Category: Startup Funding News

Critical Energy builds factory-made geothermal turbines that turn underground heat into always-on electricity. The 2024 startup has now raised $19 million in seed funding because geothermal developers are running into a physical bottleneck: there aren’t enough compatible turbines in the right sizes, especially if they need them built fast instead of assembled on-site over months or years. Founder and CEO Spencer Jackson — a former SpaceX engineering leader — says the money is going toward the company’s first 2.5 MW project. It’s a small round by fusion or advanced fission standards, but a telling one for geothermal turbines.

What is Critical Energy and how do its geothermal turbines work?

Here’s the plain-English version. Critical Energy is building modular surface power units for geothermal sites, not drilling rigs and not giant custom plants. Its first product family is called Apex. Those units are factory-assembled in shipping-container modules, can be deployed one at a time or in parallel, and are meant to bring multi-megawatt power online faster than conventional geothermal plant builds.

The workflow is pretty straightforward. A project developer brings the heat source — traditional hydrothermal, enhanced geothermal, or another compatible resource — and Critical supplies the conversion hardware that turns that heat into electricity. Inside the system, geothermal heat vaporizes a specialized working fluid. That vapor spins a turbine and generator, and then the fluid condenses and circulates again in a closed loop. No fuel truck. No combustion.

The manufacturing angle is the real pitch. Critical builds the modules in a factory and ships them in standard containers. It says crews can install them with minimal on-site labor in as little as 2 weeks. That contrasts with the usual large-turbine approach in geothermal, where site-specific equipment and field assembly slow everything down.

And this isn’t just slideware. The company already built a custom turbine and integrated it into a demo system that has generated more than 50 kW in testing. That demo matters. It validates the basic loop — heat exchange, working-fluid cycling, and turbine-driven power generation — before Critical tries to jump to the first commercial-scale units.

Who founded Critical Energy, and can this team actually build it?

The founding story

Critical Energy was founded in 2024 by Spencer Jackson. Before starting the company, Jackson was an Entrepreneur in Residence at NosTerra Ventures, where he focused on low-cost clean energy ideas. His goal for Critical was simple enough: accelerate modular power-plant deployment and make clean, dispatchable energy easier to build.

That sounds broad. But the company’s wedge is narrow. It isn’t trying to solve the whole geothermal stack at once. Jackson is going after the turbine layer — the part that sits above the wellfield and converts heat into electricity. Less glamorous than drilling breakthroughs, sure. But sometimes the boring hardware bottleneck is the whole story.

Why Jackson has real market fit

Jackson spent 7 years at SpaceX, working in engineering leadership across Falcon Heavy, Starship, and the Raptor engine program. Critical’s broader team brings more than 50 years of combined SpaceX experience, plus backgrounds in aerospace, transportation, and energy hardware. That doesn’t make geothermal easy. But it does make the company’s core bet more credible, because turbomachinery, high-performance thermal systems, and rapid hardware iteration are exactly the kinds of things SpaceX people know how to ship.

The supporting cast helps too. Critical lists Steve Kohr as head of engineering. Tyler Rowan handles build and test. Pete Perrone is fractional CFO. Its advisors include Mike Matson, a BCG partner and global geothermal lead, and Greg Leveille, the former CTO of ConocoPhillips. That mix — startup hardware operators plus people who understand geothermal and oil-and-gas scale-up — is probably what investors were buying here.

Traction, fundraising, and where it sits against competitors

Critical is still early, but not pre-everything. The 50 kW demo is already running in testing. The first commercial plant using its turbines is scheduled for completion in 2027, and that initial deployment is planned for an existing geothermal site of the kind Jackson compares to Icelandic projects or The Geysers in Northern California. The company is also designing a larger 5 MW module aimed at enhanced geothermal developers such as Fervo, where hotter and deeper resources can support bigger systems.

Susa Ventures and Upfront Ventures led the $19 million seed round, with MaC Venture Capital, Susquehanna Sustainable Investments, Humba Ventures, Scribble Ventures, and Underground Ventures also participating. Critical also added $3 million in venture debt from Silicon Valley Bank, bringing total early capital to $22 million. Jackson has said he wants the company producing many gigawatts of turbines annually within 4 or 5 years.

Competition makes the story more interesting. Legacy geothermal developers already buy proven binary-cycle systems from incumbents such as Ormat, which has built 190 binary geothermal plants worldwide. Newer geothermal darlings like Fervo and Quaise are attacking the resource-access side — drilling deeper, fracturing hot rock, or repurposing existing sites — and they’ve raised far more money to do it. Critical is taking a picks-and-shovels position between those worlds. Let the drillers open up more heat, then sell them modular conversion hardware that can be manufactured repeatedly instead of custom-built every time. Peregrine Turbine Technologies is one of the few adjacent companies also pushing transportable 1 MW to 10 MW closed-cycle turbine systems.

Why are investors backing geothermal turbines right now?

This round isn’t really about a turbine in isolation. It’s about whether geothermal can scale fast enough to catch a moment when the grid suddenly needs more firm power and can’t wait for a science project. Investors are betting that Critical can move from a 50 kW proof point to a 2.5 MW operating plant without the usual hardware startup stall in between.

There’s also a timing argument in Jackson’s pitch. Advanced nuclear fission startups and fusion companies still largely point to the early 2030s for first commercial deployments, while geothermal projects are already being drilled and interconnected now. Jackson’s blunt version is that geothermal will beat them to market “by a lot.” If he’s right, a company supplying geothermal turbines could benefit from deployment curves long before the nuclear names hit their promised milestones.

The use of funds is concrete. Critical isn’t talking about vague platform expansion. The seed money is meant to get the first 2.5 MW project built, which should tell the company a lot about field installation, maintenance, module performance, and how much custom work still creeps into a supposedly standardized product. That’s what seed investors usually want to de-risk before bigger project finance or later-stage venture money shows up.

How big could the geothermal turbines market get?

The macro case is huge — maybe absurdly huge. The IEA says geothermal electricity at depths of less than 5,000 meters carries an estimated 42 TW of technical potential over 20 years of generation, and that the broader technical potential within 8 km of depth approaches 600 TW. The same IEA analysis argues geothermal’s resource base is second only to solar PV in technical electricity potential. That’s why investors have started treating it less like a niche renewable and more like a future industrial power source.

The demand side is changing just as fast. DOE says data centers’ share of total annual U.S. electricity use rose from 1.9% in 2018 to 4.4% in 2023, and projects that figure could reach 6.7% to 12% by 2028. Rhodium’s analysis goes a step further and estimates advanced geothermal could supply nearly two-thirds of new data center demand by 2030. That’s why geothermal has gone from a quiet utility topic to an AI infrastructure topic almost overnight.

There’s another structural shift here. Modern drilling is widening the map. Critical itself is designing plants that can work with traditional hydrothermal, enhanced geothermal, advanced closed-loop systems, and hot sedimentary aquifers. If drilling keeps improving — and oil-and-gas supply chains decide geothermal is worth their time — the market for surface equipment could grow much faster than the market for bespoke geothermal plants did in the past.

Will geothermal turbines beat advanced nuclear to market?

That’s still a bold claim. Hardware is hard. Geothermal project development is never clean, and a 2.5 MW first plant is not the same thing as repeatable gigawatt-scale manufacturing.

But Critical Energy is at least aiming at a real choke point. If drilling startups keep making geothermal more available, someone has to provide the conversion hardware at a speed and price the old model can’t match. That’s why this geothermal turbines round matters. Watch the 2027 project. If it works, the company’s line about a “long-term goal” of 300 gigawatts a year in 2045 will start sounding less like startup bravado and more like a manufacturing question.

Read how Pramaana Labs raised a $27M seed round led by Khosla Ventures to build AI verification infrastructure that turns legal, tax, and scientific rules into machine-checkable logic, helping enterprises trust and audit AI-generated decisions.

FAQ

• What funding did Critical Energy raise?
  Critical Energy raised a $19 million seed round, then added $3 million in venture debt from Silicon Valley Bank for $22 million in total early capital. Susa Ventures and Upfront Ventures led the equity round, with MaC Venture Capital, Susquehanna Sustainable Investments, Humba Ventures, Scribble Ventures, and Underground Ventures also joining.
• How do Critical Energy’s geothermal turbines work?
  Critical’s systems use geothermal heat to vaporize a specialized working fluid, which spins a turbine and generator before condensing back into liquid in a closed loop. The company packages that setup in factory-built Apex modules. Its demo system has already generated more than 50 kW in testing.
• Who is Spencer Jackson?
  Spencer Jackson is the founder and CEO of Critical Energy, which he started in 2024 after serving as an Entrepreneur in Residence at NosTerra Ventures. Before that, he spent 7 years at SpaceX in engineering leadership roles across Falcon Heavy, Starship, and the Raptor engine program.
• Is Critical Energy a geothermal developer or a turbine supplier?
  It’s primarily a turbine and modular power-plant supplier, not a drilling company. That puts it in a different lane from geothermal developers like Fervo or Quaise, which focus more on opening up the underground resource. Critical focuses on the surface hardware that turns heat into grid power.

Pramaana Labs builds software that turns messy legal, tax, and scientific rules into machine-checkable logic, so AI systems can show why an answer is valid instead of just sounding confident. On June 17, 2026, the startup raised a $27 million seed round led by Khosla Ventures for that mission. The pitch is simple: enterprise AI keeps stalling when the cost of a wrong answer is too high. Pramaana was formed in 2025 by CEO Ranjan Rajagopalan, CTO Krishnan Raghavan, and chief scientist Sanjay Ganapathy, and it’s trying to solve that trust problem with formal verification rather than better prompting.

What is Pramaana Labs and how does it work?

Pramaana’s core product is a “Domain Formalizer” that converts regulatory text, statutes, contracts, policies, and scientific material into formal specifications a machine can verify. Instead of asking an LLM to freestyle over raw text, the company first maps definitions and exceptions. It also maps conditions, dependencies, and source references into a structured representation. That’s the crucial move. It changes the job from text generation to rule-bounded reasoning.

The workflow has 3 stages. First, Pramaana formalizes domain knowledge. Then it constrains what the AI is allowed to say, keeping outputs inside logical boundaries and surfacing uncertainty instead of burying it. Last, it verifies the result through self-consistency checks and proof validation, returning proof artifacts that domain experts can inspect later. That’s a lot more concrete than a confidence score.

Pramaana still uses a conventional LLM. But it places a deterministic layer on top, which Rajagopalan says matters in rule-heavy fields. Pramaana’s technical stack draws on formal verification ideas associated with the open-source LEAN language, and Rajagopalan has pointed to France’s CATALA project as proof that tax and benefits rules can be translated into executable logic.

Its first visible wedge is tax. Pramaana says the product can formalize tax codes and detect cross-rule conflicts. It can also simulate policy changes and automate tasks such as taxability decisions, nexus analysis, exemptions, and credits. On the sales-and-use-tax side, it’s explicitly targeting the advisory work companies still hand to outside specialists — a spend band it pegs at $25,000 to $500,000 a year. That’s smart. If it works, Pramaana isn’t replacing chatbots. It’s replacing expensive review loops.

Who founded Pramaana Labs and why now?

The founding team

This isn’t a random trio chasing the latest AI funding cycle. Rajagopalan is an IIT Madras alumnus who previously co-founded Astra and worked at Google and Graviton on high-performance systems, ML models, and automated content moderation pipelines. Raghavan built Glean’s India search team and helped develop its enterprise conversational AI after a stint as a staff software engineer at Google. Ganapathy came from Google DeepMind, where he worked on Gemini’s tool-use system and post-training. That mix — search, infra, frontier models, and formal methods — is why investors took this seriously at seed.

Why this problem fits them

Rajagopalan’s thesis is that high-stakes domains are easier to formalize than a lot of consumer AI tasks because they already run on rules and thresholds. Exceptions and precedent are part of the structure. He made that case using tax law, arguing that once those rules are codified, the reasoning layer becomes far more deterministic. That’s not a small claim. But it’s also not vague founder poetry. It matches the product architecture Pramaana is already showing publicly.

Early signals

Pramaana already has a live product, and its first vertical focus is tax and statutory reasoning. The company is also leaning hard on domain oversight rather than pretending model quality alone is enough. For tax law, it’s working with former IRS commissioner Danny Werfel. For cybersecurity and drug discovery efforts, professors from IIT Delhi, IIT Madras, and UC Berkeley are involved in supervising the formal systems.

Fundraising details

Khosla Ventures led the $27 million seed round, with Accel, BoldCap, Nexus Venture Partners, Premji Invest, and Unbound also participating. That’s a very large seed by any standard, and it tells you investors see Pramaana less as another AI wrapper and more as foundational infrastructure for regulated AI deployments. The company hasn’t disclosed earlier financing, so this round is the first major outside capital attached to the public launch.

How does Pramaana compare with AI guardrail rivals?

In practice, Pramaana will run into 2 kinds of rivals. One group sells monitoring and observability layers for LLM apps. It also sells evaluation tools. Companies like Arize and Patronus help teams trace outputs, benchmark models, define custom error taxonomies, and add production guardrails. Those tools matter, but they mostly inspect behavior after or around generation.

The other group is closer to Pramaana’s technical ambition: proof-first AI shops such as Harmonic, which is using formal verification in math reasoning. Pramaana’s difference is domain focus. It isn’t starting with olympiad math or generic model evals. It’s starting where enterprises already pay humans to interpret rules — tax, law, compliance, clinical safety, and research workflows. And the legacy incumbent isn’t software anyway. It’s expert review, outside counsel, and advisory teams billing for certainty.

Why are investors backing this verifiable AI startup now?

Because enterprises are done with AI demos that can’t survive audit.

That’s the short version. The longer one is that Pramaana is attacking a bottleneck that shows up after the pilot phase. Lots of companies can get an LLM to answer a question. Far fewer can put that answer into a tax workflow, legal memo, or clinical support system and defend it later. Pramaana’s architecture is built for that second step, which is where actual budget lives.

Khosla’s involvement also makes sense at the thesis level. This is a hard-technology bet on infrastructure, not an app-layer sprint. Pramaana is trying to build a verification layer that other mission-critical AI systems could sit on top of. If that layer works in tax, it can expand into adjacent domains that are equally rule-dense and equally expensive to get wrong. That’s a stronger venture story than “here’s another assistant.”

The timing isn’t accidental. Pramaana surfaced publicly just as agentic AI conversations shifted from “can it do the task?” to “can anyone trust the output chain?” That shift favors startups that can give customers an audit artifact, not just a probability. Investors are betting that proof beats vibes once real liability enters the room.

How big is the market for auditable AI?

The nearest public market category isn’t “formal verification for AI” yet. It’s explainable, transparent, and auditable AI. Grand View Research estimates the global explainable AI market at $7.79 billion in 2024 and projects it to reach $21.06 billion by 2030, an 18.0% CAGR from 2025 through 2030. That’s not Pramaana’s exact box, but it’s a good proxy for buyer demand around transparency and proof.

Technavio puts the AI explainability and transparency market at $8.89 billion in 2025, growing at a 16.6% CAGR through 2030. More interesting than the raw number is the buyer behavior behind it: the firm says over 80% of organizations in regulated sectors treat technical accountability as a top priority, and it describes a broader shift from static audits to automated, real-time observability that can cut validation times by more than 40%. That’s basically the macro tailwind behind Pramaana’s pitch.

There’s also a structural reason this category is getting serious now. Models are getting more agentic and more multimodal, which makes old-school manual review slower and less useful. At the same time, more enterprise AI is crossing into domains where a wrong answer isn’t just embarrassing — it can create a tax exposure, a compliance issue, or a clinical risk. That’s where “explainability” starts to feel too soft, and “verifiability” starts sounding like the real budget line.

What to watch next for Pramaana Labs

Pramaana Labs has raised enough money to be judged on execution, not just originality.

The company’s idea is genuinely interesting. It also happens to be brutally hard. Formalizing real-world rules is slow, expert-heavy work, and the jump from a compelling tax demo to a repeatable enterprise product won’t be easy. But if Pramaana can show that its proof-first system saves customers time without forcing them to recheck everything by hand, this seed round will look cheap. Rajagopalan’s line from launch is the right standard to hold the company to: “The world’s hardest problems are not unsolvable. They are unformalized.”

Read how Atom XVII Fund launched a ₹75 crore consumer-focused investment fund to back pre-seed to Series A startups across India, targeting underserved consumer brands and founders beyond major metro markets with early institutional capital.

FAQ

• What funding did Pramaana Labs raise? Pramaana Labs announced a $27 million seed round on June 17, 2026. Khosla Ventures led the deal, and Accel, BoldCap, Nexus Venture Partners, Premji Invest, and Unbound joined in.
• How does Pramaana Labs work? It works by translating legal, regulatory, and scientific text into formal machine-readable representations before an AI system reasons over them. The stack then constrains outputs and verifies claims with proof checks, so customers get something closer to an audit trail than a chatbot answer.
• Who founded Pramaana Labs? The company was formed by Ranjan Rajagopalan, Krishnan Raghavan, and Sanjay Ganapathy. Their backgrounds span Google, Glean, and Google DeepMind, which gives Pramaana unusually strong technical credibility for a startup trying to combine LLMs with formal methods.
• What market is Pramaana Labs in? It sits in the emerging market for auditable enterprise AI, overlapping with explainable AI, AI governance, and AI verification infrastructure. That broader explainable AI market is already measured in the high single-digit billions and is projected to roughly triple toward 2030, which helps explain why investors are paying attention to verification-first startups now.

Atom XVII is a new early-stage investment fund built to back India’s consumer startups from pre-seed to Series A. The Atom XVII Fund has launched as a Category II Alternative Investment Fund with a target corpus of ₹75 crore. It’s betting that many fast-growing consumer businesses still struggle to find organised early-stage capital once you move beyond the obvious metro deals. The fund was founded in 2026 by Harsh Kapadia, a Chartered Accountant and Oxford MBA, and it’s aiming for its first close by the end of July 2026.

That’s the headline. But the real story is smaller and sharper. Atom XVII isn’t trying to be a giant multi-stage platform. It wants to be a focused first institutional partner in consumer categories where bigger funds may show up later, not first.

What does Atom XVII Fund actually do?

At a basic level, the Atom XVII Fund pools money from limited partners into a SEBI-regulated Category II AIF and plans to deploy that capital into 13 to 15 consumer startups, typically with an average cheque size of ₹3 crore. Its sweet spot runs from pre-seed to Series A. That’s the stage where founders usually need conviction capital, not just introductions and enthusiasm.

Its investment map is narrow on purpose. Atom XVII is focused on India’s consumer sector, especially fast-growing segments that haven’t seen enough specialist early-stage money and businesses building outside Tier 1 cities. The fund also plans to co-invest with other managers that share the same view on India’s consumer opportunity. That makes it less of a lone-wolf vehicle and more of a specialist partner that can slot into syndicates.

That Category II tag matters more than it sounds. Under SEBI’s AIF rules, Category II funds sit in the private equity and venture bucket and aren’t supposed to use leverage beyond day-to-day operational needs. For founders, that mostly translates into a more standard institutional setup. For LPs, it means Atom XVII is being built inside a familiar Indian venture structure rather than as an informal angel club with a nicer logo.

And the fund hasn’t waited for paperwork theatre to end before moving. It has already led a ₹3 crore bridge round in Nothing Before Coffee, a brand that was previously part of Kapadia’s personal portfolio. It’s also close to signing a second deal in athleisure fashion. That tells you what Atom XVII wants to be known for: quick, category-specific capital in consumer brands that are already showing enough life to justify an early institutional round.

Who is Harsh Kapadia and why launch Atom XVII Fund?

How Atom XVII got started

Atom XVII comes out of a pretty clear founder thesis. Kapadia had already been investing personally before formalising the vehicle, and one of those prior bets — Nothing Before Coffee — became the fund’s first warehoused investment before the formal first close. This isn’t a case of a first-time manager launching a fund and then starting to hunt for ideas. The ideas were already in motion.

Why Kapadia fits this market

Kapadia’s resume is unusually operator-adjacent for a micro consumer fund manager. He started at PwC, where he trained in audit and worked on clients including Barclays Bank. After qualifying as a CA, he moved into financial due diligence and restructuring at Alvarez & Marsal. There, he worked on projects involving firms such as Blackstone, Brookfield, and Paragon Partners.

Later, he joined Multiples Alternate Asset Management, where he was part of the build-out of the firm’s consumer-tech portfolio. An Oxford profile published during his MBA notes that he worked on the restructuring of Essar Steel. Very different work, sure, but the kind that sharpens judgment around capital structure, business stress, and what actually breaks companies. He also holds a commerce degree from the University of Mumbai alongside his Oxford MBA.

That background matters because consumer investing in India isn’t just about spotting a cool brand on Instagram. It’s a grind of unit economics, channel discipline, repeat behavior, and timing. Kapadia’s mix of due diligence, restructuring, private-market investing, and personal angel exposure gives him a more forensic lens than the typical “I like brands” pitch. That doesn’t guarantee returns. But it does make the thesis credible.

Early signals and fundraising details

On fundraising, Atom XVII is targeting ₹75 crore and is working toward a first close by the end of July 2026. It has already secured soft commitments of ₹40 crore. Safari Commercials Private Limited is anchoring the vehicle, while Mohit Mutreja of the Alphagrep Group is among the limited partners named so far.

For a debut fund, those numbers are decent. Not massive. Not supposed to be. A ₹75 crore corpus is small enough to stay disciplined and large enough to build real ownership in a tightly selected portfolio. Because the fund is already deploying before first close, the early test won’t be brand-building. It’ll be whether those soft commitments convert and whether the second deal closes on schedule.

How is Atom XVII positioned against other consumer VCs?

India already has specialist consumer investors, so Atom XVII isn’t entering an empty market. Fireside Ventures has been focused on early-stage consumer brands since 2017. Sauce manages about ₹1,600 crore across 6-plus funds and more than 32 investments. DSG Consumer Partners has been around since 2012 and was built as a consumer-only institutional platform for India and Southeast Asia, usually investing up to $5 million.

So where does Atom XVII fit? The honest answer is that it’s going smaller and earlier. Probably more niche too. Its ₹3 crore average cheque, 13-to-15-company portfolio plan, and explicit focus on underserved consumer segments beyond Tier 1 cities suggest a sourcing strategy built around deals that may be too early or too regionally messy for larger branded consumer funds to prioritise. That’s an inference, not a disclosed line from the fund. But it follows pretty directly from the structure and the peers it’s up against.

Why does the Atom XVII Fund launch matter for founders?

For founders, the useful part of this launch is speed and fit. Consumer startups often get stuck in an awkward zone where angels are too small, generalist seed funds don’t fully understand the category, and larger consumer specialists may want more traction before writing a first cheque. Atom XVII is trying to sit right in that gap.

Its first deal is a bridge round, which is revealing. Bridge capital is usually less about headline valuation and more about timing — buying a company enough runway to prove the next milestone. If Atom XVII keeps doing those deals, it could become useful not because it writes the biggest cheques, but because it moves when founders actually need conviction.

The LP lineup matters too. Safari Commercials coming in as anchor and Mohit Mutreja joining the LP base give a first-time manager some immediate signal value. In early-stage venture, that kind of backing doesn’t just help fundraising. It helps with access. Founders, co-investors, and later-stage funds all care about whether a new manager can bring more than cash.

Atom XVII’s co-investment stance also makes practical sense. Most consumer brands don’t scale on one fund’s balance sheet alone. They need a sequence of capital. Seed, bridge, pre-Series A, then larger growth rounds if things click. A small specialist fund that’s happy to work alongside like-minded investors can punch above its corpus if it becomes a trusted early filter.

How big is the market Atom XVII Fund is chasing?

The macro case is easy to understand. India’s retail sector was valued at about $1.06 trillion and is projected to reach $1.93 trillion by 2030, while contributing more than 10% of GDP and employing nearly 8% of the workforce. That’s a big enough base to support lots of narrowly focused consumer funds, if they can pick the right pockets.

The more interesting part is where demand is shifting. Deloitte’s consumer data says Gen Z alone accounts for 43% of total consumption in 2025 with direct spending power of $250 billion. Online marketplaces now influence 73% of purchase decisions. India’s D2C market crossed $80 billion in 2024 and is on track to exceed $100 billion in 2025. More than 60% of e-commerce transactions now come from Tier II and Tier III cities. That last figure lines up almost perfectly with Atom XVII’s beyond-metros pitch.

The capital backdrop is big too. As of December 31, 2025, SEBI data showed Category II AIFs with ₹11,64,118 crore in commitments raised, ₹4,24,964 crore in funds raised, and ₹3,84,169 crore in investments made. So Atom XVII is launching into a market where the regulatory wrapper is already mainstream. The challenge isn’t whether the AIF structure works. It’s whether a new manager can stand out inside a very crowded one.

What to watch after Atom XVII Fund’s first close

The next checkpoint is simple: first close by the end of July 2026, followed by that second athleisure investment. If both happen cleanly, Atom XVII will look less like a launch announcement and more like a manager with a real pipeline.

The Atom XVII Fund story matters because ₹75 crore is small enough to miss at first glance. But if Kapadia can turn a focused fund into a reliable first cheque for under-served consumer founders, its size may matter less than its hit rate. Watch the conversion of soft commitments into hard capital. And watch whether the fund keeps finding good brands outside the usual metro echo chamber.

Read how CREST raised a $3.1M pre-seed round to build a tech-enabled fractional family office that helps ultra-rich founders, business owners, and institutions manage investments, governance, succession planning, and reporting through a single integrated platform.

FAQ

• What is Atom XVII Fund? Atom XVII Fund is a new India-focused consumer investment fund registered as a Category II AIF. It plans to invest from pre-seed to Series A and write average cheques of about ₹3 crore. It also plans to build a portfolio of 13 to 15 startups rather than spray money across dozens of names.
• How much money is Atom XVII Fund raising and who is backing it? The fund is targeting a corpus of ₹75 crore and is aiming for its first close by the end of July 2026. It has soft commitments of ₹40 crore so far, with Safari Commercials Private Limited as anchor and Mohit Mutreja of the Alphagrep Group among the named limited partners.
• Who is Harsh Kapadia? Harsh Kapadia is the founder and manager behind Atom XVII Fund, and he comes with a mix of finance, diligence, and buyside experience. Before launching the fund, he worked at PwC, Alvarez & Marsal, and Multiples Alternate Asset Management. He also earned an MBA from Oxford after qualifying as a Chartered Accountant in India.
• Why are investors launching consumer-focused funds in India now? Because the consumer market is getting bigger and more distributed at the same time. India’s retail sector is projected to reach $1.93 trillion by 2030. D2C spending has already crossed $80 billion, and Tier II and III cities now generate more than 60% of e-commerce transactions. That creates room for specialist investors who understand demand outside the usual metro playbook.

CREST is a Mumbai-based wealth management startup building a fractional family office for ultra-rich founders, business owners, and institutions. The CREST family office has raised $3.1 million, or ₹29.3 crore, in a pre-seed round as it tries to turn a very old, very relationship-driven business into something more structured and tech-enabled. Wealthy Indian families increasingly want one partner to coordinate investing, succession, reporting, and governance instead of stitching together banks, lawyers, tax advisors, and brokers on their own. CREST was founded in 2025 by ex-LEAP India VP Zuhaib Khan and former Welspun One co-chief investment officer Girish Singhi.

What does CREST family office actually do?

At a basic level, CREST sells a fractional family office. It tries to provide the kind of strategic layer a dedicated family office would offer—investment oversight, planning, governance, and reporting—without asking every client to build a full in-house setup. Its public materials show 3 visible operating pieces: family office services, a SEBI-registered investment advisory practice, and a portfolio management service for public-market investing.

The workflow is more concrete than the vague “wealth platform” label suggests. CREST’s planning pages describe a 3-step process: discovery, where it maps a client’s financial picture and family dynamics; structuring, where it designs a framework around protection, growth, and liquidity; and stewardship, where it keeps updating the plan as life and markets change. On the family office side, the firm frames the relationship as an initial consultation, followed by strategic design, then an ongoing partnership with regular oversight and reporting.

The investment engine is also fairly specific. CREST’s PMS materials describe equity, balanced, and thematic strategies, with a filtering funnel that starts from 6,000-plus listed companies. It narrows to 1,200 on quality, then 300 on valuation, then 80 for deep research, before landing on 20 to 25 final holdings. Portfolio construction runs on research and allocation. Continuous review, position caps, and sector diversification are built into the process. That’s a lot more institutional than the usual relationship-manager model wealthy clients often get from legacy distributors.

For the client, the appeal is simple. Instead of handling public-market allocation in one place, estate planning in another, and governance conversations nowhere at all, CREST is trying to bundle the whole stack. Singhi summed up the pitch as “everything a family office does, in one place.” And because the platform is invite-only and referral-led, it’s aiming for a curated, high-trust customer experience rather than a mass affluent play.

Who founded CREST family office and what experience do they bring?

The founding story

CREST came out of stealth in June 2026, but the company traces its founding to 2025. Khan and Singhi started it around a pretty obvious gap: India has more founder wealth, more business-family liquidity events, and more cross-border complexity than ever, yet much of the advisory market still runs on product distribution, fragmented service providers, or old private-banking relationships. CREST’s answer is a fractional family office aimed at India’s “top 0.01%,” working mainly with founders, business owners, and what it calls value creators across Asia.

Why the founders fit this market

Singhi looks like the investing half of the founding story. CREST’s leadership profile says he has 16-plus years across private equity and public capital markets, has raised and deployed more than $3 billion across asset classes, has built and scaled asset management platforms, and has advised large single-family offices. Before CREST, he was co-chief investment officer at Welspun One.

Khan brings a different angle. CREST’s bio says he has 16-plus years of entrepreneurial experience across Asia, Europe, and Africa, plus buy-side M&A experience, due diligence expertise, and angel investments across 57 startups. The source article ties that to his earlier role as a VP at LEAP India, while another profile lists him as vice president for international expansion at Leap Scholar. Both founders are listed as FMS Delhi alumni on CREST’s leadership page.

Early traction and fundraising

CREST is live, not just conceptual. The company launched initially with asset allocation services, and its current public setup shows active family office services alongside a registered investment advisory arm and a PMS business. Its RIA registration is valid from August 7, 2025. LinkedIn places the team in the 11-50 employee band. That’s meaningful for a firm that’s still at pre-seed stage and only recently stepped out of stealth.

On the money side, CREST raised $3.1 million in pre-seed funding led by Atrium Ventures, BEENEXT, DeVC, Sparrow, Shastra VC, Warmup Ventures, and 91ventures. More than 40 angel investors also joined, including Amit Ranjan of SlideShare, Chirag Taneja of GoKwik, Revant Bhate of Mosaic Wellness, and Shantanu Deshpande of Bombay Shaving Company. The company will use the capital for its tech platform, family office and investment hiring, compliance depth, and new asset management offerings across Indian and global public markets plus real estate.

Who CREST competes with

This isn’t a greenfield market. Waterfield Advisors has spent years positioning itself as an independent multi-family office and pure-advisory alternative to bank-led wealth management, while Julius Baer has a much bigger global private-bank machine and an India-focused family office playbook. Then there’s the broader set of private banks, distributor-led wealth desks, and boutique advisors already serving HNIs and UHNIs.

CREST’s pitch is narrower and a bit more pointed. It says the model is fiduciary-first, retrocession-free, and incentive-aligned, with buy-side teams acting almost like outsourced CIO, CFO, and COO functions for wealthy families. If that works, the edge isn’t just better investment advice. It’s tighter coordination across wealth, operations, governance, and succession. Basically, the messy stuff that gets ignored until a liquidity event or family transition forces it into view.

Why does the CREST family office round matter?

Pre-seed money into a wealth-management startup isn’t just a branding exercise. In CREST’s case, the check will fund the least glamorous parts of the business: compliance, regulatory muscle, hiring, and the internal systems needed to manage sensitive client relationships. That matters because family office clients don’t forgive operational mistakes. One weak control process can kill trust fast.

The round also suggests investors think founder wealth is becoming its own venture category. A lot of startup wealth in India used to exit into a private bank, a distributor, or a loose circle of advisors. CREST is betting that a new class of wealthy operators wants something more organized and more aligned—especially after liquidity events, secondary sales, or business restructurings. It’s a real thesis. It’s also a hard one to execute.

There’s another signal here. CREST isn’t stopping at advisory. Its roadmap points toward broader asset management in public markets and real estate. If it can win the right families early through planning and allocation, it can later move up the value chain into higher-ticket investment mandates.

How big is India’s family office market?

The raw demand story is big. The source article pegs India at more than 9 lakh millionaires, with that number expected to nearly double by 2030 alongside $2.4 trillion in new financial wealth. UBS’s 2025 wealth report adds another datapoint: India added about 39,000 new dollar millionaires in 2024 alone, a 4.4% jump year on year.

The family office category is also maturing quickly. Julius Baer’s India family office playbook says the number of family offices in India rose from 45 in 2018 to nearly 300 in 2024. It also estimates roughly 13,000 ultra-high-net-worth families today, growing to 19,000 by 2028, with about $1.3 trillion set to change hands through intergenerational transfer over the next decade.

And the money isn’t sitting idle. Domestic family offices have backed more than 230 Indian startups so far, and Mumbai alone has seen around 62 family offices participate in startup funding. So this market isn’t only about wealth preservation anymore. It’s also about alternatives, direct bets, governance, and figuring out how to professionalize family capital before complexity outruns the family itself.

Can CREST family office stand out?

CREST family office is going after a real problem, and the timing makes sense. India’s wealthy founder class is getting larger, family structures are getting more complex, and the old distributor-heavy model doesn’t look great when clients want one place to manage capital and continuity.

But this is still a trust business first and a tech business second. If CREST can turn its invite-only, white-glove promise into a repeatable operating model—without sliding into the same product-selling habits it criticizes—it could build a sharp niche in India’s modern family office market. If not, it’ll just be another boutique with a polished website.

Read how SolarSquare raised a $53M Series C led by B Capital to expand its residential rooftop solar platform, helping homeowners navigate financing, subsidies, installation, and energy management through a full-stack clean energy service.

FAQ

• What funding did CREST raise? CREST raised $3.1 million, or ₹29.3 crore, in a pre-seed round announced on June 16, 2026. Atrium Ventures, BEENEXT, DeVC, Sparrow, Shastra VC, Warmup Ventures, and 91ventures led the round, with more than 40 angels joining as well.
• How does CREST family office work? CREST works like a fractional family office that combines planning, advisory, and investment management under one umbrella. Its process starts with discovery, moves into structuring around growth, liquidity, and protection, and then shifts into ongoing stewardship. Its investment arm runs PMS strategies across equity, balanced, and thematic portfolios.
• Who are the founders of CREST? CREST was founded in 2025 by Zuhaib Khan and Girish Singhi. Khan brings M&A, due diligence, international operating experience, and angel investing exposure, while Singhi brings deep experience from private equity, public markets, and asset management, including his earlier role at Welspun One.
• Is CREST in wealth management or asset management? It’s in both, which is part of the point. CREST started with asset allocation services, but its public setup now spans family office services, registered investment advisory, and portfolio management. That puts it in the overlap between wealth management, family office advisory, and early-stage asset management.

SolarSquare is a residential rooftop solar company that designs, installs, finances, and maintains home solar systems in India. SolarSquare Series C has brought in $53 million led by B Capital, taking the startup’s total funding to more than $100 million. The problem it’s chasing is pretty obvious: for a lot of homeowners, rooftop solar still feels like a maze of vendor calls, subsidy paperwork, financing confusion, and uncertain after-sales service. Founded in 2015 by Shreya Mishra, Neeraj Jain, and Nikhil Nahar, the company has powered more than 50,000 homes and is running at an annualized revenue pace of over ₹1,000 crore.

What is SolarSquare and how does it work?

At a basic level, SolarSquare sells a full-stack rooftop solar service for homeowners. It starts with a free consultation and rooftop survey, then moves into a personalized 3D system design. It handles installation and subsidy paperwork, then stays on for monitoring and maintenance after the system goes live. That’s a lot closer to a consumer-tech workflow than the old-school solar EPC model most buyers are used to.

The company has built the experience around removing friction at each step. A homeowner doesn’t just get panels and an inverter. They get site measurement and design engineering. Installation comes with chemically anchored mounting structures. The company also helps with the subsidy application and disbursement process. SolarSquare sells both on-grid and off-grid options, which matters in a market where power reliability and state-level economics can vary a lot.

Financing is a big part of the pitch. SolarSquare offers EMI plans and collateral-free loan support through partner institutions. It also offers consumer-friendly structures including quick loan approvals, a 6-month interest-free EMI option, and longer-tenure installment plans. On its site, it pitches a near-zero upfront path where subsidy support can cover the down payment and monthly savings help offset EMIs. For a category that still scares people with capex shock, that isn’t a side feature. It’s core product design.

Then there’s the software and service layer. SolarSquare gives customers a real-time monitoring app to track power generation and savings. It also tracks promised-versus-actual output. The company pushes a branded guarantee product called GoodZero, which includes a money-back promise pegged at ₹8 per unit, plus proactive maintenance and a free 5-year annual maintenance contract. And yes, the physical install details are part of the sales story too. The company says its systems are built to withstand wind speeds up to 170 kmph.

Who founded SolarSquare and how did it reach Series C?

SolarSquare started in 2015, and its origin story ties back to a group of solar enthusiasts from IIT Bombay who wanted to make rooftop solar easier to buy and trust. The founding team is Shreya Mishra, Neeraj Jain, and Nikhil Nahar. The company’s early framing still explains the strategy now: organize a messy category, make the unit economics work, and build trust where the market had mostly offered fragmented local service.

Founding story and market fit

Mishra brings a mix of consulting and startup operating experience that makes sense for this category. She studied mechanical engineering at IIT Bombay, started her career at Boston Consulting Group, and later co-founded fashion-rental startup Flyrobe before moving full-time into clean energy. That background helps explain SolarSquare’s consumer-brand angle — it doesn’t sell solar like a contractor first. It sells it like a decision that needs trust, design clarity, and financing confidence.

Jain’s background is more finance-heavy. He studied electrical engineering at IIT Bombay and worked in Deutsche Bank’s special situations group, where he was exposed to private equity, M&A, and sectors including renewables. Nahar comes from a more technical and operating side, with prior experience at Panasonic India and training in electronics, telecommunications, and IT management. Together, the trio covers consumer strategy and capital discipline. It also covers technical execution.

Traction and fundraising

The company isn’t early-stage in the usual sense anymore. SolarSquare has installed systems across roughly 50,000 homes, manages India’s largest portfolio of residential solar assets, and operates at an annual revenue run rate above ₹1,000 crore. Its site also shows a footprint across 29 cities and a team of more than 1,000 people. This is already a fairly heavy operations business, not just a lead-gen layer sitting on top of third-party installers.

B Capital led the fresh Series C round of $53 million, with Lightspeed, Elevation Capital, Lowercarbon Capital, Rainmatter, and Good Capital participating. Before this, SolarSquare raised $40 million in a Series B round in December 2024 led by Lightspeed, with Lightrock, Elevation Capital, Lowercarbon Capital, Rainmatter, and Gruhas Proptech also joining. The new capital will go into city expansion and technology. It will also fund hiring and a broader home-energy offering that includes solar installations, financing, battery storage, and energy management.

Competition and positioning

SolarSquare competes with ZunRoof, Glow Solar, Mysun, Oorjan Cleantech, and Freyr Energy in residential rooftop solar. But those aren’t the only alternatives that matter. For many households, the real comparison is still a patchwork of local EPC contractors, neighborhood installers, and one-off referrals that may be cheaper upfront but far less consistent on service, financing support, or performance follow-through. SolarSquare’s differentiation is its vertically integrated model and monitoring software. It also leans on consumer financing and performance guarantees. The goal is to turn rooftop solar into a branded home-upgrade purchase instead of a contractor gamble.

Why does the SolarSquare Series C matter?

This round matters because SolarSquare isn’t just adding sales capacity. It’s trying to widen the product from “we install panels” to “we manage home energy.” That’s a bigger ambition, and frankly a riskier one, because batteries, financing, service quality, and energy-management software all add complexity. But it’s also where a national consumer brand could pull away from smaller installers that can’t afford the same service stack.

There’s also a pretty clear investor thesis here. B Capital is backing a company that already has meaningful install volume and a proprietary asset-management layer. It also has a repeatable city-expansion playbook. Lightspeed doubling down matters too. Existing investors usually know where the operational bruises are, so follow-on participation in a hard-execution category like solar says more than a new-investor headline does.

How big is India’s rooftop solar market?

The timing isn’t random. India’s rooftop solar market was valued at $2.52 billion in 2025 and is projected to reach $4.27 billion by 2034, according to IMARC, with residential already the biggest end-user segment at 41% and on-grid systems dominating at 90%. CareEdge has also projected India’s cumulative rooftop solar market could reach 25 GW to 30 GW by FY27, up from 17.02 GW in FY25. Those are solid numbers. The more interesting part is where the demand is shifting: straight into homes.

That shift has been pushed hard by policy and economics. PM Surya Ghar, announced in February 2024, targets rooftop solar for 1 crore households, and by 2026 the program had crossed 26.19 lakh installations. SolarSquare says India has about 70 million viable residential rooftops and still sits below 5% penetration. Shreya Mishra put the inflection point bluntly: 5 years ago, roughly 1 lakh homes were going solar in a year; now, 1 lakh homes are adopting solar every 10 days. Recent sector data backs that momentum — India added 7.1 GW of rooftop solar in 2025, up sharply from 3.2 GW in 2024.

Can the SolarSquare Series C turn it into a home energy brand?

It might. But this only works if SolarSquare can keep service quality tight while expanding fast, because residential solar gets ugly when installs scale faster than maintenance, financing, or support. The next things to watch are simple: how quickly it enters new cities, whether battery storage becomes a real revenue layer, and whether its performance-guarantee model still holds up when the customer base gets much larger.

Read how Probably AI raised a $9M seed led by Andreessen Horowitz to build a reliability-first AI platform that verifies outputs against real data, helping enterprises run natural-language analytics without the hallucinations and accuracy risks that plague traditional LLM workflows.

FAQ

• What happened in SolarSquare’s latest funding round? SolarSquare raised $53 million in a Series C round led by B Capital on June 16, 2026. Existing backers including Lightspeed, Elevation Capital, Lowercarbon Capital, Rainmatter, and Good Capital also joined, pushing the startup’s total funding past $100 million.
• How does SolarSquare work for a homeowner? It works as an end-to-end rooftop solar service rather than a simple equipment sale. A customer starts with a rooftop survey and 3D design. Then SolarSquare handles installation and subsidy paperwork. It also provides financing support, app-based monitoring, and 5 years of maintenance after the system is live.
• Who are the founders of SolarSquare? SolarSquare was founded in 2015 by Shreya Mishra, Neeraj Jain, and Nikhil Nahar. Mishra came from BCG and also co-founded Flyrobe, Jain previously worked at Deutsche Bank, and Nahar had earlier operating experience at Panasonic India before helping build the rooftop solar company.
• Is SolarSquare a solar installer or a broader home energy company? Right now it’s both, or at least that’s the direction. The company already runs a full-stack residential rooftop solar model, and the new round is meant to expand its home-energy offering into financing, battery storage, and energy management, which pushes it beyond a traditional installer category.

Probably AI builds a local-first data analysis agent that answers questions from messy datasets without inventing numbers. Andreessen Horowitz has put $9 million behind that bet in a seed round, giving founder Peter Elias a shot at turning AI reliability into a real product category instead of a perpetual demo problem. Companies want fast answers from LLMs, but they don’t want made-up numbers leaking into finance decks, analytics, or operations. Elias, a former Optimizely engineering leader and Patch co-founder, argues that the answer isn’t just a bigger model. It’s tighter verification wrapped around a smaller one.

That’s a direct challenge to how a lot of AI products are still being built.

What is Probably AI and how does it work?

Probably AI is a secure desktop app for data analysis that lets a user ask questions in plain English, connect a file or warehouse, and get back a report tied to the underlying data rather than a model’s confidence. The platform works with local files like CSV, JSON, and Parquet. It can also plug into warehouse and database systems including Snowflake, BigQuery, Postgres, MySQL, MariaDB, ClickHouse, and RisingWave. It’s built to handle datasets running into billions of rows. That puts it closer to a serious analytics tool than a chatbot with a spreadsheet gimmick.

The customer workflow is simple on the surface. You join the beta, download the app, connect your data, and start asking questions in natural language. Behind that front end, the system routes reasoning to cloud AI while keeping customer data on the local machine or inside the customer’s own network. That split matters for teams that care about privacy, competitive data, or just don’t want to ship sensitive tables into somebody else’s cloud every time they run a query.

What makes the product interesting isn’t the chat box. It’s the control layer around it. Probably delegates math to a local compute engine instead of asking an LLM to fake arithmetic. It flags missing values and odd formats before they snowball. It also builds up business context over time so the system gets less ambiguous with repeated use. Each answer comes with citations and an audit trail. That’s becoming table stakes in enterprise AI, but here the traceability is tied to deterministic checks rather than just a list of references.

That’s where Elias’s “data science mech suit” line lands. The model generates a first pass, then a validator checks whether the figures actually exist in the dataset and rejects anything that doesn’t match. Elias says the company trained the model against that validator and found that better harness engineering lets it run on a model “four classes weaker” than frontier systems. His basic point is blunt: if you cut ambiguity hard enough, the model doesn’t need to be heroic. It just needs to behave.

Who founded Probably AI and what did Peter Elias build before this?

The founding idea

Probably is Peter Elias’s attempt to make AI answers behave more like deterministic software outputs. His goal, as he framed it, is to push accuracy toward 99.99% in workflows where a wrong answer isn’t cute — it’s expensive. The first beachhead is data science, but Elias has already pointed to accounting, medical work, and other “precision-sensitive” jobs as extensions if the validation layer holds up outside analytics.

Why Elias fits this problem

Elias isn’t coming at this as a prompt engineer who discovered enterprise software last week. He studied finance and entrepreneurship at Babson College, then spent years building software systems, including principal, senior staff, and staff engineering roles at Optimizely. That background matters because Probably isn’t selling a clever model wrapper. It’s selling a workflow that has to survive real production mess — bad tables, broken formats, cost pressure, security pressure, all of it.

Past execution and early signals

Before Probably, Elias co-founded Patch with Whelan Boyd after the pair led the data platform at Optimizely. Patch focused on data packages and data pipeline portability, which makes the jump into verifiable analytics feel logical. At Probably, the product is already live as Beta 0.1. The company lists itself at 2-10 employees, and the current release supports M1 to M5 Apple Silicon with Windows support coming next.

It’s still early. But there’s a working product, not just a thesis deck.

The seed round and what investors are backing

The company announced a $9 million seed round on June 16, 2026, from Andreessen Horowitz. The core investor bet looks clear: if Probably can make smaller models trustworthy enough for sensitive internal work, it could cut both hallucination risk and token spend at the same time. That combo is attractive right now because plenty of enterprises aren’t just asking whether AI works — they’re asking whether the bill is worth it.

How Probably AI compares with rivals

Probably isn’t alone in chasing AI reliability. Patronus AI focuses on automated evaluation and hallucination detection. It also works on broader failure prevention for production AI systems. Giskard leans into testing and continuous red-teaming. It also offers enterprise controls for LLM agents. Arize Phoenix is the open-source favorite for observability and evaluation. It’s also used for debugging once LLM apps are already in motion.

Probably is taking a different swing. It starts with an end-user data agent, not a toolkit for ML teams and emphasizes local execution and deterministic validation. It also uses weaker models instead of monitoring bigger ones after the fact. The legacy alternative is even less glamorous: BI dashboards, SQL, notebooks, spreadsheet exports, and a queue to the data team. If Probably works, it collapses a lot of that manual back-and-forth into one layer. If it doesn’t, it risks landing in the crowded middle between copilots and eval tools.

Why does Probably AI’s $9M seed round matter?

This round matters because Probably’s pitch isn’t “our model is smarter.” It’s “our system is stricter.” That sounds subtle, but it’s a much bigger claim. Elias is saying reliable AI won’t come from endless model upgrades alone. It’ll come from product architecture that narrows the model’s room to improvise.

That’s a useful thesis at a moment when customers are getting pickier. Teams still want natural-language analytics. They just don’t want to babysit every output. Probably’s approach also lines up with budget reality: the company says its setup can reduce infrastructure costs by 25%, and Elias argues that stronger harnesses let weaker models do the job. If that holds, the startup isn’t just selling accuracy. It’s selling permission to keep using AI without blowing up the finance spreadsheet.

Elias also has a sharper critique of the big labs. He thinks they haven’t seriously pursued this kind of tightly constrained system because their business model benefits from more usage and more correction loops. It’s a self-serving jab. Still, it gets at something real: enterprises are tired of paying frontier-model prices for outputs they still have to double-check by hand.

How big is the market for AI reliability tools?

The market backdrop is strong, even if the category names are still messy. Menlo Ventures said enterprise generative AI spending reached $37 billion in 2025, up from $11.5 billion in 2024. Gartner has also said 40% of enterprise applications will include task-specific AI agents by the end of 2026, up from less than 5% in 2025. More agents means more places where a bad answer can do real damage.

The adoption curve is moving fast, but trust is lagging. Gartner’s 2026 survey work said only 17% of organizations had deployed AI agents so far, even though more than 60% expected to do so within 2 years. By 2028, Gartner expects the average Fortune 500 company to have more than 150,000 agents in use.

That’s a staggering number.

There’s also the simple fact that hallucinations haven’t gone away. Stanford’s 2025 AI Index showed best-in-class models still posting nonzero hallucination rates, which is fine for a brainstorming tool and a lot less fine for finance, healthcare, or compliance work. That gap is exactly where startups like Probably are trying to live. Not in model creation. In error containment.

What to watch after Probably AI’s seed round

Probably AI is still young, and plenty could go wrong. Local-first products can be harder to distribute. Deterministic validators can become brittle outside the domain they were tuned for. Turning one strong data product into a broader reliability platform is a lot of work.

The startup is asking the right annoying question: what if the best way to make AI useful isn’t to make it sound smarter, but to give it fewer chances to be wrong? If Probably AI can carry its verification model from analytics into other precision-heavy workflows, this seed round will look less like a niche bet and more like an early wager on how enterprise AI becomes dependable.

Read how TruNativ raised $30M from OrbiMed Advisors to expand offline retail distribution and grow its clean-label nutrition portfolio, aiming to turn a successful D2C wellness brand into a mainstream consumer health company across India and international markets.

FAQ

• What funding did Probably AI raise? Probably AI raised a $9 million seed round announced on June 16, 2026. Andreessen Horowitz backed the company as it pushes a reliability-first approach to AI, rather than competing on raw model size alone.
• How does Probably AI stop hallucinations in data analysis? Probably AI uses a validator layer that checks the model’s first-pass answer against the underlying dataset before the result reaches the user. It also offloads computation to a local engine for math-heavy work and keeps customer data on the machine or inside the customer’s own network. That’s a very different setup from a generic cloud chatbot.
• Who is Peter Elias? Peter Elias is the founder of Probably AI and a software engineer with experience at Optimizely, where he held staff and principal engineering roles. He also co-founded Patch and studied finance and entrepreneurship at Babson College, which helps explain why his current pitch is as much about cost discipline as it is about model behavior.
• Is Probably AI a data tool or an AI reliability startup? It’s both, and that’s why the company is interesting. The first product is a natural-language data analysis tool in open beta, but the bigger thesis is that the same verification stack can be used in other precision-sensitive categories where wrong AI output is unacceptable.

TruNativ is a Mumbai-based clean-label nutrition brand that sells protein, fibre, and sugar-reduction products for everyday health-conscious consumers. Its new TruNativ funding round brings in $30 million from OrbiMed Advisors LLC at a time when Indian nutrition shoppers still deal with confusing labels, processed formulas, and patchy access outside online channels. Founded in 2019 by Pranav Malhotra and Mamta Malhotra, the company now wants to turn a digital-first nutrition business into a much broader retail brand.

What is TruNativ and what does it sell?

TruNativ started with plant-based protein powders and has since widened into a larger nutrition portfolio that includes supplements built around protein intake, fibre, and sugar replacement. It sells through its own website and other ecommerce platforms. That puts it in the fast-growing D2C nutrition brand bucket rather than old-school pharmacy-led supplements.

The product pitch is pretty clear. TruNativ isn’t trying to be a hardcore bodybuilding label. It’s built more for mainstream consumers who want everyday nutrition fixes without the usual ingredient-list headache. Two of its strongest categories have been fibres and sugar replacers, which says a lot about where it sees demand in India’s wellness market.

The customer journey is simple. A buyer comes in with a need — more protein, less sugar, better digestion, or a cleaner daily nutrition add-on — and chooses a use-case-led product instead of decoding a dense sports supplement catalogue. That matters because a lot of supplement buying in India still feels like guesswork. TruNativ’s edge is less about tech and more about removing that confusion with transparent, everyday-use formats.

That positioning has kept expanding. Over time, the company moved beyond an early protein-led identity into a broader nutritional supplements line, and founder Pranav Malhotra said in 2023 that the brand planned to launch 15 new SKUs in a single quarter. That’s aggressive.

Who founded TruNativ and what traction has it built?

The founding story

TruNativ was founded in 2019 by Pranav Malhotra and Mamta Malhotra in Mumbai. Pranav Malhotra is founder and CEO, while Mamta Malhotra is cofounder. From day 1, the business was built around a direct idea: healthier food alternatives can’t stay niche if they’re hard to understand, hard to trust, or hard to fit into daily routines.

The brand’s identity matters here too. TruNativ talks about “clean-label” nutrition, and that phrase gets thrown around a lot. In practice, it usually means shorter ingredient lists and clearer formulations. Products also try to avoid the over-engineered feel of legacy supplement brands. For Indian consumers who’ve become more skeptical about artificial sweeteners and heavily processed wellness products, that’s a real positioning choice.

Traction and early signals

A few public signals show how it’s executing. In July 2023, TruNativ said it had generated $6 million in revenue in the first 3 years since inception and expected a 5x rise in FY24. At that point, 80% of sales came from online channels, while the remaining 20% came from offline retail through chains such as Nature’s Basket and Wellness Forever.

That split explains the current strategy better than any founder slogan could. The company already proved people will buy clean-label nutrition online. The harder part is building the same trust and repeat purchase behavior in physical retail, where shelf competition is brutal and consumer attention is short.

Inc42 currently lists TruNativ at 52 employees and categorizes the company at the Series B stage after the latest raise. For a nutrition startup that began with a narrower D2C product set, that’s a sign it’s no longer an experiment. It’s an operating brand with a scaled-up team and a more serious capital base.

How does the TruNativ funding round break down?

The new TruNativ funding round is worth $30 million, and OrbiMed Advisors LLC led it. OrbiMed is a global healthcare-focused investment firm. The deal includes both fresh primary capital for the company and secondary share sales by some early investors. That mix tells you two things at once: the business needs growth capital, and early backers are getting at least partial liquidity.

This isn’t TruNativ’s first outside backing. Rainmatter, the Zerodha-backed early-stage investment firm, invested ₹10 crore in November 2024. Before that, TruNativ raised an undisclosed seed round in April 2021. Public reporting from 2023 also showed Emami had taken a 19% stake in the parent company, giving TruNativ earlier strategic validation from a larger consumer player.

The new money is earmarked for offline distribution and product portfolio expansion. It will also fund faster growth in India and overseas. That’s a logical use of capital. Nutrition brands don’t become durable by winning online ads forever. They become durable when people can find them easily and buy them again without thinking too hard.

How does TruNativ compare with other nutrition brands?

TruNativ sits in a crowded part of India’s consumer internet market. It’s up against clean-food and supplement brands like The Whole Truth, OZiva, Wellbeing Nutrition, and sports-nutrition-heavy players such as MuscleBlaze. There’s also older competition — chemist shelves, legacy nutraceutical brands, and generic sugar-free or protein products that don’t exactly win on transparency.

Its differentiation is pretty specific. TruNativ isn’t only chasing gym users, and it isn’t selling itself as a medical nutrition company either. It’s building around everyday use cases: better protein intake, cleaner sugar alternatives, digestive support, and products that can fit normal households rather than only fitness subcultures. That middle ground is crowded. It’s also where the biggest consumer volume usually sits.

OrbiMed’s bet likely rests on that widening appeal. If TruNativ can move from an online-first wellness label into a recognizable omnichannel nutrition brand, it gets a lot more valuable. Repeatable consumer health habits tend to create sticky businesses when the brand earns trust early.

Why the TruNativ funding round matters for retail growth

This round matters because it changes the company’s next test.

Until now, TruNativ had already shown it could find customers online and stretch beyond a single product identity. What it hadn’t fully done was build serious offline muscle. That’s where the new capital comes in. More retail presence means more visibility and a shot at becoming a habitual purchase instead of an occasional digital reorder.

It also matters because of who wrote the check. OrbiMed isn’t a casual D2C tourist. It’s known for healthcare investing, so its entry suggests TruNativ is being viewed through a wider preventive-health lens, not just as another packaged-food startup. That doesn’t guarantee success. But it does suggest investors see nutrition and functional food as a longer-term healthcare adjacency, not a short-term trend.

There’s a quieter signal here too. Secondary share sales in the deal mean some early investors got partial exits without killing growth financing. That’s usually healthier than endless paper markups with no liquidity.

How big is India’s clean-label nutrition market?

The addressable market is big enough to justify ambition. IMARC estimates India’s nutritional supplements market reached $22.9 billion in 2025 and could grow to $58.8 billion by 2034, a CAGR of 10.7%. In a separate estimate, the India dietary supplements market stood at ₹201.46 billion in 2025 and is projected to hit ₹572.62 billion by 2034.

That growth isn’t happening by accident. Indian consumers are spending more on preventive health. Protein intake is becoming a mainstream conversation rather than a gym-only one. Ecommerce has made discovery easier for niche brands. Clean-label products also benefit from a broader trust shift: buyers want simpler ingredient stories, especially in categories tied to daily consumption and family health. IMARC’s 2026 nutraceutical outlook also flags rising demand for plant-based and clean-label products in India, which lines up with TruNativ’s pitch.

TruNativ has raised a lot of money for a brand that still has plenty to prove in offline retail. The next thing to watch isn’t whether it can launch more products. It’s whether the TruNativ funding round can turn a digital nutrition label into a real consumer brand with shelf power.

Read how Sarvam AI raised $234M in a Series B led by HCLTech to build Indian-language AI infrastructure, helping enterprises deploy voice, text, and document intelligence systems that work across local languages and real-world business workflows.

FAQ

• What is the latest TruNativ funding round?
  TruNativ has raised $30 million in its latest round led by OrbiMed Advisors LLC. The transaction includes both primary capital for the company and secondary share sales by some early investors, which gives TruNativ new growth money while also creating liquidity for earlier backers.
• What does TruNativ actually sell?
  TruNativ sells clean-label nutrition products rather than a single hero supplement. Its range began with plant-based protein powders and expanded into broader nutritional supplements. Fibre and sugar replacers emerged as important categories in the brand’s earlier growth phase.
• Who founded TruNativ?
  TruNativ was founded in 2019 by Pranav Malhotra and Mamta Malhotra. Pranav Malhotra is founder and CEO, and the company was built in Mumbai around the idea of making healthier daily nutrition easier to trust and easier to use.
• Is TruNativ in the supplements market or the consumer food market?
  It sits across both, which is part of why investors may find it attractive. TruNativ operates as a D2C consumer brand, but it sells into the much larger nutrition, nutraceutical, and dietary supplements category — a market that IMARC estimates could expand sharply through 2034 in India.

Sarvam builds Indian-language AI models and enterprise tools for voice, text, and document workflows. The Sarvam AI funding round has pushed the Bengaluru startup into unicorn territory after it raised $234 Mn in the first close of a $300 Mn Series B at a $1.5 Bn post-money valuation, with HCLTech leading the round and committing $150 Mn. That matters because Indian enterprises don’t just want a flashy chatbot anymore — they want AI that can handle local languages, plug into real systems, and run in production. Founded in 2023 by Pratyush Kumar and Vivek Raghavan, Sarvam is now using fresh capital to bet harder on agentic AI, coding, cybersecurity, and bigger compute capacity.

What does Sarvam AI actually sell?

Sarvam isn’t one app. It’s a full-stack AI company that sells models and APIs. It also sells enterprise products tuned for Indian languages. Its flagship conversational platform, Sarvam Samvaad, lets businesses deploy agents across voice calls, WhatsApp, and the web. Those agents connect to enterprise systems so they can pull customer data, trigger actions, and return conversation analytics instead of just answering prompts.

Under that application layer sits a broader developer stack. Sarvam exposes speech-to-text, text-to-speech, translation, chat completion, and document digitisation APIs. Named models include Saaras v3 for ASR and Bulbul v3 for TTS. It also offers Mayura and Sarvam-Translate for multilingual translation, Sarvam-30B and Sarvam-105B for chat, and Sarvam Vision for OCR and structured document extraction in 23 languages including English.

The customer workflow is pretty practical. A team can get an API key in minutes and test a pilot fast. Then it can move to managed cloud or private VPC-style deployment depending on security needs. Samvaad also keeps context across channels, so a user who starts on a phone call and comes back on WhatsApp doesn’t feel like they’re talking to a fresh bot every time.

That’s the sales pitch. Sarvam is trying to replace the usual pile of separate speech vendors and translation tools. It also wants to replace bot orchestration layers and analytics add-ons with one platform built for code-mixed Indian usage. Sarvam’s own 30B model already powers Samvaad.

Who built Sarvam AI and why now?

Founding story

Sarvam was founded in August 2023 by Dr. Vivek Raghavan and Dr. Pratyush Kumar. Their thesis was simple and pretty aggressive: India needed its own AI stack instead of depending entirely on foreign model providers, especially for multilingual use cases and regulated industries where data control matters.

Why the founders fit this market

Raghavan brings infrastructure instincts, not just AI enthusiasm. He’s closely associated with India’s digital public infrastructure work — from Aadhaar to ONDC — and earlier served as managing director of Synopsys India after returning to the country in 2007. Sarvam isn’t selling consumer novelty. It’s trying to build systems that can survive population-scale and enterprise-grade workloads.

Kumar brings the research depth. He studied electrical engineering at IIT Bombay and earned a PhD from ETH Zurich. He also worked at IBM and Microsoft Research, and served as an adjunct faculty member at IIT Madras. Sarvam says he led India’s open-source AI efforts across Indian languages.

Track record and early signals

The product timeline shows a team moving fast, not drifting. Sarvam started with OpenHathi-v1 in December 2023 — a Hindi model fine-tuned on Meta’s Llama 2. Then it launched Sarvam-2B in mid-2024 as a lightweight model trained from scratch for efficient Indic processing. By October 2024 it had shipped Sarvam-1, a 2 Bn parameter model spanning 10 major Indic languages and English. In 2026 it moved upmarket with Sarvam-30B and Sarvam-105B, open-weight models designed for tougher enterprise reasoning and longer context across more than 22 local languages.

The business is already live. Sarvam’s systems are deployed across banking, insurance, government, and defence. Tata Capital is one of its named customers. Conversational agents make up nearly 80% of ARR, which has been estimated at about $12 Mn. The startup’s conversational platform now handles more than 2 Mn interactions a day, while its inference platform processes over 10 Mn API calls daily. In a June 16, 2026 interview, Vivek Raghavan said voice AI alone had crossed 2 Mn calls a day and API usage had climbed to more than 300 Mn calls in the last month. FY26 revenue stood at ₹45.1 Cr, up sharply from ₹1.5 Cr in FY25.

Sarvam has also been willing to chase unusual infrastructure bets. Earlier in 2026, it partnered with spacetech startup Pixxel to build Pathfinder, an orbital data centre satellite targeted for launch in late 2026. It sounds a little wild. But it fits the company’s broader view that AI advantage won’t come from apps alone.

Fundraising details

This round made Sarvam India’s 130th unicorn. It raised $234 Mn as part of a $300 Mn Series B at a post-money valuation of $1.5 Bn. HCLTech led the round, with Bessemer Venture Partners, Khosla Ventures, and Peak XV Partners also participating. HCLTech’s exchange filing said it acquired 41,421 equity shares, equal to a 10.46% stake, for ₹1,427.3 Cr.

The money is earmarked for research and compute. It’s also meant for rollout. Sarvam plans to build next-generation models centered on agentic AI, coding, and cybersecurity, expand compute infrastructure, and scale deployments across sectors. The founders have also said the round should help with global hiring and productisation, including plans connected to a San Francisco office.

How does Sarvam compare with rivals?

Sarvam’s competition comes from a few different camps. Krutrim is pushing open models and giant compute ambitions, including plans around a large supercomputer. Gnani is strong in enterprise voice AI and multilingual speech. Another IndiaAI Mission contender, Soket, is building a 120 Bn parameter open-source foundation model aimed at areas like defence, healthcare, and education.

But the older alternative usually isn’t another sovereign-model startup. It’s the patchwork enterprise stack: a global LLM on top, separate speech and translation vendors underneath, then a services integrator trying to stitch it all together. Sarvam’s edge is that it can sell the whole bundle — models, Indian-language speech, document intelligence, APIs, and deployment. It’s also arguing that more of the compute and value chain should stay in India. That’s the strategic bet HCLTech is backing.

Why does the Sarvam AI funding round matter?

This isn’t just a vanity valuation story. HCLTech gives Sarvam something most frontier-model startups don’t get early: serious enterprise distribution and instant credibility with cautious buyers. It also gives Sarvam a partner that already sits inside the banking, insurance, and public-sector accounts it wants. Because HCLTech is taking a 10.46% stake, this looks like a strategic alliance, not a ceremonial check.

The round also marks a shift in what Sarvam is trying to become. It’s no longer enough to be the promising Indian-language model company. Sarvam now wants to ship larger models and build enterprise-grade agentic systems. It also wants to widen Samvaad access through self-serve onboarding, free usage tiers, and usage-based pricing for startups, developers, and SMBs. That’s a move from bespoke enterprise selling toward something more platform-like.

There’s risk baked into that ambition. Frontier-model R&D burns cash fast, and Sarvam is stretching into coding and cybersecurity while still scaling voice, API, and document products. If it can turn HCLTech’s channel into repeat deployments, this round could matter a lot more than the unicorn label itself.

How big is the market Sarvam AI is chasing?

The near-term market here isn’t “all AI.” It’s enterprise generative AI in India — especially jobs where voice, documents, multilingual support, and compliance all collide. One forecast puts India’s enterprise generative AI market at $183.4 Mn in 2024 and $1.225 Bn by 2030, which works out to a 38.3% CAGR from 2025 to 2030.

And the mix of that market matters. Software was the biggest revenue segment in 2024, but services are expected to grow faster. That lines up with what Indian buyers often need in practice: not just a model endpoint, but deployment help, workflow integration, and ongoing tuning before AI is useful inside a bank, insurer, or government department.

The macro tailwind is clear. Indian enterprises want lower-cost AI and better support for local languages and scripts. They also want more control over where data and compute live. Policymakers want sovereign model capacity for roughly the same reasons. Sarvam didn’t invent that demand — but it showed up at the right time to package it into a product and an investment story.

Final take on Sarvam AI funding

Sarvam has gone from an Indic AI research bet to a $1.5 Bn company in under 3 years, which is fast even by 2026 AI standards. But the hard part starts now. The Sarvam AI funding story gets more interesting from here: whether wider Samvaad access, bigger compute, and HCLTech’s enterprise reach can turn strong usage into durable revenue instead of just bigger expectations.

Read how Foodstories raised ₹50 crore from Nikhil Kamath and Narotam Sekhsaria Family Office to expand its omnichannel gourmet food platform that blends premium grocery retail, food discovery, and fast delivery across India’s major cities.

FAQ

• What is the latest Sarvam AI funding round? As of June 16, 2026, Sarvam had raised $234 Mn in the first close of a $300 Mn Series B at a $1.5 Bn post-money valuation. HCLTech led the round with a $150 Mn commitment, and Bessemer Venture Partners, Khosla Ventures, and Peak XV Partners also joined.
• How does Sarvam AI work? Sarvam works as a full-stack enterprise AI platform for Indian languages. Companies can use its APIs for speech, translation, chat, and document digitisation. They can also deploy Samvaad agents that connect to internal systems, act on customer requests, and run across voice, WhatsApp, and web from one setup.
• Who are the founders of Sarvam AI? Sarvam was founded by Vivek Raghavan and Pratyush Kumar in 2023. Raghavan is known for work tied to India’s digital public infrastructure, while Kumar built deep research credentials through IIT Bombay, ETH Zurich, IBM, Microsoft Research, and Indian-language AI work before starting Sarvam.
• Is Sarvam AI a chatbot company or a foundation-model startup? It’s closer to a full-stack enterprise AI company than either label alone. Sarvam builds foundation models such as Sarvam-30B and Sarvam-105B. But it also sells production products like Samvaad and APIs for speech, translation, and document intelligence — which is why its revenue is increasingly tied to enterprise deployment, not just model access.

Foodstories is an omnichannel gourmet food retail platform that sells curated groceries, ingredients, and food-led experiences through stores and digital channels. The Foodstories funding round brings in ₹50 crore, led by Zerodha co-founder Nikhil Kamath, with participation from existing investor Narotam Sekhsaria Family Office. The gap it’s chasing is obvious: traditional grocery feels transactional, while premium food buyers increasingly want curation, discovery, and a reason to step into a store at all. Founded in 2024 by sisters Ashni Biyani and Avni Biyani, the company now has a presence in Delhi, Bengaluru, Hyderabad, and Mumbai.

Kamath’s bet isn’t on a plain grocery chain. It’s on a company trying to turn food shopping into a category of its own — part retail, part discovery. Part lifestyle brand. That’s a much harder business to build. But if it works, it can be a lot more defensible than just selling the same SKUs everyone else has.

What is Foodstories and how does it work?

Foodstories is a premium food platform where a customer can shop curated groceries online, order delivery in supported cities, or walk into a store built around browsing, tasting, and food storytelling. Its assortment spans gourmet pantry items and fresh produce. It also sells bakery, beverages, meats, cheeses, spices, oils, snacks, and other specialty ingredients sourced from both Indian makers and global brands.

What makes it feel different is the way the retail layer is packaged. The Mumbai flagship launched with That Grocery Café, That Bev Bar, and That Bake Shop. So the same visit can move from shelf to plate to live baking. The store also includes a fresh pasta bar and live spice grinding. There’s also freshly roasted nuts, made-to-order nut butters, a working flour mill built with Two Brothers Organic Farms, and a Tea Library built around origin and craft.

Online matters too. Foodstories already delivers in Delhi, Hyderabad, and Bengaluru. In Mumbai it launched a mobile app and city delivery setup promising orders in under 60 minutes. So the pitch isn’t just “come admire imported olive oil.” It’s “discover, learn, buy, and reorder without friction.”

Before this kind of model, premium grocery in India often meant hunting across separate stores, reseller shelves, or generic quick-commerce search results. Foodstories removes a lot of that manual effort by curating the assortment and wrapping it in content and retail theatre. Delivery is part of it.

Who are the founders behind Foodstories?

A comeback built on Foodhall

Ashni Biyani and Avni Biyani are the daughters of Future Group founder Kishore Biyani, and Foodstories is their return to food retail after the shutdown of Foodhall during Future Retail’s insolvency process in 2023. Their first Foodstories store opened in March 2024 at Ambience Mall in New Delhi’s Vasant Kunj, framed from day 1 as an omnichannel gourmet store and dining café.

That history matters.

Foodhall wasn’t a side project. It was one of India’s better-known premium food retail formats, launched in 2011 from Mumbai’s Palladium Mall and scaled to under 10 stores before the parent company’s problems pulled it down. Foodstories looks a lot like the sisters’ second shot at the same broad consumer — but with a heavier digital layer and an experience-first retail thesis.

Why the Biyani sisters fit this market

Avni’s fit with this category is straightforward. She joined Future Group in 2011 as the concept head of Foodhall and spent years building a premium food retail brand around imported ingredients, culinary education, and in-store discovery. Ashni came up through Future Ideas, Future Group’s innovation and incubation arm. There she worked on consumer insight, design thinking, and format development before later being associated with Future Consumer.

They’re also co-founders of Think9, a consumer brand-building platform launched with brand strategist Santosh Desai. That doesn’t automatically make Foodstories a winner. But it does mean the founders know brand architecture and premium positioning. They also understand how modern Indian consumption is changing. For a business like this, taste-making is part of operations.

Early traction, the round, and where rivals already are

Foodstories is live, not in beta. It has stores in Delhi, Bengaluru, Hyderabad, and now Mumbai, where it recently opened its flagship and plans another outlet in the city. By November 2025, the founders said the company had already seen triple-digit growth in its first year.

Now to the round itself. Foodstories has raised ₹50 crore from Nikhil Kamath, with Narotam Sekhsaria Family Office also participating. The company will use the capital for digital channels, delivery, and expanding its retail footprint. Ashni Biyani set the ambition plainly: “We’re building a ₹1,000 crore business.”

Competition is real, and it isn’t coming from one place. Nature’s Basket already operates over 35 stores and sells everything from artisanal bread and cheese to fresh produce and staples. Le Marché has built a premium grocery chain with 20,000 SKUs and a strong focus on butchery, imported foods, and live sections. Then there are the older alternatives: premium neighborhood grocers, gourmet sections inside larger supermarkets, and increasingly quick-commerce apps.

Foodstories is trying to separate itself by being less of a store and more of a food platform. The company brings together farmers, producers, bakers, chefs, and storytellers. It then turns that into retail, content, cafés, and delivery. That’s the edge Kamath seems to be backing — not just better shelves, but a brand consumers may actually remember.

Why does the Foodstories funding round matter?

Because this money is aimed at the three parts of the business that will decide whether Foodstories becomes a niche darling or a real scaled company: digital distribution, delivery, and store expansion. Those are expensive muscles to build. They matter.

For customers, the round should mean more convenience without flattening the brand into another catalogue. Better delivery coverage and stronger digital ordering can make the model easier to use between big “experience” visits. More stores can do the same. That matters a lot in food, where frequency is everything.

For Kamath, the thesis sounds clear. He called Foodstories one of the few platforms building “the real infrastructure” around better food and said, “The founders understand both the product and the business they’re building.” Investors don’t usually back premium retail because it looks fun. They back it when they think curation, habit, and margin can travel together.

How big is India’s gourmet food market?

Big already, and growing fast.

IMARC pegs India’s gourmet foods market at $5.4 billion in 2025 and expects it to hit $24.5 billion by 2034, which implies a 17.78% CAGR. In the same broad consumption shift, India’s online grocery market reached $11.4 billion in 2024 and is forecast to climb to $96.3 billion by 2033.

The trend underneath those numbers is simple. Urban consumers are spending more on premium, health-conscious, globally influenced food, and they want access through both specialty stores and digital channels. That’s why gourmet retail, boutique bakeries, premium dessert formats, and curated e-commerce are all expanding at the same time.

That’s why Foodstories is showing up now, not 10 years ago. India has more consumers who care about provenance, ingredient quality, and food as identity. The market is still tough, of course. Premium grocery can get crushed by rents, inventory complexity, and copycat assortments.

Final take on Foodstories funding

The Foodstories funding round gives the Biyani sisters fresh capital for a second attempt at premium food retail — this time with stores, delivery, and digital all tied together from the start. That’s a smarter setup than relying on footfall alone. The next thing to watch is whether Mumbai becomes more than a flashy flagship and turns into repeat demand that can support the company’s ₹1,000 crore ambition.

Read how NewCore raised a $66M seed led by Cyberstarts to build an identity platform that gives AI agents governed access, task-scoped permissions, and enterprise-grade security controls as businesses deploy software workers at scale.

FAQ

• What is the latest Foodstories funding round?
  Foodstories has raised ₹50 crore in a funding round led by Zerodha co-founder Nikhil Kamath, with Narotam Sekhsaria Family Office also participating. The capital is earmarked for digital growth, delivery, and expanding the company’s retail footprint across cities.
• How does Foodstories work as a business?
  Foodstories combines premium food retail with digital commerce and in-person experiences. Customers can shop curated grocery and gourmet products online, use delivery in supported cities, or visit stores that also feature concepts like cafés, beverage bars, and live baking.
• Who founded Foodstories?
  Foodstories was founded in 2024 by sisters Ashni Biyani and Avni Biyani. Before this venture, they were closely tied to Foodhall and Future Group, and they also co-founded Think9, which gives them an unusual mix of retail, branding, and consumer-insight experience.
• Is Foodstories a grocery startup or a D2C food brand?
  It’s closer to an omnichannel gourmet retail platform than a single-brand D2C food company. The business sits in the premium grocery, gourmet foods, and experiential retail category, with a model that blends specialty stores, curated assortments, and online ordering.

NewCore builds enterprise identity software that lets companies manage human workers and AI agents in one system. On June 15, 2026, the stealth startup said it raised $66 million in seed funding to tackle a problem a lot of companies are about to hit: once AI agents start touching production systems, old identity stacks start to look shaky. Co-founder and CEO Zohar Alon started the company with CTO Amihai Neiderman and CCO Erez Yarkoni after the idea took shape in 2023, when Alon saw customers paying huge identity bills without much real satisfaction. Cyberstarts led the round, with Index Ventures and Evolution Equity Partners joining, and it values NewCore at $300 million after the investment.

What is NewCore’s AI agent identity platform and how does it work?

Giving AI agents their own identities

Here’s the plain-English version: NewCore gives every AI agent its own governed identity. It then sits inline on the identity layer so every authentication request, token, and authorization decision runs through the platform in real time. That means a company can let an agent sign into enterprise systems, but only with short-lived access tied to a specific task instead of broad standing privileges. It can run as a standalone system or alongside an existing identity provider. That matters because most enterprises won’t rip out Okta or Entra overnight.

Agentic SSO and task-scoped access

The workflow is more concrete than the usual “AI security” hand-waving. NewCore’s Agentic SSO gives agents an auditable sign-in path to connected tools. Its task-scoped tokens are minted at the narrowest permission level the destination app allows, so an agent gets access for the job in front of it, not a permanent all-you-can-eat credential. The platform also keeps an AI inventory and audit trail. Security teams can see which human or agent touched what, and when.

Managing AI agents across enterprise systems

That setup targets a pretty obvious mess inside enterprises right now: developers and employees are wiring Claude Code, Codex, Cursor, and internal copilots into production systems with whatever credentials are handy. NewCore’s “Agentic Skill” package is meant to clean that up by letting those coding agents access enterprise systems as managed identities instead of borrowed secrets or manually distributed keys. For customers, the before-and-after is simple. Before, AI tools piggyback on service accounts. After, they show up as first-class identities with permissions and lifecycle controls. They also get revocation paths of their own.

Security features and human oversight

NewCore is also trying to make the underlying identity plumbing harder to break, not just easier to administer. Its Secure Split Key model divides signing authority between the vendor and the customer environment so neither side can sign alone. The company also layers in VisualMFA and hardware-bound credentials anchored in TPM or Secure Enclave for human users. It also offers a mobile app that lets employees grant, review, or yank access for agents when human oversight is needed. That’s not a small detail. It’s the difference between “we deployed agents” and “we know how to stop them.”

Who founded NewCore and why now?

Alon’s story is the core of this company.

The founding story

NewCore started with a blunt observation. In 2023, while helping review one company’s tech budget, Alon saw what it was paying a major identity provider and assumed the customer must be thrilled. He asked, “You must be extremely happy with them.” The answer was: “No, I’m not.” That exchange pushed him toward a market he saw as big, expensive, and sleepy — right as AI agents were starting to move from demos into actual work. Alon has said the rise of software workers convinced the founders that 15- to 20-year-old identity platforms would crack under the scale and complexity ahead.

Why this team fits the market

NewCore’s founding bench is unusually strong for a seed-stage security company. Alon previously founded Dome9, the cloud-security startup Check Point acquired in 2018, and earlier in his career he helped build Provider-1, one of Check Point’s foundational enterprise products. Amihai Neiderman, NewCore’s CTO, led research in Israel’s Unit 8200 and previously founded healthcare AI startup Nym Health. Erez Yarkoni, the commercial co-founder, brings operator credibility from the buyer side after serving as CIO at T-Mobile USA and Telstra.

That mix matters. A lot of AI-security startups have strong researchers but weak enterprise selling muscle, or the reverse. NewCore has a founder who has already sold into security teams. It has a CTO who has built applied AI systems. And it has a third co-founder who has lived through big-company identity and IT pain from inside the building. That’s one reason investors were willing to back a seed round this large.

Early traction and the $66M seed round

The company has more than 50 employees across the U.S. and Israel, or more specifically Tel Aviv and the U.S. on the company’s launch materials. It’s still early: NewCore has fewer than 10 customers using the platform and more than 10 design partners, and it expects to start charging in summer 2026. That’s not massive commercial traction yet. But it’s enough to show this isn’t just a concept deck with an AI label slapped on top.

The financing is big by any seed-round standard. Cyberstarts led the $66 million round, with Index Ventures and Evolution Equity Partners participating, and the post-money valuation lands at $300 million. For a company just emerging from stealth, that price tells you investors think identity for AI agents could become its own control plane category — not just a feature inside somebody else’s admin console.

How NewCore compares with Okta, Microsoft Entra, and Aembit

This is where the pitch gets interesting. Okta and Microsoft Entra are both adding tools for AI agents and non-human identities, which means the incumbents clearly see the same opening. Microsoft now offers Entra Agent ID and governance workflows for agent identities. Okta has rolled out “Okta for AI Agents” and a broader secure-agentic-enterprise blueprint. So NewCore isn’t inventing the problem. It’s racing bigger companies that already own enterprise identity budgets.

NewCore’s counterargument is that the incumbents are bolting agent controls onto platforms built for browser logins, SAML-era federation, service accounts, and static credentials. Alon’s line is that those systems were designed for human employees first, while NewCore was built from scratch for a workforce of humans, machines, and agents. The split-key architecture and inline token control are part of that case. So are agent lifecycle management and the side-by-side deployment model.

There’s also a younger-company comparison. Aembit has been pushing IAM for agentic AI and broader workload identity, so it’s one of the clearer startup peers in this category. But Aembit’s roots are closer to workload and machine access management, while NewCore is pitching itself as a unified workforce identity layer where humans and agents live in the same plane. That distinction could matter if buyers want one policy model for both employees and software workers. Or it could blur fast if the category gets crowded.

Why this AI agent identity round matters

Because this round isn’t really about selling another dashboard.

It’s about giving NewCore enough capital to attack a category that usually favors giants. Identity is sticky, high-risk software. Buyers hate replacing it. So if a startup wants to break in, it needs enough engineering muscle to ship core security architecture. It also needs enough product depth to coexist with legacy systems, and enough go-to-market patience to win cautious enterprise customers. A $66 million seed round gives NewCore room to do that before revenue fully ramps.

It also signals that investors believe AI-agent governance won’t stay a side module forever. If enterprises really do move from a few copilots to fleets of semi-autonomous agents, the company controlling identity, authorization, and revocation becomes extremely valuable. That’s the thesis here. Alon put it more bluntly: “It’s inevitable.” The real question, he said, is whether companies build those guardrails in time.

Why is AI agent identity becoming a real market?

The macro numbers are starting to line up. Gartner said in June 2025 that 24% of CIOs and IT leaders in a webinar poll had already deployed at least a few AI agents, and another 4% had deployed more than a dozen. Separate market research put the broader IAM market at $26.77 billion in 2025, with a forecast of $62.90 billion by 2033. Even if those forecasts move around, the direction is obvious: identity is getting bigger, not smaller, and AI is dragging non-human access into the center of that spend.

The enterprise anecdotes are getting hard to ignore. Goldman Sachs tested the AI coding agent Devin as a new employee in 2025. McKinsey said earlier in 2026 that 25,000 AI agents were already working alongside its 60,000 employees. TCS chairman N. Chandrasekaran has made a similar point, saying AI agents could eventually rival his company’s workforce in size. If that’s even half right, identity teams aren’t heading toward a mild upgrade cycle. They’re heading toward a scale problem.

That’s why NewCore’s timing makes sense, even if the company still has a lot to prove. Legacy identity tools were built for people logging into apps. Agentic systems create nonstop token requests, sub-agents, delegated actions, and a flood of machine-speed decisions. NewCore’s own view is dramatic — identities could grow roughly 100x and identity events 100x as agents mature — but even a softer version of that claim points to the same thing: this category is no longer theoretical.

Can NewCore win the AI agent identity race?

Maybe. But it won’t win just by naming the problem first.

NewCore has a serious founding team and a very large seed round. It also has a product story that’s more specific than most AI-security launches. Now it has to beat timing risk, prove that enterprises want a new identity layer instead of extensions from Okta or Microsoft, and convert design partners into paying customers starting in summer 2026. That’s what to watch next.

Read how AutoVRse raised $2.4M from Singularity AMC and Lumikai to expand its enterprise VR training platform that helps industrial companies turn frontline expertise into scalable, AI-powered immersive learning workflows.

FAQ

• What is the NewCore funding round? NewCore raised a $66 million seed round announced on June 15, 2026. Cyberstarts led the financing, with Index Ventures and Evolution Equity Partners participating, and the deal valued the company at $300 million after the investment.
• How does NewCore’s platform work for AI agents? It gives each AI agent its own enterprise identity instead of treating it like a shared service account. The platform handles sign-in and issues short-lived task-scoped tokens. It evaluates access requests in real time and keeps an audit trail so companies can monitor and revoke agent access when needed.
• Who founded NewCore? NewCore was founded by Zohar Alon, Amihai Neiderman, and Erez Yarkoni. Alon previously founded Dome9, Neiderman led research in Unit 8200 and founded Nym Health, and Yarkoni was CIO at both T-Mobile USA and Telstra — which gives the team a mix of security, AI, and enterprise IT experience.
• Is AI agent identity really a separate market category? It’s starting to look like one. Big incumbents like Microsoft and Okta now ship agent identity features. Newer vendors like Aembit are targeting agentic AI access. Gartner’s 2025 poll showed that a meaningful slice of enterprise tech leaders had already deployed at least some AI agents.