“Silicon Valley has done very well with software, but while software was eating the world, they forgot about silicon,” Barrett told 91¾«Æ· News in an interview.

The firm recently closed a $475 million fund focused on investing in deep-tech startups at seed and Series A. In the decade-plus since its founding, it has built its investment thesis around the idea that breakthroughs in science and engineering — not just software — would create the next generation of valuable companies.

With demand surging for compute, semiconductors and energy, Barrett argues the rest of the industry is now catching up. “We’ve been at it for more than a decade,” he said. “In recent years, as AI is eating software, people are scrambling back to recognize that the energy, semiconductors and infrastructure they operate on all need capital too. We’ve been operating in that regime for a very long time.”

Barrett is originally from Australia and came to Silicon Valley in the 1980s. He’s been coding for 50 years, he said, after developing an early and deep respect for science and engineering as the child of two engineers. His childhood was steeped in punch cards, draftsmen and drawings of control systems and machinery, he said.

“Science lets you follow breadcrumbs from prehistoric plumage to semiconductors. One principle can be applied somewhere orthogonal and create extraordinary value,â€� Barrett said in a lengthy interview with 91¾«Æ· News.

Barrett went on to found video game developer , joined to build the entertainment browser acquired by , and was subsequently CTO at prior to co-founding Playground Global in 2015.

Playground Global operates a lab in the former Palo Alto Research Building in Palo Alto, California. The location hosts 350 people, including those working at its portfolio companies and others with adjacencies working from the lab.

On a recent visit to the warehouse, I saw various models of robots, materials for aerospace construction, and a model of building powerful lasers to increase the speed of semiconductor manufacturing. The quantum computing startup , a Playground portfolio company, moved in when it had three employees and moved out when it reached 90.

The firm has four general partners. Along with Barrett, they are , the former CEO of and who architected CPUs at Intel that helped computing take off at scale, and who joined the Playground team last year as a general partner specializing in semiconductors; , who has made many investments in biotech, including ; and co-founder , who led the investment in .

What follows are highlights from a wide-ranging interview with Barrett that covered topics including sovereign technology, the need to invest in companies that operate on the physical plane, and why he believes putting data centers in space is stupid.

This interview has been lightly edited for clarity.

Gené Teare: What is the thesis for Playground Global?

Peter Barrett: It is about reducing new results in science and engineering into commercial and societal value. That means operating at the boundary between computation and the physical world. We are very interested in new capabilities of computation driving civilization forward, and that inevitably means operating in the same physical plane that we live in.

We’re seeing in our data a huge amount of funding going into space, semiconductors and robotics. It seems as if the whole venture industry has pivoted to this much broader array of companies. Do you see that as a good thing?

Barrett: We lost a lot when people weren’t investing in things that strike us as important. It is good that there is capital chasing the things we care about and that have real consequence.

You can’t spin up a deep-tech practice overnight. You still need domain expertise. You still need to understand why investing in nuclear reactors is good, and why data centers in space are preposterous.

Silicon Valley hasn’t been very efficient with much of the capital it’s deployed over the past decade or so. But I do think it’s good that people recognize that software may be eating the world, but you can’t eat software. We have to operate in the physical layer.

Do you think Silicon Valley gets more efficient?

Barrett: We need to do the work. You develop the instincts and the platform to deploy capital efficiently into these places.

It’s important that people recognize there’s this unprecedented funnel of technical change. AI is an early indicator of it, but we have technologies like quantum. We know how to produce computation using things beyond transistors and semiconductors.

We’re scratching the surface in terms of AI models. We’re right at the beginning of an explosion and renaissance in materials science driven by things like quantum computing.

Now would be the time — and candidly, I feel the imperative — that anywhere there is science and capital, it needs to be turned into value, especially in liberal democracies, because the despots are doing a pretty good job of it. It’s incumbent on us to stay ahead.

We’re in the DOS age of AI. We’re scratching the surface, both in terms of the models we make and the hardware we run them on.

Now would be the time for people to write checks into things that are sensible and valuable. We spent a lot of time on NFTs. How are we doing with cancer? How are we doing with our most difficult challenges in terms of healing and feeding the world?

There are lots of new degrees of freedom that could take capital and turn it into value.

Do you think deep tech fits the venture thesis, despite the long time horizons and the amount of capital it requires?

Barrett: The long time horizons certainly exist. If you’re building PsiQuantum, we’re building million-qubit quantum machines. That takes billions of dollars and a decadal effort.

The corollary is that we’ve had hardware exits in two years. The timelines for hardware aren’t necessarily that different from software.

Therapeutics naturally take a longer time, because of clinical trials. But we’ve also seen exits there. One of our companies tested half a million drugs in a single animal and created a new corpus of AI input for building models to create therapeutics. That’s not a decadal effort — that’s a handful of years before exit.

We try to craft a portfolio that’s a mix of tactical and strategic. Some of these companies get to hundreds of millions in revenue within a few years. Others, like PsiQuantum or , may take a decade to reach full entitlement. That’s part of portfolio construction.

The biology company you mentioned —Ìıwhat’s its name?

Barrett: . It did the largest pharma deal of its kind last year with . The deal could be worth $2 billion on the back end.

It’s a unique mechanism to create giant AI training sets by using physical systems — using animals and in vivo testing to create that dataset. It affords the ChatGPT and biology moment, where you can have large enough training sets to build big models.

You describe the firm as investing somewhere between improbable and impossible. Are there companies that really fit that thesis when you first met them?

Barrett: When we first met PsiQuantum, they were talking about building a machine which was 10,000x the state of the art. Using then-current technologies, it would have been the size of the Sierra Nevadas.

They required exponential improvements in both hardware and software, and they’ve achieved both. It’s the size of a warehouse, not a laptop.

The work we’re doing in biology, materials, quantum algorithms and superconducting logic — which will replace transistors and semiconductors — all of these things sound like science fiction, but they’re much closer to improbable. In many cases they’re entirely practical before we invest; they just seem improbable to those unfamiliar with the domain.

There are things that are not impossible but are still really dumb — data centers in space, small modular reactors (SMRs), or fusion. The physics may work, but the economics don’t, or the timelines don’t align.

I’m disappointed we haven’t invested in anything that turned out to be more impossible than we thought. None of our portfolio companies failed because the technology didn’t work.

We’ve had capitalization failures. We flew hydrogen planes. We’ve built things that were thought to be virtually impossible that turned out to be straightforward. They may have missed their market or may have been unable to raise the capital to continue.

I want to do something where the technology doesn’t work, and we’ve yet to do one of those.

Is there a company you missed out on where it looked impossible and you wish you’d invested?

Barrett: I wish I hadn’t taken ‘s word for it when was a non-profit.

We haven’t missed many. As the roadmap developed, we wish we had been earlier in a couple of categories that are really interesting. But overall, we haven’t missed too many.

In which sectors or companies have you invested where the time horizons have shortened due to AI?

Barrett: Adding Pat Gelsinger to the team reflects an interest in scaling semiconductors along various dimensions, including energy efficiency and how power is delivered.

We do everything from nuclear reactors all the way through to transmission, energy conversion outside the data center, inside the data center, under the chip, what kinds of chips you’re running, what models run on top of those chips, what architectures those chips are made from, and what materials those chips are made from.

At every layer of the infrastructure — optical interconnects, memory systems — we have a best-in-class company at every point. We built the first AI accelerator a decade ago, and we’ve broadened that to encompass the entire ecosystem, from the creation of electrons to how they expend themselves doing useful software work.

There are bubbly aspects of the current AI moment, but the bubble is being modulated to some degree by the unavailability of energy.

We’re in the DOS age of AI. LLMs are embarrassingly incompetent compared to what comes next, but we believe in the durability and growth of AI, and are making investments in model architectures and the ways AIs are trained. We see demand for compute, energy and infrastructure continuing to grow.

We have technologies that can reduce general-purpose compute workloads by 100x to 1,000x over state of the art. We believe we know how to make the energy and deliver it. We know how to connect these systems.

So quixotic pursuits like putting data centers in space are unnecessary.

Talking privately to hyperscalers and Fortune 50 companies, they all say there is way more demand for AI in its future incarnation than exists today. It’s incumbent on us to figure out how to do it 100x, 1,000x or 10,000x more efficiently, because that demand turns into GDP growth and better solutions to our hardest problems.

What are the companies in energy and semiconductors that you are betting on?

Barrett: One example is the wild superconducting logic company . We can make things that are post-semiconductor and post-transistor, with devices that switch five orders of magnitude more efficiently than transistors.

They operate at cryogenic temperatures, but quantum computers do that, and our extreme ultraviolet lithography system does that. The future of computation is cryogenic. Even after you pay to make it cold, you’re still 100x to 1,000x more energy-efficient on compute.

This technology has been around since last century, but it’s mainly been used for secure signals intelligence and radar applications. We’re generalizing it for compute.

Another example is . People talk about SMRs, which are a physics solution to a financial problem, or fusion, which is still decades away. Alva instead uprates the existing nuclear fleet to get hundreds of megawatts out of each unit by replacing 1970s steam generators with a 2020 steam generator.

We can deliver power in a handful of years. No new fuel, no new regulatory path, and a business model that makes sense for operators. We can put gigawatts onto the grid without moving a fence line of an existing reactor and without upgrades to the electricity grid.

We know how to make AI training wildly more efficient. We know how to train different kinds of AI models that we’ve been unable to train.

The last supercomputer at uses something unlike a CPU or GPU to run existing software. We’ve been running software the same way for 70 years, but there are other ways, with dataflow architectures. We have a company doing that — [].

The degrees of freedom from materials, systems, code and models have never been greater. We’re exploring all of them. But most require rolling your sleeves up in the physical world.

LLMs feel like brute-forcing something — like a drunk looking for keys under the streetlight. We’re pushing more and more into that, and I think that’s a dead end. We know other ways of moving forward.

Are you seeing new model companies, separate from LLMs, that are going to solve things?

Barrett: Our brains are not LLMs. They’re not transformers. Transformers are effective, but they are one of a long line of soon-to-be-extinct models that get replaced by something that works better.

That millionfold gap between our brains and GPUs is an architectural gap. Meat is much worse at computation than hardware can be, so biology shouldn’t be better.

Physics allows a million times a million more efficiency, and we should start chipping away at that.

Intelligence is useful and can be pressed into service against basic things like photosynthesis. Plants were invented by accident of evolution 3 billion years ago. They’re pretty, but not efficient. They shouldn’t be green; they should be black. We know how to make photosynthesis twice as efficient, and probably 5x more efficient.

We’re not stuck with the physical constraints of our technology or of nature. Nature is beautiful, but cobbled together by a process that we can have agency over.

All the materials that operate our civilization are discovered, not designed, because we can’t design things we can’t simulate. Our best computers cannot simulate the quantum nature of nature. That’s about to change.

We’re stumbling around in the dark, relying on serendipity and the occasional magical material. Whereas we can construct any number of materials with magical properties that are currently hidden from us by our inability to simulate the quantum mechanical processes that animate chemistry.

We are right on that threshold of unlocking all of these dimensions. And at the same time, we’re putting money into NFTs, the metaverse and other things that will come and go, without anybody ever caring.

Are you talking about the mix of quantum with biology and model-focused companies?

Barrett: Quantum allows us to directly design materials, directly explore the method of action of drugs, and directly design drugs.

AI has a role to play in biology and understanding structures we can measure. We think there are quantum wet labs where we can measure the performance of small-molecule drugs against models of nature and then verify in nature.

We don’t know how many things that animate our industry actually work. We don’t know how Tylenol works. We don’t know how the Type II superconductors we’re building fusion reactors out of work. We know that if you take iron and nitrogen and arrange them in a certain way, they produce magnets stronger than rare earth magnets, but we don’t know why.

There are mysterious things we’ve stumbled across that hint at an Aladdin’s cave locked behind a wall of computation. That wall is coming down.

Which sectors do you think are going to take a lot longer to come to fruition?

Barrett: Civilization will operate on fusion eventually, but right now the only reactor that works using gravimetric confinement is the sun. I think that’s a long way off.

Data centers in space are stupid. You can’t operate a gigawatt data center in a thermos. We have terrestrial answers to those questions that we should pursue.

I’ve always been a detractor of self-driving cars, which are starting to work. Now we need an economic model that makes them sensible and doesn’t drown our cities. The problem with transportation in cities is not the degree of autonomy. If we cared about traffic deaths, we’d worry about roundabouts.

There’s also nonsense with NFTs and the metaverse which have sopped up enormous amounts of capital. Small amounts of capital using these tools against our most difficult diseases would yield results. Small modular reactors are an unwarranted innovation.

There are lots of things that, at first blush, seem good and valuable, but there are far better solutions that are simpler and more imminent. We need to be practical about where the money goes.

There was a company that just joined the 91¾«Æ·, valued over $1 billion this past month, doing orbital data centers. Are you saying this whole category doesn’t make sense?

Barrett: To his credit, will show you a picture of what a 100-kilowatt data center looks like, and it’s bigger than Starship. A 100-kilowatt is a small rack from that is human-sized.

The arguments are that there are a lot of renewables in space. But there are a lot of renewables on the ground too. North Western Australia has solar and wind that are 70% naturally firm, and on the ground, so you can build things on it.

Put a data center in North Western Australia, which we are doing. We have a renewable site 35x the size of Manhattan.

Energy generation and compute in space is a nonstarter because space is not cold. You’re building things in a thermos and need to get rid of heat. A single human-sized rack is 100 kilowatts, which is about the size of the International Space Station’s radiators and solar panels.

Starship has yet to actually put anything in orbit. It’s made some fireworks, which are pretty, and it’s a beautiful thing. is an amazing company because of Falcon 9 and Starlink. But data centers and power generation in space makes no sense.

We know how to build arbitrary amounts of energy generation on the ground with very safe, very large nuclear reactors. We’ve been doing it for decades.

For all the talent and genius rattling around the Valley, we do spend money on silly things.

Do you think now is the most exciting time to be investing, or have some of those investments already been made and are going to come to fruition?

Barrett: We’ve already made investments in things on a really steep trajectory.

Snowcap will take a decade before we’re building GPUs with that technology, but we’ll have commercial product from them next year. We’re getting better at early, undeniable signals.

PsiQuantum is a long journey, but some things just take that amount of time.

X-Lite seems like a ridiculously long journey, although we’re building the prototype facility now, and it received the first money from the new CHIPS Act.

Some hardware companies making silicon or systems are getting significant revenue in a handful of years.

There’s a sleeper in Fund I. Its first trick was to make MRI machines 100,000x more sensitive, and they’re shipping those. In the background they’ve also been developing that core physics to build a new quantum computing modality. So we actually have two quantum computing companies in Fund I.

Even though that’s a 10-year-old company, there are about to be two companies, one of which will be a unicorn virtually overnight.

There are wild things bubbling under the surface that people are going to wonder where they came from.

Companies like — the only co-packaged optics on TSMC — we’ve been working on that for a long time. Now people are waking up to silicon photonics and co-packaged optics.

There are also stealth companies that are indistinguishable from magic. Some of those will come out of stealth this summer.

Is there anything we haven’t chatted about that you think is worth noting?

Barrett: It’s a sobering note, but globally there is a need and desire for sovereign capability in tech — in Western Europe, Australia, Canada and elsewhere.

There are extraordinary pools of capital, pension funds and Australia’s superannuation fund. Given the things we can invest in, globally the West needs to do a better job translating that capital into societal and economic value.

The safety and durability of liberal democracies depends on creating wealth and staying ahead.

We see a resurgent desire to do that in Europe and Australia. Around those pools of capital, there’s ambition. We need to drive that ecosystem globally, not just in the U.S.

The pace of innovation in Ukraine, driven by need, is indicative of changes that can be made in parts of the world less friendly to the tenets we hold dear in liberal democracies.

We can’t operate under the assumption that everybody clever lives in Palo Alto or that we can only invest in things we can drive to. We need to deploy capital globally, and we do. We’re going to do more of that.

Do you feel encouraged by the amount of infrastructure build-out that’s going to happen over the next few years? It feels like it will create a boom in all sorts of technologies because the drive for efficiency will become much stronger.

Barrett: LLMs are not the end. We’ll run LLMs on these data centers initially, but we’ll run their descendants and other more useful things on these machines and on quantum machines.

It’s going to be hard to overbuild because computation is incredibly useful. There’s no upper bound. We’re not in a Malthusian zero-sum game for resources.

We know how to make everything more productive. We know how to grow GDP arbitrarily large. But we need food, energy and medicine there, and we need to normalize the distribution of wealth.

There is unbounded abundance we can unlock if we spend capital on the right things. We know how to do much more of that than people suspect.

The fact that sensible people are considering data centers in space indicates they’re not paying attention to the things we already have in hand that can move the needle.

We do need compute in space. We need AIs in space, sensing in space, and Starlink is great. But we need to use technologies that make sense, not try to make skyscrapers out of toothpicks.

91¾«Æ· queries:

Related reading:

• Sector Snapshot: Quantum Computing Startup Investment Slows In 2026 While Public Markets Hold Strong
• Sector Snapshot: Semiconductor Startup Funding Still Running Hot

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and each launched multibillion-dollar deployment ventures staffed with forward-deployed engineers, while a long list of startups building AI infrastructure, autonomous software and robotics also reached unicorn status. Together, the new entrants point to where investors increasingly see value creation: turning AI advances into real-world applications and pairing software intelligence with physical automation.

Beyond AI, new unicorns were minted across many sectors including healthcare, quantum, aerospace, financial services, manufacturing, e-commerce and energy.Ìı

China dominated in the robotics sector, while Canada did so in quantum. The single new legaltech unicorn last month was from Brazil. also joined the board this past month, as the adult creator content company raised its first external financing.Ìı

Of the new unicorns, 17 are U.S-based, while four each are based in China and the UK. Two new unicorns joined the board from Canada, as one each from India and Brazil.Ìı

Unicorn IPOs

The board’s total value is undergoing rapid fluctuations amid lofty new valuations for some of the largest new unicorns, as well as high-profile exits to the public markets.

The 91¾«Æ· reached $9.9 trillion in value in May, as Anthropic moved ahead of OpenAI to become the second most valued private company after . On the heels of the funding, Anthropic privately filed for an IPO, followed shortly thereafter by OpenAI’s .Ìı

SpaceX is expected to list this Friday, in what would be the largest-ever IPO. Its listing will erase more than one-tenth of value from the board as the the -led company exits the private markets.Ìı

Chip company went public in May in a blockbuster IPO that valued the company at $56.4 billion,Ìıwell above its last private valuation of $23 billion just three months earlier in February.Ìı

New unicorns in May

Here are May’s new unicorn companies, including 10 companies that are less than 3-years old:Ìı

AI deployment

• San Francisco-based raised a $4 billion private equity round led by with co-leads , and . The new company is majority owned by with partnerships with 19 investment firms and consultancies. OpenAI acquired , with its 150 forward-deployed engineers to support enterprises in this effort. The less than 1-year-old-based company was valued at $14 billion in the new funding, which it said will be used to scale operations and acquire companies.Ìı
• raised a $1.5 billion private equity funding to build an AI services company to work with companies to bring Claude into their operations. Each of the co-leads — , private equity investor and legal firm —Ìıinvested $300 million into the round. and also invested in the joint venture. The less than 1-year-old-based, San Francisco-based company’s valuation was not disclosed.
• , a company building search for AI agents, raised a $250 million Series C led by . The 5-year-old San Francisco-based company was valued at $2.2 billion and is used by coding agents, go-to-market agents and chat agents.Ìı
• Boston-based autonomous AI software developer raised a $200 million Series A led by . Blitzy’s platform reverse engineers existing code bases to build a knowledge graph and thereby enable autonomous development of software projects over days or weeks that can re-engineer and test complicated systems and deal with technical debt. The 2-year-old company was valued at $1.4 billion and is said to be used by dozens of global 2,000 companies.Ìı
• , a routing technology for applications to select from 400-plus models, raised a $113 million Series B led by Alphabet’s . Investors in the round included a host of corporate venture firms including , , , and . The 3-year-old New York-based company was valued at $1.3 billion.

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• raised a $700 million Series A led by . The company plans to build personalized robotics developing its own models, training and hardware. The 1-year-old San Jose, California-based company was valued at $6 billion. It was founded by CEO , founder of humanoid robotics unicorn .
• Guangdong, China-based , a dual arm robotics developer, raised a $147 million Series B led by and . It said its new funding will be used for R&D, production and a global sales network. The 10-year-old company was valued at $1.5 billion.Ìı

• Shanghai-based has raised four funding rounds since it was spun out of in January, and reached a valuation of $1 billion. Agilink is focused on dexterous hand technology. The funding will be used for model development, data and hardware with the spinout able to license to the broader robotics market.Ìı
• , a robot leasing and rental platform, raised a Series A funding. The less than 1-year-old Pudong, China-based company was valued at $1 billion. It is looking to expand from event rentals to warehousing, logistics and park operations.Ìı

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• , a treatment provider for cardiovascular and orthopedic disease, raised a $1.5 billion corporate round led by . Boston Scientific has an option to acquire its heart valve technology. The 10-year-old Georgia, U.S.-based company was valued at $4.4 billion.Ìı
• , a longevity biotech company, seeking to extend human life by a decade, with therapeutics targeting age related disease raised the initial close of funding round led by . The 5-year-old Redwood City, California-based company was valued at a pre-money valuation of $1.8 billion.Ìı
• , launched a suite of AI agents for healthcare built from its clinical data, raised $146 million in equity and secondary funding led by . The 15-year-old New York-based company was valued at $1.6 billion.

Quantum computing

• Vancouver-based , a quantum computing company that combines silicon-based qubits with native photonic interconnects, raised a $70 million extension funding led by Luxembourg-based . Photonic raised $130 million in January. The 9-year-old company was valued at $2 billion.
• Quebec-based , which says it addresses quantum error correction in each qubit, raised a $30 million funding. The company has raised a mix of government grants and venture capital. The 6-year-old company was valued at $1.4 billion.

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• , a builder of rockets to deploy data centers in space, raised a $305 million Series B led by . The 2-year-old San Carlos, California-based company, formerly called Aetherflux, was valued at $2 billion. The company plans to launch its first satellite later this year. Its technology entails using the upper stage of the rocket as a low-earth orbit satellite that uses solar energy to create 1-megawatt data centers in space.Ìı
• Hyderabad, India-based , a rocket company that delivers satellites into space, raised a $60 million funding led by Singapore-based and Menlo Park, California-based . Skyroot is planning the maiden voyage of Vikram-1 in June. The 7-year-old company was valued at $1.2 billion.

Financial servicesÌı

• , an AI insurance provider for startups, raised a $160 million Series B led by . The 2-year-old San Francisco-based company was valued at $1.3 billion and plans to go after the trucking industry next.Ìı
• Intelligent wealth management platform raised a $150 million Series D led by . With in recruited assets, it is built to create an all in one system for advisors. The 7-year-old San Francisco-based company was valued at $1 billion.

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• , a manufacturer of aerospace and defense components, raised a $300 million Series B led by . The 1-year-old El Segundo, California-based company, which aims to strengthen America’s industrial base, operates six factories across the U.S. and was valued at $1 billion.
• , likewise says it is building out American manufacturing with a rapid custom manufacturing software to production platform. It raised its first institutional funding of $110 million led by , and founders and . The 7-year-old Reno, Nevada-based company supports small-scale inventors to large-scale enterprises and has shipped 30 million parts to 300,000 customers. The company was valued at $1 billion.

E-commerce

• , a real-time inventory management platform, raised a $170 million Series B led by and . Its sensor technology tracks items and its precise location and movement in the store. Retail customers include and . The 13-year-old New York-based company was valued at $1 billion.

• London-based , a booking service for hair salons, beauty experts and wellness salons raised a $80 million Series C led by . The 11-year-old London-based company was valued at $1 billion.

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• , a nuclear fusion startup spun out of Tsinghua University, raised a $74 million Series A funding. The 4-year-old China-based company was valued at $1 billion.
• , a provider of fast charging batteries, raised a $60 million Series C led by strategic investor . The batteries are used in data centers, robotics, electric vehicles and grid infrastructure. The 7-year-old Cambridge, UK-based company was valued at $1 billion.

Social mediaÌı

• Creator platform raised its first external funding, a $535 million private equity round led by , which now owns around 16% of the company. The 10-year-old London-based adult content platform was valued at $3.2 billion. Its CEO noted the company has paid out since 2016.

Data centerÌı

• Modular data center builder raised a $230 million Series B led by , and. In partnership with the company plans to build capacity for secure data centers useful for military and remote manufacturing environments. The 3-year-old San Francisco-based company was valued at $2.2 billion. Customer booking for fiscal year 2026 was up 540% from 2025.Ìı

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• São Paulo-based , a Brazilian AI legal platform to manage company litigation, raised a $100 million Series B led by that valued the 2-year-old company at $1.2 billion. Enter counts , and among its customers, who use its technology along with law firms to handle litigation paperwork and settlements. Around have been managed through the platform. led the Series A.

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• , a digital asset trader, raised a $150 million funding led by , UK bank Standard Charter’s fintech arm. The deal brings digital assets into banking and represents GSRs first strategic external investor. The 12-year-old London-based company was valued at $1 billion.Ìı

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• , a security platform built for an open-source automated coding environment, raised a $60 million Series C led by . The platform is adopted by companies including Anthropic, , , , and and supports 27,000 organizations. Its socket firewall product is free to block malicious packages. The 6-year-old Stanford, California-based company was valued at $1 billion.

Related 91¾«Æ· unicorn lists:Ìı

• (1,785)
• (619)
• (160)
• (189)
• (118)
• (102)
• (921)
• (525)
• (241)
• (39)
• (486)

Related reading:

• Anthropic Files Confidentially For IPOÌı
• Active Startup Investors Didn’t Hold Back In May
• Anthropic Funding Pushed Startup Investment To Near-Record Levels In May As Exit Market ReopenedÌıÌı

Methodology

The 91¾«Æ· 91¾«Æ· is a curated list that includes private unicorn companies with post-money valuations of $1 billion or more and is based on 91¾«Æ· data. New companies are as they reach the $1 billion valuation mark as part of a funding round.Ìı

The unicorn board does not reflect internal company valuations — such as those set via a 409a process for employee stock options — as these differ from, and are more likely to be lower than, a priced funding round. We also do not adjust valuations based on investor writedowns, which change quarterly, as different investors will not value the same company consistently within the same quarter.Ìı

Funding to unicorn companies includes all private financings to companies that are tagged as unicorns, as well as those that have since graduated to .Ìı

Exits analyzed here only include the first time a company exits.Ìı

Please note that all funding values are given in U.S. dollars unless otherwise noted. 91¾«Æ· converts foreign currencies to U.S. dollars at the prevailing spot rate from the date funding rounds, acquisitions, IPOs and other financial events are reported. Even if those events were added to 91¾«Æ· long after the event was announced, foreign currency transactions are converted at the historic spot price.

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This is a weekly feature that runs down the week’s top 10 announced funding rounds in the U.S. Check out last week’s biggest funding deal roundup here.

Startup investors were in a spendy mood this week, backing more than a dozen rounds in the multiple hundreds of millions. Of those, the biggest one went to spend-management platform , which closed on $750 million, followed by three $500 million rounds for companies in the AI and space tech sectors.

1.Ìı, $750M, finance software: Spend-management software provider Ramp secured $750 million in a financing led by , Ìıand . The round set a $44 billion valuation for the 7-year-old, New York-based company.

2. (tied) , $500M, space tech: Redondo Beach, California-based Impulse Space, a developer of spacecraft and propulsion systems for transport, moving and orbital repositioning in space, raised $500 million in Series D funding. and led the financing which brings total investment to date to more than $1 billion.Ìı

2. (tied) , $500M, AI developer tools: Supabase, provider of an open source platform for developers and AI app builders, closed on $500 million in fresh funding. led the financing, which set a $10.5 billion valuation for the 6-year-old, San Francisco-based company.

2. (tied) , $500M, foundational AI: New York-based Flourish, a startup working on artificial intelligence models inspired by the human brain, raised $500 million in initial funding. Backers include , Ìıand .

5. , $465M, fusion energy: Helion, a startup with a mission to build the world’s first fusion power plant, picked up $465 million in Series G funding led by at a $15.5 billion post-money valuation. The round brings total reported funding for the Everett, Washington-based company to at least $1.5 billion, per .Ìı

6. , $435M, longevity medicines: NewLimit, a developer of medicines designed to restore youthful function in old cells through epigenetic reprogramming, closed on $435 million in Series C funding. led the financing for the South San Francisco, California-based company, which was co-founded by CEO .

7. (tied) , $400M, AI for music: Suno, a provider of AI tools for making music, raised $400 million in Series D funding led by . The round set a $5.4 billion valuation for the company, which is currently facing lawsuits from multiple music labels for training its AI on copyrighted materials.

7. (tied) , $400M, robotics: Generalist AI, a startup focused on using AI to enable robots to do complex tasks, picked up $400 million in new funding led by . The financing reportedly set a $2 billion valuation for the 2-year-old, San Mateo, California-based company.

9. , $350M, AI enterprise software: AlphaSense, an AI-enabled market intelligence and workflow orchestration platform, closed on $350 million in a new funding round led by , , , Ìıand . The round set a $7.5 billion valuation for the New York-based company.

10. , $300M, defense tech: Defense tech startup Mach Industries raised $300 million in Series C funding at a $1.8 billion valuation. and led the financing for the 3-year-old, Huntington Beach, California-based company.

Methodology

We tracked the largest announced rounds in the 91¾«Æ· database that were raised by U.S.-based companies for the period of May 30-June 5. Although most announced rounds are represented in the database, there could be a small time lag as some rounds are reported late in the week.

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A grab bag of funded startups caught our attention this past month, from a previously bootstrapped custom metal manufacturer that got its first outside funding from big-name Silicon Valley backers, to a startup that aims to provide geothermal energy from underwater volcanoes to small island nations. Let’s take a look.

$110M for on-demand custom manufacturing

First, let’s start with a refreshingly non-AI round, and a sizable one at that.

Reno, Nevada-based said last month that it has raised $110 million in funding led by brothers and founders and , along with and , at a $1 billion valuation.

The company operates an on-demand manufacturing platform specializing in custom-cut metal and fabrication. The round is its first venture investment, and apparently came only after Sequoia’s flew to Reno to woo SendCutSend CEO into accepting Silicon Valley backing. Previously, Belosic had bootstrapped the company, founded in 2018, with personal savings, bank loans and credit cards, he told .

He held little interest in taking cash from startup investors until SendCutSend started to be flooded earlier this year with orders from AI-driven industries including robotics and data centers, and Belosic said he realized the business needed outside investment to grow.

Investor of Paradigm told WSJ that underlying SendCutSend’s booming business is intense demand for rapid, on-demand sheet metal and custom parts. “If you think about the entire frontier of robots, defense companies, rocket companies, electric-car companies, they all need very fast turn prototyping,� he said.

The investment is Paradigm’s first into the manufacturing sector, he noted.

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$100M for insurance-covered metabolic health counseling

GLP-1 weight-loss drugs may be booming, but a well-funded startup is betting that medication alone isn’t enough to solve the chronic disease crisis.

, a New York-based metabolic health startup that combines dietitians, AI tools and GLP-1 medication management, last month said that it raised a $100 million Series C round led by . , , and a long list of other investors also backed the round, which brings the company’s total funding to date to just over $213 million, .

Founded in 2021, Nourish operates what it describes as the country’s largest dietitian-led metabolic health clinic, pairing more than 10,000 registered dietitians with AI coaching, lab testing and virtual care. The company has increasingly expanded into GLP-1 prescribing and medication management as demand for drugs such as Ozempic and Wegovy continues to surge.

Nourish said it has partnered with hundreds of health insurers in the U.S. and that its service is covered by most plans.

Its pitch is that the next phase of the GLP-1 boom will require more than prescriptions. While the drugs have transformed obesity treatment, many patients struggle to stay on them long term or maintain results after stopping, according to the company. Nourish is positioning itself as a broader metabolic health platform focused on nutrition, behavior change and ongoing clinical support alongside medication.

“Chronic disease is the central failure of U.S. healthcare — nearly 200 million Americans affected, trillions spent, and outcomes that still don’t move,â€� Menlo Ventures partner said in a statement. “What Nourish has built in four years is remarkable: a care model that actually bends the cost curve, with 10,000 dietitians, deep payer relationships, and clinical outcomes patients stick with.â€�

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$58M for Gen Z group travel adventures

Group travel startups are having a moment as younger travelers increasingly look for ways to meet people while exploring new destinations.

, a Milan-based startup that organizes group travel experiences for millennials and Gen Z travelers, raised a €50 million (roughly $58 million) Series C funding round as it looks to expand further across Europe and enter the U.S. market. The round was led by .

Founded in 2017, WeRoad operates a platform that connects solo travelers and small groups through curated multiday trips led by coordinators. The company says it has served more than 300,000 travelers across over 1,000 itineraries, with offerings ranging from adventure travel and cultural experiences to outdoor excursions. Participants are typically grouped with strangers in similar age ranges, turning the trips into a hybrid of travel booking and social networking.

“We live in a time when artificial intelligence and social media are reshaping the way we connect with each other. And amid all this digital connection, real human connection has become increasingly rare. Around 30% of young adults say they feel lonely every day. In the United States, this phenomenon is especially significant,� the company said in a statement. “We believe we have an answer. Not the only one, not a perfect one, but a real one: putting people in a room together (or on a quad bike in Morocco, in a canoe in Vietnam, or in front of a sunset in Patagonia) and letting whatever is meant to happen, happen.�

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$26M to keep AI data centers cooler

AI may be driving the data center boom, but keeping those facilities cool is becoming a business opportunity in its own right.

, a U.K.-based startup developing precision liquid cooling systems for AI infrastructure, said last month that it raised a $26 million Series B as demand surges for technologies that can manage the growing heat and power requirements of next-generation AI data centers. The round was led by and and brings Iceotope’s total funding to date to just under $100 million, .

Founded in 2005, Iceotope has developed a chassis-based liquid cooling approach designed to replace traditional air cooling and cool entire systems rather than individual chips. The company says it now holds 219 granted and pending patents. It said it will use the new funding to expand product and engineering development, grow its patent portfolio and accelerate partnerships that bring its cooling technology to market.

The raise comes as AI workloads create mounting challenges for conventional cooling systems. Iceotope argues its technology can reduce energy consumption and water use while supporting high-density AI and high-performance computing deployments in both data centers and edge environments.

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$25M for geothermal energy from subsea volcanoes

As AI companies scramble for more electricity, investors are increasingly willing to fund some unconventional ideas for generating it. One of those is , a Seattle-based startup developing subsea geothermal power systems designed to tap into heat generated by subsea volcanic activity.

The company recently raised between $25 million and $30 million in a seed round led by , sources familiar with the matter .

Founded just last year, Endurance Energy is targeting island nations — where it says electricity can cost almost 7x as much as in the U.S. — industrial sites and eventually hyperscale data centers that need large amounts of reliable power.

Unlike solar and wind, geothermal energy carries the promise of round-the-clock, renewable baseload electricity, a feature that has become increasingly attractive as AI infrastructure drives soaring power demand.

Endurance says its seafloor geothermal generators could deliver gigawatts of power from hydrothermal systems along tectonic plate boundaries and volcanic regions. It is , where about 80% of electricity generation still relies on imported diesel fuel.

Earlier this year, the company signed an agreement with the Tongan government and launched a pilot project aimed at harnessing geothermal heat generated by subsea volcanic activity around the island nation.

“Clean geothermal power will enable us to substitute most of our diesel base load power and further insulate ourselves from future external shocks caused by geopolitical conflicts and global economic impacts,� Tongan Prime Minister Lord Fakaf�nua said in a statement.

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This is a weekly feature that runs down the week’s top 10 announced funding rounds in the U.S. Check out last week’s biggest funding deal roundup here.

Venture funding has always been a world of haves and have nots. And these days, the haves are having more than ever. Case in point this week was . The 5-year-old generative AI giant secured $65 billion in Series H funding this week, pushing its post-money valuation to a mind-blowing $965 billion.

After that, the next-biggest financing was a $1 billion round for AI software development tool maker , lifting its valuation to $26 billion. Companies in a range of other sectors also managed to secure sizable though smaller rounds, in areas including commerce logistics, developer AI, insurtech, fusion and more.

1. , $65B, foundational AI: Generative AI company Anthropic raised $65 billion in a Series H funding round, more than doubling its post-money valuation to a staggering $965 billion. San Francisco-based Anthropic said , , and led the financing, and that , , , , and co-led the investment.

2. , $1B, AI software development: Cognition, developer of AI software engineer Devin, has closed on over $1 billion at a $26 billion valuation. , , and 1Ìıled the financing for the San Francisco-based company.

3. , $250M, logistics: Atlanta-based Stord, developer of a fulfillment network, software and AI tools for independent brands, secured $250 million in Series F funding. The round set a $3 billion valuation for the 11-year-old company.

4. , $113M, AI for developers: OpenRouter, a marketplace for AI models, secured $113 million in Series B funding. led the financing for the New York-based startup.

5. , $106M, insurtech: San Francisco-based Corgi Insurance, developer of an AI-native insurance platform for startups, picked up $106 million in Series B1 funding led by . The financing, which set a $2.6 billion valuation, comes just three weeks after Corgi $160 million in Series B funding at a $1.3 billion valuation.

6. (tied) , $100M, fusion energy: Kearny, New Jersey-based Thea Energy, a developer of technology for fusion energy systems, raised $100 million in Series B funding led by . Thea says the funding will go toward manufacturing infrastructure.

6. (tied) , $100M, healthcare data: Garner Health, a platform for finding healthcare providers, closed on $100 million in Series E funding led by . The financing set a $2.74 billion for the New York-based company.

8. , $90M, space tech: Observable Space, a space tech startup that develops and builds advanced optical systems, says it raised $90 million in Series A funding led by to scale manufacturing and develop its technology. The Santa Monica, California-based company also announced that it secured a $94 million contract with the.

9. , $59M, AI video: Reactor, a San Francisco-based developer platform for real-time generative video, emerged from stealth with $59 million in funding led by .

10. , $52M, cancer detection: San Diego-based ClearNote Health, a developer of early detection and monitoring tests for multiple forms of cancer, picked up $52 million in Series D financing. Founding investor led the round.

Methodology

We tracked the largest announced rounds in the 91¾«Æ· database that were raised by U.S.-based companies for the period of May 23-29. Although most announced rounds are represented in the database, there could be a small time lag as some rounds are reported late in the week.

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The global innovation economy remains largely defined by agglomeration dynamics. Worldwide, 19 ecosystems dominate the innovation landscape, increasingly concentrating innovation demand (corporates) and supply (scaleups) — attracting further growth capital (investors).

Meanwhile, other ecosystems struggle to achieve a meaningful presence on the global innovation map and are at serious risk of technological disruption and economic downfall.

Yet something is happening below the surface. Over the past decade, the composition of the Global Innovation Ecosystems Life Cycle Curve changed dramatically, as the number of scaleup ecosystems worldwide has more than doubled.

The trend is not stopping just here: we expect these figures to even triple in the coming years.

In this new scenario, emerging innovation economies hold the potential for disrupting the agglomeration paradigm, toward a new scheme of interconnected networks of specialized local innovation hot spots.

Among them, there is also Africa. While the continent still lacks ecosystems at the most advanced stages of maturity, it now counts four ecosystems at the startup stage and 40 at the standup stage, compared with respectively 25 of those 10 years ago, according to by my organization, , in collaboration with and .

Africa: the awakening giant of the coming decade?

As of today, Africa’s innovation economy includes 883 tech scaleups that have raised a combined $24.7 billion. Despite this progress, the continent still represents only about 1% of global figures.

The African innovation landscape remains highly concentrated around four main hubs: South Africa, Egypt (North-East), Nigeria (West Africa) and Kenya (East Africa). The North-Western corner of the continent still lacks a dominant hub, although Tunisia, Morocco and Algeria remain the leading candidates.

A testbed for clean technologies?

Emerging innovation economies that thrive on the global innovation map typically build on top of highly specialized, unique local strengths.

Our recent analysis has identified clear evidence that Africa holds significant potential over the development of clean energy systems and technologies.

The relative prominence of the cleantech sector in Africa is evident from the data:

• Africa is home to 95 cleantech scaleups, representing roughly 11% of the total scaleup base.
• Collectively, they have attracted approximately one-fifth of all capital deployed to African ventures.
• Cleantech has also generated a disproportionate share of high-growth leaders, accounting for around 20% of both scalers (scaleups that raised more than $100 million) and super scalers ($1 billion-plus).

Within cleantech, a highly specialized vertical is also emerging, what we might call “gridtech�:

• It comprises 16 scaleups (17% of the cleantech total) and two scalers (25% of total).
• It has attracted around 30% of total cleantech funding.
• Africa’s sole cleantech tech giant, Kenya-based , operates within this gridtech vertical.

That said, the numbers still point to a gap.

The elephant in the room

The main challenge is the grid infrastructure deficit, which remains the primary bottleneck to scaling energy system technologies. As shown in the map below, Africa’s grid infrastructure is highly fragmented: High-voltage networks are concentrated in a few densely populated areas, while large parts of the continent remain largely disconnected.

As a result, grid infrastructure development and electrification are key to unlocking Africa’s growth — consider that Africa still accounts for only about 5% of global energy supply — and its innovation potential.

At the same time, the continent holds world-class renewable resources, including approximately 13% of global technical hydropower potential and around 60% of the world’s best solar resources.

Africa’s energy system is expanding, but fully unlocking its economic and innovation potential will depend on accelerating electrification and strengthening grid infrastructure.

Blended finance will be critical to enable this growth. Both private and public capital are required: private capital drives innovation, while public finance enables foundational infrastructure such as grid expansion.

In particular, private capital needs to be complemented by structured public finance initiatives to address the inherent limitations of a relatively small domestic VC market, which remains heavily focused on early-stage investments.

Public capital will be essential for infrastructure development. In gridtech especially, public investors are expected to account for up to about 80% of total investments by 2030, reflecting the capital intensity and risk profile of grid infrastructure.

International capital still dominates the market, with approximately 69% of active investors originating outside Africa, underscoring continued reliance on foreign capital despite growing local participation.

Get the full story in our report:

is chairman of and a professor at . He is a serial entrepreneur who has started three startups in his career, the last of which is , among the five Italian scaleups that have raised the largest amount of capital. He is recognized among the leading international experts in open innovation and has wide experience in setting up and managing open innovation projects — venture clients, venture builders, intrapreneurship, CVCs — with large multinational companies, as well as advising and training on this subject. Onetti has a column on () and several other tech blogs.

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Defense, energy, robotics and government have historically been classic no-go areas for VC investment. These “hard� industries have slow procurement cycles, tight regulatory oversight and high-friction customer migration in common. Legacy software vendors serving them have benefited from a barrier of complexity to innovate slowly without facing the risk of customer churn.

This made the victims of this year’s AI anxiety-driven sell-off all the more dramatic. Software juggernauts serving heavy industries — , , , — have gone from safe bets to being the subject of investor scrutiny.

While headlines have attributed that sell-off to quick-fire launches of tools for vertical industries, there’s more at play. The macro trend is a newfound founder enthusiasm to build AI-native entrants in legacy industries, and the backing they’re enjoying from VCs that can see the once-in-a-generation opportunity to disrupt entire industries.

Why investor perceptions are changing

Context is important. Geopolitical instability, supply chain pressure and energy security concerns have placed industrial resilience at the center of national policy.

Be it the U.S. or across Europe, policymakers are prioritizing investment in grid upgrades, transportation networks and public sector infrastructure, while also re-examining procurement and compliance systems that have slowed the adoption of emerging technologies that could bring said industrial resilience about quicker.

At the same time, quick advances in AI and agentic systems make it possible to build a new class of AI-native software tailored to “hard� industries through deep integration with verticalized tooling and specialist automation of critical workflows.

Age-old incumbent moats, like cumbersome migration cycles that put businesses off moving to new software providers, are also being challenged as embedded automation cuts migration processes down from weeks to days.

The creation of software in and of itself has become commoditised in the AI era, and more investors are spotting that operational depth, intuitive UI/UX, speed to market and seamless integration into complex real-world systems are traits of high-quality vertical software that startups are well-placed to build.

Investors are also realizing that most of the available value from horizontal SaaS has been extracted. In those early post-ChatGPT years, VCs widely backed AI companies building for non-regulated SMB adoption — exactly the audience that foundational model players like and Anthropic are now making inroads with as they push into enterprises. Foundational models are general in nature, and their verticalization can therefore only stretch so far. Given this, AI-native products built for heavy industries are compelling and competitive propositions for VCs.

Growing faith that incumbents are vulnerable

There’s always been lots of skepticism among investors and tech executives that AI startups can meaningfully challenge incumbents that have been on top for decades. But those companies are operating over sprawling product architecture and processes that were built in the pre-AI era.

Pivoting from that state of affairs to AI-native systems is a massive undertaking, whereas new companies are being launched with those systems in place from day one. Incumbents also have a low incentive to innovate at pace when customer churn is limited. But in the current context of breakneck speed improvements to AI models and agentic systems, waiting for churn to show up will be too late.

Scepticism also risks overlooking the profile of outstanding founders building AI-native challengers. Some of the fastest-growing startups in defense, energy, government and the public sector are led by people who came directly from the same industries they are transforming. Their understanding of sector constraints and operational realities gives them an advantage over general software providers that lack the same specialism and experience.

Picking up pace

Savvy entrepreneurship and VC investors are colliding to make a play for hard sectors. Once seen as off-limits due to procurement complexity or regulatory burden, these sectors represent huge, untapped potential in the new AI-native era.

The emerging companies offering solutions designed for these industries with deep, vertical-specific tooling integration and critical workflow automation are well placed to command a growing share of overall AI funding as they serve customer pain points that have gone unanswered for years.

We are talking about disruption within markets worth trillions. The scale of the opportunity for growing VC interest in sectors they’ve historically avoided is no mystery or miscalculation. The vision is an ambitious one. Rather than simply building better software, the foundational sectors of the world economy are about to be reimagined.

is a partner for the U.S. and Europe at early-stage venture capital firm . He currently oversees the deployment of the firm’s latest $1 billion fund, backing a range of AI-native startups building to disrupt legacy industries and business processes. In a personal capacity, Cuvelier wrote an angel check for at pre-seed.

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This is a weekly feature that runs down the week’s top 10 announced funding rounds in the U.S. Check out last week’s biggest funding deal roundup here.

Defense tech unicorn led the fundraising lineup in a week heavy with rounds for companies focused on applications in the physical world. Anduril’s $5 billion financing was by far the biggest. Other large rounds went to companies focused on supplying data power, robotics, space tech, biotech, and even strawberries.

1.Ìı, $5B, defense tech: Defense tech unicorn Anduril Industries raised another $5 billion in funding at a $61 billion valuation — double the valuation of $30.5 billion it received less than a year ago. The Series H round, led by and , brings the Costa Mesa, California-based company’s total raised to date to $11.4 billion, .ÌıÌı

2.Ìı, $775M, energy: Houston-based VoltaGrid, a provider of mobile natural gas generators for data centers, microgrids and industrial applications, secured $1 billion in strategic investment from and . The investment includes $775 million in capital funding and a $225 million secondary purchase from existing investors.

3.Ìı, $400M, robotics: Palo Alto, California-based Mind Robotics, developer of an AI-enabled industrial robotics platform, picked up $400 million in new financing led by . The round brings total funding to date to more than $1 billion for the startup, which launched in 2025 as a spinout of .

4.Ìı, $275M, space tech: Cowboy Space, a developer of rockets and satellite infrastructure to power and run AI compute in space, closed on $275 million in Series B funding at a $2 billion valuation. led the financing for the San Carlos, California-based startup, which was founded by co-founder .Ìı

5.Ìı, $150M, indoor farming: Oishii, operator of highly automated indoor farms for growing strawberries, raised $150 million in Series C funding led by . Founded in 2016, the Jersey City, New Jersey-headquartered startup has raised $370 million in total funding to date.

6.Ìı, $125M, cybersecurity: San Jose-based Exaforce, developer of an AI-native security operations platform, secured $125 million in Series B funding from backers including , , , ÌıandÌı .

7.Ìı, $122M, biotech: Create Medicines, a Cambridge, Massachusetts-based startup focused on in vivo immunotherapies for autoimmune diseases and cancer, closed on $122 million in Series B funding. , , and led the financing.

8.Ìı, $100M, autonomy: Providence, Rhode Island-based HavocAI, a provider of tools for developing military and commercial-grade autonomous systems across sea, air and land, secured $100 million in Series A funding. The round brings total funding to date for the 2-year-old company to $200 million.

9.Ìı, $65M, space tech: Star Catcher, a startup that says it is building the first power grid in space by beaming concentrated solar energy on demand to satellites, picked up $65 million in Series A funding. , and led the financing for the Jacksonville, Florida-based company, which was founded less than two years ago.

10.Ìı, $64M, data center power: GridCare, developer of technology to more efficiently provide power to AI data centers, raised $64 million in Series A funding. led the financing for the Redwood City, California-based startup.Ìı

Related reading:

• Anduril Raises Another $5B As Defense Tech Startups Shatter Funding RecordsÌı

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AI and software continue to draw the biggest share of startup investment, but most of the interesting companies that caught our eye in the past month were working on problems in the physical world, often far from the glow of a laptop screen.Ìı

They include a defense-tech startup that aims to bring manufacturing closer to the frontlines, a company working to recycle valuable raw materials from defunct solar panels at industrial scale, and a startup that wants to produce cell-based milk for the dairy supply chain. Let’s take a look.

$82M to build near the battlefield

A decade ago, defense tech was considered a niche and sometimes controversial corner of venture capital, with few startup investors daring to place bets on companies working with the military.Ìı

How times have changed. Already this year, $13.6 billion in venture investment has gone into companies in 91¾«Æ·â€™s military, national security and law enforcement categories — more than 1.5x last year’s annual total.Ìı

is one of the latest defense startups to get some of that funding, with an approach that aims to bring manufacturing closer to the battlefield. The San Diego-based startup last month announced an $82 million Series B led by .Ìı

Firestorm builds expeditionary manufacturing systems and modular drones for military use. Its containerized “xCell� manufacturing platforms are designed to produce drones, replacement parts and other systems closer to the battlefield, a concept gaining traction as militaries rethink supply chains and logistics in contested regions such as the Indo-Pacific.

Existing and new investors including, , , , and others also joined its latest funding round, which brings Firestorm’s total funding to nearly $150 million, .

“The ability to produce, adapt, and sustain systems at speed and scale will define outcomes in future conflict,â€� , founder and chief investment officer at Washington Harbour Partners, said in a statement. “We’re excited to lead Firestorm’s Series B and back a company building a new model for manufacturing that replaces centralized supply chains with deployable, containerized units that can operate at the edge.”

The raise lands amid a broader surge in investor appetite for military tech, not just from defense-industry investors but also some of Silicon Valley’s biggest venture names. Sector heavyweight recently raised another $5 billion at a staggering $61 billion valuation in an – and -led round, underscoring just how mainstream venture-backed defense startups have become.

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$60M for a legal tech operating system

Legal tech has been one of the fastest-growing startup sectors in recent years, at least when measured by funding to the area, with venture investors pouring a record $4 billion-plus into the industry last year. That growth, of course, has been driven by AI’s rapid automation of many aspects of the notoriously paperwork-heavy industry.

Adding to this year’s tally is , a startup that says it’s building the operating system and brand for AI-native law firms. The startup said last month that it raised $60 million in Series A funding at a $750 million valuation from big-name investors. led the round and , and participated.

Manifest OS says it takes a different tack than most legal tech startups. Rather than sell software to traditional law firms that operate under a billable hour model, the company only caters to AI-native firms that charge clients based on outcomes.

“Companies want fee transparency, predictability, and speed,â€� , a Manifest investor and former general counsel for Ìı1, and , said in a statement. “Lawyers want to focus on delivering results, not justifying billable hours. Manifest OS’s model and use of advanced technology align those interests in a way the traditional system simply doesn’t.â€�

Along with AI software that helps attorneys with tasks like client communications, legal research, document drafting and billing, Manifest OS also offers a centralized back office to handle client intake, business development, paralegal work and other administrative tasks. That, according to the firm, frees attorneys up to focus on more complex legal work.

One important caveat: All firms that use its platform operate under the Manifest Law name. According to the startup, that results in a consistent brand presence, pricing, response time and service quality to clients. Its is a business immigration law firm.

The startup says it has already served 150-plus corporate clients, including large tech companies, since launching 18 months earlier. It has hired more than 100 attorneys to date, it said, less than 1% of those that applied.

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$23M for industrial solar panel recycling

French cleantech startup said last month that it has secured €20 million (about $23 million) in Series B and grant funding to tackle a growing problem: industrial-scale solar panel recycling.Ìı

By 2050, tens of millions of tons of solar panels are expected to become defunct, according to ROSI. The company’s technology recovers high-purity raw materials including silver, silicon, copper, aluminum and glass from those panels so that they can be recycled into new products.Ìı

ROSI said the new funding will be used to build its first large-scale recycling plant in Spain. The site will be able to process 10,000 tonnes per year.Ìı

The funding was led by , , and Spanish family office . Zurich-based corporate advisory firm , which specializes in deep tech, acted as strategic financial adviser and investor. Other investors included unnamed Swiss and Polish family offices.

“Our ambition is to build a European-scale industrial platform for circular management and the production of strategic raw materials, transforming end-of-life solar panels into a reliable source of high-purity materials for the European industries of tomorrow,� ROSI President and co-founder said in a statement.

The investment comes as cleantech funding has seen tepid investor enthusiasm in recent years. Overall funding to startups in 91¾«Æ·â€™s cleantech-, electric vehicle- and sustainability-related categories fell to a five-year low in 2025. Still, some areas — including solar and recycling — have continued to see larger rounds.

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$2.3M for a cell-based milk supplierÌı

Venture investment in food and beverage startups has fallen precipitously in recent years, from more than $22 billion in the peak year of 2021 to . Companies working on cell-based alternatives to traditional sources of protein such as meat and dairy products, in particular, have largely fallen out of favor with startup investors, 91¾«Æ· data shows.

That makes Montreal-based ’s recent $3.2 million CAD (roughly $2.3 million) seed round all the more interesting. The company, previously named BetterMilk, says it produces “complete milk� — with proteins, fats and sugars — from mammary cells in a bioreactor, without employing any cows.

Its recent round was led by , with participation from , , and existing investors including , and .

Rather than make a direct-to-consumer play, as many food and beverage startups have done, Opalia is positioning itself as a supplier in the food industry. The company recently inked a two-year deal with dairy supplier and a paid pilot with an unnamed “Canadian division of a leading global dairy group.�

“We see Opalia as a foundational player in the next era of dairy,� , managing partner at Nadarra Venture, said in a statement. “What sets them apart is a combination of highly credible, differentiated science and a clear, executable path to scale within existing dairy infrastructure, addressing the economics required to compete globally. Today, global demand for dairy is outpacing supply, and the traditional system is under increasing pressure from climate and resource constraints, making innovation no longer optional.�

Opalia plans to make its commercial debut in 2028 and said it’s currently working through the regulatory process in North America.

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$16M to automate the factory playbook

Mountain View, California-based last month announced a $16 million seed funding roundÌıto speed up what it calls one of manufacturing’s most stubborn bottlenecks: turning digital product designs into actual production plans.

The startup’s platform, dubbed AutoAssembler, plugs into existing CAD and PLM systems and uses AI to automate process planning, the painstaking engineering work required to determine how parts fit together, in what order they should be assembled, and how products can realistically be built at scale. C-Infinity says workflows that once took weeks can now be completed in minutes.

Its seed round was led by with participation from and

C-Infinity’s pitch taps into a broader trend gaining traction across industrial tech: software that doesn’t just analyze operations, but actively participates in physical production decisions. That kind of investment in physical AI — real-world applications of artificial intelligence, including in factories and on construction sites — has taken off this year.ÌıAll told, startups working on physical AI have already hauled in more than $37 billion in venture funding globally in 2026, , shattering the full-year records of $21 billion set in both 2025 and 2021.

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This is a weekly feature that runs down the week’s top 10 announced funding rounds in the U.S. Check out last week’s biggest funding deal roundup here.

Another week, another infusion of big AI rounds. For this past week, the largest fundraiser by a long shot was , a developer of AI customer experience tools that picked up $950 million. Other big rounds went to companies in sectors including satellite development, biotech, and, yes, more vertical AI and AI infrastructure.

1. , $950M, customer experience AI: Sierra, a provider of AI-driven tools for customer experience management, raised $950 million in fresh funding at a $15 billion valuation. and led the financing for the three-year-old, San Francisco-based company.

2.Ìı, $455M, space tech: Astranis, a developer of advanced satellites for high orbits, secured $450 million in equity and debt investment. The financing included a $300 million Series E equity round led by and and up to $155 million in credit through .Ìı

3.Ìı, $250M, biotech: Natick, Massachusetts-based Anagram Therapeutics, a developer of a pill for people living with exocrine pancreatic insufficiency due to cystic fibrosis, pancreatic cancer and related disorders, closed on $250 million in new funding from .Ìı

4.Ìı, $200M, AI software development: Blitzy, developer of an autonomous software development platform, picked up $200 million in fresh funding at a $1.4 billion valuation. Northzone led the financing for the Cambridge, Massachusetts-based company.ÌıÌı

5. , $160M, insurance: Corgi Insurance, provider of an AI-native insurance platform for startups, secured $160 million in Series B funding. led the financing, which set a $1.3 billion valuation for the San Francisco-based company.Ìı

6. , $140M, renewable energy: Portland, Oregon-based Panthalassa, which aims to perform AI inference computing at sea using power generated from ocean waves, raised $140 million in a Series B financing led by .

7. , $125M, insurance: Reserv, a provider of third-party administrator services to the insurance industry, closed on $125 million in a Series C funding round led by . Launched in 2022, New York-based Reserv has raised over $200 million in known funding to date, per 91¾«Æ· data.

8.Ìı, $107M, AI infrastructure: DeepInfra, a cloud platform for high-throughput AI inference, landed $107 million in Series B funding. and led the financing for the four-year-old, Palo Alto, California-based company.

9. , $60M, vertical AI: San Jose, California-based Tessera Labs, developer of an AI platform for enterprise ERP systems and data, secured $60 million in a funding round led by .Ìı

10. , $56M, gaming: Astrocade, developer of an AI platform for creating, building and playing games, announced $56 million in new funding. The funding for the Los Altos, California-based company includes a Series B led by and a Series A led by , Astrocade said.Ìı

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