech for customer support and phone automation.

FAQ

• What is the latest Fora Travel funding round? Fora’s latest round is a $60 million Series D announced in July 2026. It was led by Forerunner and Tactile Ventures, included Insight Partners and Thrive Capital, and valued the company at $1 billion. Total funding now stands at $138.5 million.
• How does Fora Travel work for new advisors? It works like a host-agency platform with a software layer on top. New advisors pay $299 per year or $99 per quarter, get access to booking tools and training. They also get supplier partnerships, an IATA number, and support, then use Fora’s portal to research trips, build proposals, and manage bookings while earning commission splits that start at 70/30.
• Who founded Fora Travel? Fora was founded in 2021 by Henley Vazquez, Evan Frank, and Jake Peters. Vazquez came from high-end travel advising, Frank previously co-founded onefinestay, and Peters led product and engineering work before and after co-founding PayPerks, which was acquired in 2021.
• Is Fora Travel a travel agency or a travel tech company? It’s basically both. Fora operates as a modern travel agency and host-agency platform, but its real differentiation is the software stack — advisor portal, booking workflow, research tools, training, and AI assistants like Sidekick and Via — that supports human advisors rather than trying to replace them.

Rime builds voice models for enterprise phone systems, and the San Francisco startup has raised a $24 million Series A to push deeper into AI-powered calls. The pitch is simple: most enterprise voice bots still sound off, pause too long, or butcher brand names and industry jargon. That’s why big companies keep clinging to old IVR setups. Founded in 2022 by Lily Clifford, Brooke Larson, and Ares Geovanos, Rime is betting that better conversational speech data — collected in its own studio, not scraped from the web — can make phone automation feel less synthetic and more useful.

What is Rime voice AI and how does it work?

Rime voice AI is a text-to-speech platform for real-time voice agents and IVR systems. A customer picks a model, chooses a voice, sends text through Rime’s API or dashboard, and gets back streaming speech designed for live phone conversations. The default choice for most new deployments is Coda, while Mist is aimed at teams that care most about speed or deterministic pronunciation behavior.

The workflow is pretty practical. Teams can connect over standard HTTPS or WebSockets. They can route traffic to the nearest regional endpoint for lower latency, and self-host or run on-prem when compliance rules demand tighter control. Rime also exposes word-level timestamps. Those matter more than they sound. They help with interruption handling, barge-in, and the kind of turn-taking that keeps a call from feeling awkward.

What removes manual work is the tuning layer around speech itself. Rime offers 600+ voices and 50+ languages and dialects. It also includes controls for accent, pace, and tone, plus tools for spelling names, numbers, and codes out loud. Mist v2 is the model built for fine-grained pronunciation control, which lines up with the company’s broader pitch: customers shouldn’t have to retrain a model every time a brand name, place name, medical term, or fintech acronym comes up on a call.

That’s where Rime is trying to stand apart. Its models are trained on full-duplex conversational speech between real people, with interruptions, laughter, hesitation, and all the messy bits that usually get cleaned out of training data. Coda is built for sub-100ms model latency when self-hosted or on-prem, and cloud deployments add roughly 25–50ms of network round-trip time across most of the continental U.S. Small gap. But it’s the difference between a voice that feels responsive and one that sounds like it’s waiting for permission to talk.

Who founded Rime and why build voice AI for enterprises?

The founding story

Rime was founded in 2022 by Lily Clifford, Brooke Larson, and Ares Geovanos. Clifford had been a Stanford PhD student in computational linguistics. Larson came in as a PhD linguist with Amazon Alexa experience. Geovanos brought the engineering and product side. Together, they set out to build speech that sounded less polished in the artificial sense and more human in the useful sense.

The company’s earliest strategic choice still explains a lot about it. Instead of scraping random audio from the internet, Rime built a recording studio in San Francisco and started collecting its own conversational dataset. That dataset became the base for models trained on spontaneous, overlapping, real-world speech — not audiobook cadence, not voiceover cadence, not demo-day cadence.

Why this team fits the category

Clifford’s background is unusually relevant for this market. She has talked publicly about studying computational linguistics and sociophonetics at Stanford before leaving to build Rime, which helps explain why the company talks so much about rhythm, stress, dialect, and trust rather than just raw speech generation. Brooke Larson’s Alexa work adds the hard-earned lesson that voice systems fail fast when they don’t understand how people actually speak.

Geovanos adds another piece that isn’t trivial. Before Rime, he was working at UC San Francisco on brain-computer interfaces for people who had lost the ability to speak. Different domain. But it suggests the founding team wasn’t coming at speech as a toy problem. They were already thinking about communication as infrastructure.

Early traction and the Series A

Rime is already live through its dashboard and API, and it powers tens of millions of conversations each month. Its customer base spans food service, healthcare, airlines, and fintech, and the startup has cited enterprise names including Mayo Clinic, Dialpad, Upstart, and Asurion. On the product side, it has also been pushing volume: the homepage says Rime powers more than 1.5 million minutes of conversation.

M13 led the Series A, with participation from Twilio Ventures, Corazon Capital, Unusual Ventures, and other existing backers. It follows a $5.5 million seed round announced on May 29, 2025. Morgan Blumberg from M13 is joining the board, and Rime has also added Rafael Valle as chief scientist after his work at Meta Superintelligence Labs and Nvidia’s applied deep learning audio research team.

How Rime plans to use the funding

Rime will use the new money to expand beyond its current team of 35, with hiring aimed at model development, engineering, and partnerships. It also marks a technical shift. The company started with separate speech-to-text, text-to-speech, and LLM components. Now it’s shifting toward speech-to-speech models to cut latency, improve turn-taking, handle background noise better, and reduce how much orchestration glue it has to manage.

Competition is crowded. On one side, you’ve got voice model developers like ElevenLabs and Deepgram. On another, infrastructure players like Vapi, Retell, and LiveKit. Then there are full-stack customer support companies like Decagon and Sierra. And hanging over all of them is the oldest incumbent in the room: IVR.

Clifford isn’t pretending the problem is solved. She said, “The voice technology is still not there to automate the vast majority of enterprise phone calls. LLMs have made it a lot easier to build voice applications that work, but they haven’t changed how it feels to interact. Talking with a voice AI agent is not the most compelling experience for the end user. It’s kinda like a new IVR, but with a better voice.”

That honesty is part of the positioning. Rime isn’t selling a fantasy about totally solved voice automation. It’s selling lower latency and stronger pronunciation control. It also has proprietary conversational data and deployment options that fit regulated environments. Blumberg put it this way: “Companies like ElevenLabs have moved into being an orchestration and the application layer, going head to head with the Sierras and Decagons of the world. I think there’s just so much more to be done technically, and Rime’s approach of pushing forward on the best model with low latency and high reliability in a regulated environment stands out.”

Why does this $24M round matter for Rime voice AI?

This isn’t just growth capital. It’s model-building capital.

Rime is using the round to hire deeper into research and engineering at the exact moment it’s trying to move from a stitched-together pipeline toward more capable speech-to-speech systems. If that works, the payoff isn’t just nicer audio. It’s less latency and smoother interruption handling. Better performance in noisy environments too. It also means less architectural overhead from coordinating too many separate models.

It also matters for customers in regulated or high-trust settings. Healthcare, fintech, and travel don’t need a fun demo voice. They need something fast, accurate, and predictable enough to sit in front of patients, cardholders, or travelers without immediately eroding trust. Rime’s on-prem and self-hosted options make that thesis more believable than a cloud-only pitch would.

How big is the enterprise voice AI market?

Pretty big already, and still climbing fast. Grand View Research estimates the conversational AI market at $17.6 billion in 2026 and projects it to reach $78.9 billion by 2033. In the narrower call center AI segment, the firm expects the market to hit $7.08 billion by 2030, growing at a 23.8% CAGR from 2025 to 2030.

The more interesting shift is structural. Enterprises are no longer buying “voice AI” as one monolithic thing. They’re picking across layers — model vendors, orchestration stacks, and application companies — while still benchmarking all of it against legacy IVR. That’s why Rime’s bet on speech quality, pronunciation, and latency matters now. Building a voice app is easier than it was 2 years ago. Building one that people don’t hate on a real customer call is still hard.

Can Rime voice AI beat IVR in enterprise calls?

Rime has a credible shot because it’s not trying to win with a generic “AI agent” story. It’s going after the parts of voice automation that still break in production — speed, pronunciation, turn-taking, and trust. If the company can turn its studio-trained data and speech-to-speech push into measurably better live calls, Rime voice AI could become an important layer in enterprise phone systems. If not, it risks becoming exactly what Clifford warned about: just a better-sounding IVR.

Read how Promom raised ₹30 crore from Fireside Ventures to expand its maternal and baby care products, grow nationwide distribution, and build feeding solutions designed for Indian mothers.

FAQ

• What funding did Rime just raise? Rime raised a $24 million Series A announced on July 15, 2026. M13 led the round, and Morgan Blumberg joined the board as part of the deal. The new financing came a little over a year after Rime’s $5.5 million seed round in May 2025.
• How does Rime’s voice AI product work? Rime gives companies a dashboard and API for real-time text-to-speech in phone calls and voice agents. Teams choose a model like Coda or Mist, configure voice and pronunciation behavior, then deploy through standard API connections or on-prem if they need tighter compliance controls. It also supports streaming output and word-level timestamps, which help live systems react naturally during interruptions.
• Who are the founders of Rime? Rime was founded in 2022 by Lily Clifford, Brooke Larson, and Ares Geovanos. Clifford came out of Stanford’s computational linguistics world, Larson previously worked on Amazon Alexa, and Geovanos brought engineering and product experience that included brain-computer interface work at UC San Francisco. It’s a founding team with real speech and language depth, not just general AI credentials.
• Is Rime a call center AI company or a voice infrastructure startup? It sits closer to the voice model and infrastructure layer than to a full outsourced contact-center platform. Rime sells the speech layer — voices, latency, pronunciation, deployment, and APIs — that other enterprise products can build on top of. That’s why its competitive set stretches from model makers to orchestration vendors, even though its core bet is still the underlying voice technology itself.

Promom makes breast pumps, bottle sterilizers, warmers, and other feeding products for new mothers. The Promom funding round has now brought in ₹30 crore, or about $3.1 million, from Fireside Ventures as the startup tries to widen its maternal and baby care range across India. Early motherhood in India is still full of product gaps, especially around feeding, comfort, and convenience, even as parents spend more on trusted baby-care brands. Founded in 2023 by Anavi Kalia, Manas Tripathi, and Aditya Srivastava, Promom began as a bootstrapped D2C business. Customer referrals did a lot of the early heavy lifting.

What does Promom sell after this funding round?

Promom is a maternal and baby care brand built around feeding and postpartum-use products, with its current lineup spanning wearable breast pumps, bottle sterilizers, bottle warmers, formula makers, and accessories. Its best-known device is the Promom Neo, a wireless breast pump that fits inside a nursing bra. It lets mothers pump hands-free instead of carrying a larger machine.

That product design choice is the whole point. Mothers can use Promom’s pump while moving around the house, working, or stepping out instead of setting aside time for a bulky pumping setup. The device uses adjustable suction and soft silicone flanges. It also has a frontal diaphragm designed to reduce pinching, while the milk collector bottle holds up to 160 ml, with 120 ml described as the optimal working capacity.

The customer workflow is simple. A mother buys the pump online, wears it inside a regular nursing bra, and can use the same unit on either side. Mothers can use two pumps together for simultaneous pumping. Promom then tries to extend beyond that one use case with a broader feeding stack that includes sterilization, warming, and formula prep.

And that’s where Promom is more interesting than a generic D2C baby brand. It isn’t selling “cute baby stuff.” It’s selling utility products that sit inside daily routines.

Who founded Promom and what’s behind the funding round?

Founding story

Promom founders Anavi Kalia, Manas Tripathi, and Aditya Srivastava launched the company in Lucknow in 2023. The company spent its first months on product research and testing, then started commercial sales in January 2024. The founders drew inspiration from their own parenting journey and frustration with breast pumps designed mainly for Western consumers rather than Indian users.

Promom cofounder and CEO Manas Tripathi described the core design problem plainly: existing products did not account for Indian breast sizes, nipple sizes, or lactation flow. That’s a very specific consumer insight.

Founder fit and early execution

Publicly available founder detail is thin, which is common at this stage, but a few signals are clear. Anavi Kalia is closely associated with the brand’s consumer-facing identity and has been described as “Chief Mom,” while her background includes content creation and education at Amity University Lucknow. In a category where trust, relatability, and community-led discovery matter a lot, that kind of founder positioning can matter as much as formal medtech credentials.

Promom also didn’t begin with institutional capital. Before this raise, it was a bootstrapped D2C business, and referrals and recommendations were central to growth. That matters because baby-care categories are brutally unforgiving. Mothers don’t keep recommending products that are annoying, unreliable, or uncomfortable.

Traction, distribution, and what investors saw

The clearest traction number so far is this: Promom says its flagship breast pump has been used by more than 1.5 lakh mothers. The company sells through its own website as well as Amazon and FirstCry. It also sells on Flipkart and has placed its breast pumps across more than 29 Cloudnine Hospitals locations. That mix matters. Marketplaces help reach. Hospital presence helps credibility, and a direct channel helps margins and customer feedback.

Now to the money. The Promom funding round brought in ₹30 crore from Fireside Ventures in what the company describes as its first institutional raise. Promom plans to use the capital to expand its product portfolio and invest in product development. It also wants to widen pan-India distribution and set up an office in Delhi-NCR while continuing logistics operations from Lucknow.

Competition and market positioning

Promom isn’t entering an empty shelf. On the legacy side, Indian parents already know global and established baby-care brands such as Pigeon and Chicco, while the broader category also includes players like Johnson & Johnson, Me N Moms, and Himalaya. Those companies give consumers familiarity, retail reach, and big-brand comfort.

There are also Indian growth brands competing for the same parent wallet. R for Rabbit raised $27 million in a Series B led by Filter Capital, while SuperBottoms and LiLLBUD have also attracted fresh capital in 2026. They don’t all overlap product-for-product with Promom, but they do compete on trust, distribution, and brand recall in the larger mother-and-baby commerce market.

Promom’s pitch is narrower and sharper. It’s focusing on feeding-related problems first, and it’s using India-specific product design rather than a broad catalog from day one. That’s a sensible place to start. The risk is whether it can keep quality high while expanding beyond its core hero product.

Why does the Promom funding round matter now?

This raise matters because it gives Promom room to stop behaving like a single-product D2C brand and start acting like a category brand. Expanding the portfolio sounds routine in startup announcements, but here it’s logical: once a mother trusts a breast pump, adjacent products like warmers, sterilizers, and other postpartum essentials become much easier sells.

It also matters because Fireside doesn’t usually back consumer brands by accident. The firm’s interest suggests it sees early motherhood as a repeat-purchase, trust-heavy segment where product performance can create durable customer behavior. Fireside principal Ankur Khaitan described early motherhood as one of the more compelling openings in consumer healthcare. That framing is telling.

For customers, the practical implication is boring in the best way: more products, more availability, and probably better offline access over time. For Promom, the next test won’t be fundraising headlines. It’ll be whether the company can keep its India-specific product edge while scaling distribution beyond the referral engine that got it here.

How big is India’s maternal and baby care market?

The category is big enough to attract real capital now. India’s baby care products market was valued at $4.82 billion in 2025 and is projected to reach about $10.62 billion by 2034, growing at a 9.17% CAGR. That’s not just a vanity forecast. It reflects a market getting deeper as organized retail expands and e-commerce penetration rises. Parents are also spending more deliberately on hygiene, feeding, and infant wellness.

India also has the demand base to support specialized brands. A recent children’s products funding report noted that the country records roughly 23 million births a year — the largest birth cohort in the world. That matters.

You can see that investor confidence showing up across the category in 2026. In June 2026, LiLLBUD raised ₹6 crore in seed funding led by Zeropearl VC. Earlier in 2026, SuperBottoms secured $5 million in a Series A1 round led by Lok Capital and Sharrp Ventures. In July 2026, Swara Baby Products — the contract manufacturer backed by FirstCry parent BrainBees — filed draft papers for a ₹1,000 crore IPO.

The public-market angle matters too. BrainBees reported a 34% year-on-year rise in operating revenue to ₹8,342 crore, while net loss narrowed 25% to ₹214 crore as it kept investing in omnichannel expansion. Put simply, parents are buying. Investors are still writing checks, and the sector is maturing past the point where only giant legacy brands get taken seriously.

What to watch after the Promom funding round

The Promom funding round looks small next to giant consumer deals, but that’s not the right comparison. What matters is whether Promom can turn one trusted feeding product into a broader maternal-care franchise without losing the product specificity that got mothers talking in the first place.

Watch three things over the next 12 months: deeper offline presence beyond hospitals, whether the company’s next products feel as focused as the pump, and whether distribution growth comes with the same referral-led trust it built while bootstrapped. If that holds, Promom could become more than a niche lactation brand. If it doesn’t, ₹30 crore will disappear fast.

Read how Open Secret raised over ₹50 Cr from Desai Brothers Group and institutional debt to expand its healthy snack portfolio, grow offline retail, and build an AI-powered supply chain.

FAQ

• What is the Promom funding round about? It’s Promom’s first institutional funding round, led by Fireside Ventures, worth ₹30 crore or about $3.1 million. The startup plans to use the money for product expansion, product development, wider distribution across India, and a Delhi-NCR office push while keeping logistics tied to Lucknow.
• How does Promom’s product actually work? Promom’s core product is a wearable breast pump called Promom Neo that fits inside a nursing bra and allows hands-free pumping. It uses adjustable suction, can be used on either side, and is part of a wider product stack that includes sterilizers, bottle warmers, formula makers, and accessories aimed at daily feeding routines.
• Who founded Promom? Promom was founded in 2023 by Anavi Kalia, Manas Tripathi, and Aditya Srivastava. The company says the idea came from the founders’ own parenting experience and a belief that products in India weren’t designed around local maternal needs, especially around breastfeeding and pumping comfort.
• Is Promom in the baby care market or maternal health market? It sits across both, but its clearest entry point is maternal and baby care products focused on feeding and postpartum utility. That’s a fast-growing category in India, with the baby care market estimated at $4.82 billion in 2025 and projected to cross $10.62 billion by 2034, which explains why investors are backing specialized brands in the segment.

Open Secret is a Mumbai-based healthy snacking brand that sells cleaner-label versions of everyday packaged foods like cookies, chips, namkeen, cereals, and drink mixes. The latest Open Secret funding round brings in over ₹50 Cr from equity and debt as the company pushes harder into offline retail, expands its savoury snacks portfolio, and starts using AI in its supply chain. That matters because Indian snack buyers don’t just want “healthy” anymore—they want familiar formats that don’t read like nutritional damage on the back of the pack. Founded in 2019 by Ahana Gautam, Open Secret has already crossed ₹200 Cr in ARR, is growing 10% month on month, and is EBITDA profitable.

What is Open Secret and what does it sell?

Open Secret takes mainstream snack formats and rebuilds them with a healthier pitch. Its catalog now spans cookies, chips, namkeen, cereals, dry fruits, nuts, protein-rich mixes, gift hampers, and a wider “unjunked” assortment that also includes products from other food brands on its platform. By 2023, it had evolved beyond a single-product brand into a broader healthy food storefront.

The brand’s original hook was Nutty Cookies. Those cookies are built around nuts rather than the usual refined-flour-heavy base. Open Secret says they contain 40% to 50% nuts, no added maida, and a mix of protein and fibre. The company also positions them as portion-controlled: each cookie has about 50 to 60 calories and roughly 1 to 2 grams of sugar, depending on the flavour.

Its savoury line is where things get more interesting. Open Secret launched what it called India’s first nutty sandwiched chips, and the brand’s FAQ lists flavour combinations like lemon chilli almond butter, choco almond butter, and spicy peanut butter. Across the range, the formulation story leans on alternatives like oat flour, jowar, nachni, rice flour, nuts, and sunflower oil instead of the usual cheap-fillers play that dominates packaged snacks.

For shoppers, that changes the buying experience in a simple way. Instead of choosing between “tasty” and “better for you,” Open Secret is trying to make the healthier option look and feel like the same pantry routine—cookies for tea time, chips for cravings, namkeen for sharing, cereals for breakfast, gifting when needed. It’s less radical than a nutrition startup selling niche wellness products.

Who founded Open Secret and how has it grown?

How Ahana Gautam started Open Secret

Open Secret was founded in 2019 by Ahana Gautam, who built the company around a blunt idea: India’s packaged snack aisle had scale, but not enough options that felt clean, modern, and family-safe. Her motivation was personal as much as commercial. Earlier reporting on the company tied that impulse to her own childhood eating habits and to a later realization, while studying in the US, that Indian retail shelves lacked the kind of healthier snack variety common in American supermarkets.

The brand’s voice still follows that origin story. Open Secret talks about “unjunking” food, not turning snacks into punishment. It’s aimed at households, especially mothers buying for families, not only gym-first consumers chasing macros.

Why Gautam looks like a credible builder here

Gautam didn’t come into food blind. She studied chemical engineering at IIT Bombay, then earned an MBA from Harvard Business School. Before launching Open Secret, she spent close to 4 years at Procter & Gamble across product supply and finance. She also worked on marketing special projects. After that, she moved to General Mills, where she worked on cereal growth channels and led the natural and organic baking business for Annie’s and Immaculate Baking. Since July 2023, she has also served as an independent board director at Godrej Tyson Foods. That’s a serious operator stack.

The early execution signals showed up fast

Open Secret didn’t stay a single-SKU story for long. In 2020, the company shared more than 1,000,000 cookies, grew over 1200%, and launched 2 new lines—nutty sandwiched chips and nutty spreads. By 2022, it had expanded into 15 categories, and by 2023 it was presenting itself as a one-stop “UnJunk” shop with 250+ products, 100+ brands, and a community figure of 15L+ families. It also says more than 50% of its workforce is made up of women.

The more current business markers are the ones investors will care about. Open Secret’s products are already sold through ecommerce, quick commerce, and physical retail. The company is present on Amazon, Flipkart, Blinkit, and Zepto, and it is stocked in more than 500 retail outlets across India. It has also crossed ₹200 Cr in ARR, is growing 10% month on month, and the business is EBITDA profitable.

Inside the new Open Secret funding round

This round mixes primary equity with debt rather than reading like a plain-vanilla VC cheque. Desai Brothers Group is putting in ₹30 Cr in primary equity, with the rest coming from institutional debt, taking the total raise to more than ₹50 Cr, or about $5.2 Mn.

The capital is being used for 3 very specific bets. Open Secret wants a much bigger offline footprint beyond its current store base. It wants to build out its portfolio harder in savoury snacks, especially chips and namkeen, which are growing fastest inside the business. It also plans to use AI across its supply chain. That promise can sound generic until a food company uses it for demand planning, replenishment, and inventory discipline.

Gautam is setting a pretty aggressive marker: “Our goal is to hit ₹1,000 Crore ARR within three years, all while maintaining our profitability. This is Open Secret 2.0.”

How Open Secret is positioned against rivals

Open Secret isn’t alone. The company is up against brands like Wellbeing Nutrition, Phab, The Whole Truth, Yoga Bar, and Snackible in India’s healthy snacking category. Those are just the startup names. The bigger fight is still against legacy packaged snack brands selling cheaper, more habit-driven biscuits, chips, and namkeen at enormous scale.

Its shelf strategy stands out. Open Secret isn’t trying to win only one health-conscious subcategory like protein bars or supplements. It’s trying to sit in the middle of everyday Indian snacking with a family-friendly reformulation pitch. That gives it a broader TAM, but it also means harder execution. Cookies, namkeen, cereal, gifting, quick commerce, and retail all behave differently.

Why does the Open Secret funding round matter?

This round matters because it doesn’t look like survival capital. It looks like acceleration capital.

A lot of D2C consumer brands spend years talking about scale before they show real operating proof. Open Secret is coming into this raise with profitability already on the table and a meaningful revenue base behind it. That changes the investor reading. The question is no longer whether consumers will buy healthier snacks online. They already are. The question is whether Open Secret can become a real national packaged food brand without losing discipline.

Offline expansion is the biggest test. Snack brands become habits when they’re seen often and bought casually, not only when somebody searches for them online. If Open Secret can move from 500+ outlets to something much deeper across modern trade and general trade, it stops being a digital-native brand with retail exposure and starts looking like a mainstream FMCG contender.

Then there’s savoury. Cookies helped build the brand, but chips and namkeen are much higher-frequency categories. Crack that, and repeat purchase gets easier. Miss it, and the brand stays stuck in occasional indulgence. The AI supply-chain angle matters for the same reason. Food brands don’t scale cleanly on branding alone. They scale when forecasting, fill rates, and inventory don’t fall apart.

How big is the healthy snacks market in India?

The market backdrop is why investors keep showing up here. One estimate puts India’s healthy snacks opportunity at $8.1 Bn by 2033. A narrower IMARC sizing places the India healthy snacks market at $3.13 Bn in 2025 and projects it to reach $4.77 Bn by 2034, with online channels growing fastest at about 6.8% CAGR. However you slice the definition, the direction is the same: more demand, more premiumization, and more room for specialist brands.

That shift isn’t random. Indian consumers are paying a lot more attention to protein, sugar, fibre, ingredient lists, and preventive health than they were even 5 years ago. Quick commerce has removed a ton of friction from trial. And rising disposable income means a larger base of shoppers is willing to pay a little extra for snacks that feel less junky and more intentional. That’s why recent funding has also gone into brands like Phab, Good Monk, and Salad Days.

What should Open Secret funding watchers track next?

The Open Secret funding story is easy to like on paper. Profitable brand. Growing category. Known operator. Fresh money for distribution and product expansion.

But the next 18 to 24 months will tell the real story. Watch whether offline expansion actually deepens repeat purchase, whether savoury becomes a meaningful share of sales, and whether the AI supply-chain push turns into better execution instead of just better wording. If Open Secret can do those 3 things, this won’t look like another D2C snack raise. It’ll look like the point where a niche brand started behaving like FMCG.

Read how Anmasa raised ₹30 crore in a seed round led by Fireside Ventures to expand its Bright Store network and scale made-to-order grocery staples processed fresh after every order.

FAQ

• What happened in the Open Secret funding round?
  Open Secret raised over ₹50 Cr in a mix of equity and debt. The structure includes ₹30 Cr in primary equity from Desai Brothers Group, along with institutional debt, and the company plans to use the capital for offline expansion and portfolio growth. It also plans AI-led supply-chain work.
• How does Open Secret make its snacks different?
  Open Secret sells familiar snack formats, but with a reformulation-first approach. Its cookies use 40% to 50% nuts and no added maida, while parts of its range lean on ingredients like oat flour, jowar, nachni, rice flour, and nut butters instead of standard low-cost fillers.
• Who is Ahana Gautam?
  Ahana Gautam is the founder and CEO of Open Secret, which she started in 2019. She studied chemical engineering at IIT Bombay, earned an MBA from Harvard Business School, worked at Procter & Gamble and General Mills, and led the natural and organic baking business for Annie’s and Immaculate Baking before returning to India to build the brand.
• Is Open Secret a healthy snacks brand or a broader packaged food company?
  Right now, it’s best understood as a healthy snacking brand expanding toward a broader packaged-food play. The core identity is still snacks—cookies, chips, namkeen, cereals, dry fruits, and mixes—but the company has also widened into a larger “UnJunk” assortment and platform model as it scales.