Globally, robotics startups have so far raised $18.8 billion in 2026, compared to $15 billion in the full year of 2025. The figure also handily surpasses the $14.1 billion raised in the peak venture funding year of 2021, and we still have more than six months of fundraising left.

The impressive rise in funding reflects a marked shift in perception among venture investors about the robotics sector, which was traditionally considered an expensive, asset-heavy hardware gamble. In particular, investors appear to be drawn to startups working on embodied AI, or artificial intelligence with a physical body that interacts with the real world in real time.

Noteworthy recent rounds

The surge in funding is driven by a number of robotics-focused startups raising considerable capital from investors this year. Also, interestingly, two of the five largest raises in 2026 to date have been by Austin-based companies.

Topping the list of largest deals in 2026 so far is Austin-based , a defense tech startup focused on autonomous sea vessels. In March, the 4-year-old company raised $1.75 billion in Series D funding, bringing its total funding to around $2.6 billion. led the round, which set Saronic鈥檚 valuation at $9.25 billion 鈥� more than double its Series C level in 2025.

Earlier this month, Germany鈥檚 , a developer of AI infrastructure for robots to learn, collaborate and operate across real-world environments, said it secured up to $1.4 billion in Series C funding. led that raise.

In January, , a robotics company building an 鈥渙mni-bodied鈥� brain to operate any robot for any task, announced that it had raised $1.4 billion, tripling its valuation to over $14 billion. That financing came just over seven months after Skild raised at a $4.5 billion valuation. led the startup鈥檚 latest round, which included participation from , 鈥檚 venture capital arm.

On June 15, Beijing-based , which creates water robots and intelligent unmanned equipment, raised $1 billion in a massive Series A round led by .

And in February, AI-powered robotics company raised $520 million in an extension of its $415 million Series A raise in February 2025, bringing the total round to over $935 million. Existing backers , , and joined new investors, including and manufacturing giant in participating in the extension.

Interestingly, spinout has already raised two rounds in 2026. In March, the Palo Alto, California-based startup closed on a $500 million Series A round, co-led by and . Then in May, it raised another $400 million in a financing led by . The company is developing an AI-enabled industrial robotics platform focused on automating industrial and manufacturing tasks at scale.

Exits

While mergers and acquisitions have been relatively robust with several strategic buyouts, the robotics IPO landscape is a bit quieter, particularly in the U.S.

In China, however, a number of robotics companies have recently gone public. The of , targeting a $3 billion to $7 billion valuation, was considered a milestone for the industry. In March, the company filed for an to list on the , and its IPO was widely expected to spur other startups in the space to pursue their own public-market debuts.

, a startup based in China鈥檚 Shandong province that makes lightweight industrial robots, in May listed on the , raising about $86 million. And it did not disappoint. Robotphoenix closed its first full day of trading at HK$53.75 ($6.86 U.S.), up nearly 80%, though shares have dipped to the HK$37 range more recently.

On the M&A front, a number of Big Tech and automotive giants have been aggressively acquiring embodied AI and humanoid talent to anchor their physical automation strategies.

In February, AI-powered supply chain provider acquired , an Austin-based maker of autonomous forklifts and lift trucks.

Skild AI in April that it had picked up the robotics arm of in an effort to deploy its technology to warehouses.

And in May, tech giant entered the humanoid robotics field directly by acquiring San Diego-based . The team was absorbed into Meta’s Superintelligence Labs unit to accelerate training of its foundational physical AI model.

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Related reading:

• 5 Startup Sectors Seeing Big Funding Growth
• The Year Of Humanoid Robots
• Embodied AI Fuels Record Robotics Funding In China As IPO Momentum Builds
• Amid Record Robotics Funding, Apptronik Raises $520M Series A Extension To Boost Production Of Humanoid Robot Apollo
• Robotics Startup Skild AI Lands $1.4B, Tripling Valuation To $14B In Just 7 Months

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“Silicon Valley has done very well with software, but while software was eating the world, they forgot about silicon,” Barrett told 91精品 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 鈥� not just software 鈥� 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.

鈥淪cience lets you follow breadcrumbs from prehistoric plumage to semiconductors. One principle can be applied somewhere orthogonal and create extraordinary value,鈥� Barrett said in a lengthy interview with 91精品 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.

Gen茅 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鈥檛 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 鈥� and candidly, I feel the imperative 鈥� 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 鈥� 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 鈥斕齱hat’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 鈥� 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 鈥� which will replace transistors and semiconductors 鈥� 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 鈥� 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鈥檝e 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鈥檛 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鈥檙e 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 鈥� optical interconnects, memory systems 鈥� we have a best-in-class company at every point. We built the first AI accelerator a decade ago, and we鈥檝e 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鈥檙e 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鈥檚 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鈥檙e still 100x to 1,000x more energy-efficient on compute.

This technology has been around since last century, but it鈥檚 mainly been used for secure signals intelligence and radar applications. We鈥檙e 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鈥檝e been unable to train.

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

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

LLMs feel like brute-forcing something 鈥� like a drunk looking for keys under the streetlight. We鈥檙e pushing more and more into that, and I think that鈥檚 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鈥檙e 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鈥檛 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鈥檙e pretty, but not efficient. They shouldn鈥檛 be green; they should be black. We know how to make photosynthesis twice as efficient, and probably 5x more efficient.

We鈥檙e 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鈥檛 design things we can鈥檛 simulate. Our best computers cannot simulate the quantum nature of nature. That鈥檚 about to change.

We鈥檙e 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鈥檙e 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鈥檛 know how many things that animate our industry actually work. We don鈥檛 know how Tylenol works. We don鈥檛 know how the Type II superconductors we鈥檙e 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鈥檛 know why.

There are mysterious things we鈥檝e stumbled across that hint at an Aladdin鈥檚 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鈥檚 a long way off.

Data centers in space are stupid. You can鈥檛 operate a gigawatt data center in a thermos. We have terrestrial answers to those questions that we should pursue.

I鈥檝e 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鈥檛 drown our cities. The problem with transportation in cities is not the degree of autonomy. If we cared about traffic deaths, we鈥檇 worry about roundabouts.

There鈥檚 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 91精品, valued over $1 billion this past month, doing orbital data centers. Are you saying this whole category doesn鈥檛 make sense?

Barrett: To his credit, will show you a picture of what a 100-kilowatt data center looks like, and it鈥檚 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鈥檙e 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鈥檚 radiators and solar panels.

Starship has yet to actually put anything in orbit. It鈥檚 made some fireworks, which are pretty, and it鈥檚 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鈥檝e 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鈥檝e already made investments in things on a really steep trajectory.

Snowcap will take a decade before we鈥檙e building GPUs with that technology, but we鈥檒l have commercial product from them next year. We鈥檙e 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鈥檙e 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鈥檚 a sleeper in Fund I. Its first trick was to make MRI machines 100,000x more sensitive, and they鈥檙e shipping those. In the background they鈥檝e 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鈥檚 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 鈥� the only co-packaged optics on TSMC 鈥� we鈥檝e 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鈥檛 chatted about that you think is worth noting?

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

There are extraordinary pools of capital, pension funds and Australia鈥檚 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鈥檚 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鈥檛 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鈥檙e going to do more of that.

Do you feel encouraged by the amount of infrastructure build-out that鈥檚 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鈥檒l run LLMs on these data centers initially, but we鈥檒l run their descendants and other more useful things on these machines and on quantum machines.

It鈥檚 going to be hard to overbuild because computation is incredibly useful. There鈥檚 no upper bound. We鈥檙e 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鈥檙e 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.

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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.听

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.听

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.听

Unicorn IPOs

The board鈥檚 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 91精品 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 .听

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.听

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

New unicorns in May

Here are May鈥檚 new unicorn companies, including 10 companies that are less than 3-years old:听

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.听
• 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 鈥� , private equity investor and legal firm 鈥斕齣nvested $300 million into the round. and also invested in the joint venture. The less than 1-year-old-based, San Francisco-based company鈥檚 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.听
• Boston-based autonomous AI software developer raised a $200 million Series A led by . Blitzy鈥檚 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.听
• , a routing technology for applications to select from 400-plus models, raised a $113 million Series B led by Alphabet鈥檚 . 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.

搁辞产辞迟颈肠蝉听

• 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.听

• 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.听
• , 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.听

贬别补濒迟丑肠补谤别听

• , 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.听
• , 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.听
• , 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.

础别谤辞蝉辫补肠别听

• , 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.听
• 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 services听

• , 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.听
• 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.

惭补苍耻蹿补肠迟耻谤颈苍驳听

• , 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鈥檚 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.

贰苍别谤驳测听

• , 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 media听

• 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 center听

• 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.听

尝别驳补濒迟别肠丑听

• S茫o 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.

颁谤测辫迟辞肠耻谤谤别苍肠测听

• , a digital asset trader, raised a $150 million funding led by , UK bank Standard Charter鈥檚 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.听

厂别肠耻谤颈迟测听

• , 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 91精品 unicorn lists:听

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

Related reading:

• Anthropic Files Confidentially For IPO听
• Active Startup Investors Didn鈥檛 Hold Back In May
• Anthropic Funding Pushed Startup Investment To Near-Record Levels In May As Exit Market Reopened听听

Methodology

The 91精品 91精品 is a curated list that includes private unicorn companies with post-money valuations of $1 billion or more and is based on 91精品 data. New companies are as they reach the $1 billion valuation mark as part of a funding round.听

The unicorn board does not reflect internal company valuations 鈥� such as those set via a 409a process for employee stock options 鈥� 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.听

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

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

Please note that all funding values are given in U.S. dollars unless otherwise noted. 91精品 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 91精品 long after the event was announced, foreign currency transactions are converted at the historic spot price.

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Just through mid-May, China-based robotics companies this year have raised $5.6 billion across 176 deals, 91精品 data shows. That sum matches total investment to the nation鈥檚 robotics companies in all of 2021, the peak of the funding cycle. Investment in the sector has also already eclipsed the $4.3 billion raised by China-based robotics companies in all of 2025.

Startup funding in Asia overall surged to $27.4 billion in Q1, its highest level in over three years, with China capturing $16.5 billion 鈥� 60% 鈥� of that total, according to recent 91精品 data. Robotics contributed meaningfully to that $16.5 billion total, with startups in the sector raising $3.3 billion across 126 deals.

Embodied AI boom

A review of 91精品 data shows that investors now are no longer funding mostly pre-programmed hardware, but increasingly backing China-based startups working on embodied AI 鈥斕齩r artificial intelligence with a physical body that interacts with the real world in real time.

That shift toward artificial intelligence-driven robotics mirrors a global surge in investment into robotics and other physical AI startups. It鈥檚 also thanks to the rise of advanced, open-source reasoning models that have fundamentally changed how robots operate. Startups are moving away from coding robots line-by-line toward Vision-Language-Action models that allow physical machines to observe, reason and execute physical tasks end-to-end.

In China, robotics startups at the intersection of the software and hardware integration are drawing the largest checks in the space and often back-to-back funding rounds. They include:

• , a 1-year-old humanoid robotics company that integrates embodied intelligence that last month raised a massive $513 million seed round led by and . The Shanghai-based company was valued at $1.9 billion.
• , which develops robotic systems and automation solutions for industrial and service applications, closed a $140 million Series A extension round in January from investors including . Then just three months later, it raised $293 million in a massive Series B round co-led by and
• In February, Beijing-based , which says it鈥檚 building a 鈥渦niversal brain鈥� for robots, raised a $290 million Series A led by and . The 2-year-old company was valued at $1.5 billion. Then in April, it announced a $145 million Series A extension financing, bringing the total round to $435 million.
• Humanoid robotics company in February raised a $145 million Series B led by . The 2-year-old China-based company was valued at $1.4 billion. In April, it announced a $290 million extension to that round, bringing its total to $435 million
• Shenzhen-based , a builder of humanoid and quadruped robots, raised a $200 million Series B last month led by and . The 2-year-old company鈥檚 robots will be deployed for traffic, security and retail. It was valued at $1.5 billion.

Top investors

91精品 data shows the most active investors in the space are largely Asia-based. The busiest this year has been Hong Kong-based , taking part in six deals, including a $200 million round last month for humanoid robotics and embodied intelligence developer .

Among lead or co-lead investors, three China-based firms 鈥� , and 鈥� have each taken part this year in deals totaling $290 million or more.

Exits gain steam

Venture investors are likely feeling confident as the sector notches notable liquidity events, including IPOs and acquisitions.

The of , targeting a $3 billion to $7 billion valuation, is a milestone for the industry. The company in March filed for an to list on the , and its IPO would likely spur other startups in the space to pursue their own public-market debuts.

The sector has already seen some notable exits.

They include Hong Kong-based ,听 a Shanghai-based startup that makes lightweight industrial robots. The company on May 18 listed on the , raising about $86 million. And it did not disappoint. Robotphoenix closed its first full day of trading at HK$53.75 ($6.86 U.S.), up nearly 80%. (Interestingly, Chinese robotics firms as their primary liquidity hub.)

On the M&A front, in what is widely considered a historic first for China鈥檚 embodied artificial intelligence sector, AI robotics unicorn in July 2025 engineered a two-stage consortium takeover to in legacy manufacturer for about $290 million. AgiBot鈥檚 co-founder formally stepped in to chair Swancor, effectively turning the publicly traded shell into a direct extension of AgiBot.

Ultimately, it seems that 2026 is the year China鈥檚 robotics companies are pivoting from raising early venture rounds to mass production, as a domestic market that currently accounts for more than 43% of global robotics venture investment, per 91精品.

Related 91精品 queries:

Related reading:

• China Leads Asia鈥檚 Startup Funding To Its Highest Level In More Than 3 Years
• Amid Record Robotics Funding, Apptronik Raises $520M Series A Extension To Boost Production Of Humanoid Robot Apollo

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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.听

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鈥檚 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.听

How times have changed. Already this year, $13.6 billion in venture investment has gone into companies in 91精品鈥檚 military, national security and law enforcement categories 鈥� more than 1.5x last year鈥檚 annual total.听

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 .听

Firestorm builds expeditionary manufacturing systems and modular drones for military use. Its containerized 鈥渪Cell鈥� 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鈥檚 total funding to nearly $150 million, .

“The ability to produce, adapt, and sustain systems at speed and scale will define outcomes in future conflict,鈥� , founder and chief investment officer at Washington Harbour Partners, said in a statement. 鈥淲e’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鈥檚 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.

Related 91精品 query:

$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鈥檚 rapid automation of many aspects of the notoriously paperwork-heavy industry.

Adding to this year’s tally is , a startup that says it鈥檚 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.

鈥淐ompanies want fee transparency, predictability, and speed,鈥� , a Manifest investor and former general counsel for 听1, and , said in a statement. 鈥淟awyers want to focus on delivering results, not justifying billable hours. Manifest OS鈥檚 model and use of advanced technology align those interests in a way the traditional system simply doesn鈥檛.鈥�

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.

Related 91精品 query:

$23M for industrial solar panel recycling

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

By 2050, tens of millions of tons of solar panels are expected to become defunct, according to ROSI. The company鈥檚 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.听

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.听

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.

鈥淥ur 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,鈥� 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 91精品鈥檚 cleantech-, electric vehicle- and sustainability-related categories fell to a five-year low in 2025. Still, some areas 鈥� including solar and recycling 鈥� have continued to see larger rounds.

Related 91精品 query:

$2.3M for a cell-based milk supplier听

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, 91精品 data shows.

That makes Montreal-based 鈥檚 recent $3.2 million CAD (roughly $2.3 million) seed round all the more interesting. The company, previously named BetterMilk, says it produces 鈥渃omplete milk鈥� 鈥� with proteins, fats and sugars 鈥� 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 鈥淐anadian division of a leading global dairy group.鈥�

鈥淲e see Opalia as a foundational player in the next era of dairy,鈥� , managing partner at Nadarra Venture, said in a statement. 鈥淲hat 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.鈥�

Opalia plans to make its commercial debut in 2028 and said it鈥檚 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 round听to speed up what it calls one of manufacturing鈥檚 most stubborn bottlenecks: turning digital product designs into actual production plans.

The startup鈥檚 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鈥檛 just analyze operations, but actively participates in physical production decisions. That kind of investment in physical AI 鈥� real-world applications of artificial intelligence, including in factories and on construction sites 鈥� has taken off this year.听All 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.

Related 91精品 query: 听

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Existing backer (KIP) led the financing, which is described as a bridge round. (KBIC) also participated. The raise brings Santa Fe Springs, California-based Xpanner鈥檚 total funding to $38 million since its 2020 inception.

Xpanner turns construction equipment that customers already own into automated assets 鈥渨ithout replacing a single machine,鈥� according to , the company鈥檚 co-founder and CEO.听

鈥淭here鈥檚 no upfront investment, no rip-and-replace,鈥� Lee added. 鈥淟ike a smartphone gaining new capabilities through app updates, customers expand their automation through simple software updates.鈥�

The benefits for its customers include significant cost savings and shorter project durations, according to Lee.

Originally founded in South Korea, Xpanner moved its headquarters to the U.S. in 2023. Today, , , and are among its customers.听

Notably, all of Xpanner鈥檚 co-founders have deep industry experience. Lee spent two decades in executive positions at and , driving unmanned construction projects and corporate venture initiatives in the heavy equipment world. CFO spent over 12 years working in heavy equipment at Bobcat, followed by eight years in venture capital at Korea鈥檚 largest commercial bank. CTO led robotics and automation at for 20 years, becoming the first in the industry to commercialize semi-automation features for construction machinery.

Growth and a path to profitability

Xpanner is refreshingly transparent about its financials. The company grew revenue from $3 million in 2023 to $7 million in 2024 to $21 million in 2025, according to Park. It saw $8 million in revenue and $1 million in EBIT (earnings before interest and taxes) in the first quarter of 2026.

The startup is targeting $60 million in ARR by year鈥檚 end.

Impressively, the company says it maintains a gross margin above 80%, thanks mostly to its subscription-based AaaS model. It achieved monthly break-even in 2025, and Park said Xpanner is on track for full-year profitability this year.

鈥淥nce hardware is deployed, incremental subscription and service revenue flows at near-zero marginal cost,鈥� he said.听

The company plans to use its new capital in part to strengthen its development capabilities by advancing its next-generation physical AI hardware and software platform, deepening its core component engineering, and expanding its data and AI infrastructure.听

Some of its customers are still on a perpetual modular model, which includes the one-time purchase of its X1 Kit hardware paired with its software. Looking ahead, Xpanner expects to be fully on its subscription model by the end of the year.听

The company is also actively expanding into adjacent verticals, including battery energy storage systems (BESS) and AI data center construction.

鈥楽trong gross margins, near-zero churn鈥�

, managing director at KIP, told 91精品 News via email that his firm was impressed by Xpanner鈥檚 commercial traction and unit economics.

鈥淪trong gross margins, near-zero churn, and rapid account expansion are signals that the value proposition is real and not pilot-driven,鈥� he said.

director at KBIC, believes that most construction automation companies hit a scalability wall because they automate entire machines end-to-end. However, he said that since Xpanner’s task-specific approach scales through software rather than hardware redesign, the company 鈥渃an expand wallet share inside accounts without proportional cost.鈥�

鈥淭hat’s a software-economics business operating in a hardware-dominated market, and it’s rare,鈥� he wrote via e-mail.

Physical AI funding smashes records

Xpanner sits at the intersection of two sectors that have received strong interest from investors in recent years.

Startups working on physical AI 鈥� real-world applications of artificial intelligence, including technologies such as automated hardware and robotics 鈥� have already hauled in more than $37 billion in venture funding globally this year, , shattering the full-year record of $21 billion set in both 2025 and 2021.

At the same time, venture investment in real estate and property-related startups rebounded last year, largely driven by funding to AI-centric companies.

Related 91精品 queries:

• 听
• 听

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The Series H round, led by and , brings the Costa Mesa, California-based company鈥檚 total raised to date to $11.4 billion, per 91精品. The funding comes amid record venture investment into startups developing defense, wartime and national security technologies and a administration push to modernize the U.S. military.

Just through mid-May, defense-related startups 鈥� defined by 91精品 as the industries of military, national security and law enforcement 鈥� have raised nearly $13.6 billion this year, per 91精品 . That puts them on track to more than double the already record-breaking total of $8.8 billion raised in 2025, when Anduril was by far the sector’s largest venture capital recipient.

鈥淲hen we founded Anduril in 2017, defense was not a category that attracted significant venture investment,鈥� company CEO and co-founder said in a . 鈥淭hat has changed meaningfully over the last several years. Investors have increasingly recognized the scale of the technological and industrial challenges facing the United States and its allies. They are also observing an environment in which the most agile, adaptive, and ambitious companies are the ones most capable of solving these challenges.

In March, Anduril signed a $20 billion, 10-year contract with the to supply software and weapons. It also announced that it was part of a group of companies building the $185 billion missile defense system for the U.S. government.

After Anduril, several other defense-tech startups, all based in the U.S., have received sizable investments this year:

• : In March, San Diego-based Shield AI secured $2 billion in fresh funding led by and. The startup develops AI pilots and autonomous aircraft systems for military applications and has raised more than $3.5 billion overall, per 91精品 data.
• : Austin, Texas-based Saronic said in March that it has raised $1.75 billion in a Series D led by. The startup builds unmanned surface vessels for naval and defense use and has now brought in nearly $2.6 billion in total funding.听
• : Centennial, Colorado-based True Anomaly said last month that it has raised $600 million led by and as investors continue pouring capital into space-security infrastructure. The company develops spacecraft and orbital defense systems and has raised more than $1 billion to date, per 91精品.
• : Commercial space company Sierra Space said in March that it had raised $550 million in funding led by . The startup develops commercial space stations, satellite systems and the reusable Dream Chaser spaceplane for cargo and defense-related missions. The company, based in Louisville, Colorado, has now raised roughly $2.2 billion overall, according to 91精品.

Related 91精品 query:

Related reading:

• Sector Snapshot: Defense Tech Funding Hits Record High
• After Swarmer鈥檚 Soaring Debut, Here Are 12 Other Potential Defense Tech IPOs

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Two newly founded AI labs, both based in London and both with researchers from , raised large rounds out of the gate and made their 91精品 debuts. The two companies, and , both raised large initial fundings out of the gate, though take very different approaches to training AI.听 They were joined by another new unicorn in the foundation AI sector: , an open-source model company from China with on-device smaller models.听

Six companies working on humanoid robotics 鈥斕齠ive from China and one from Japan 鈥� also received billion-dollar-plus valuations last month. Quite a few of these companies are building models for robotic intelligence using simulated data.听

The financial services, defense, developer tools, energy and healthcare sectors each added two or three new unicorns in April.听

Of the 28 companies, 12 are U.S.-based and eight are from China. The UK counted two new unicorns last month, while Germany, Spain, Switzerland, India and Japan each added one.听

April鈥檚 new unicorns

Here are April鈥檚 new unicorn companies. Of the 28 companies, 26 are AI-related.听

Foundational AI听

• , a London-based AI lab using reinforcement learning rather than human-generated data, raised a $1.1 billion seed round led by and . The less than 1-year-old company was founded by of AlphaGo and . It was valued at $5.1 billion in its first funding.听
• London-based , a new AI intelligence lab with the goal of continuous learning improvement, raised a $500 million Series A led by and . Founded by DeepMind researchers and 鈥檚 1 previous AI lead, the less than 1-year-old company was valued at $4.5 billion.听
• Beijing-based , an on-device foundation model developer, raised funding led by and . Its open source MiniCPM is deployed in automotives, smartphones, PCs and home devices. The 3-year-old company was valued at $1 billion.听

搁辞产辞迟颈肠蝉听

• Shanghai-based is a robotics AI company building a foundational model as well as hardware. It uses simulated training to create a model for grasping and spatial awareness. The 1-year-old company raised a Series A round and was valued at $2 billion.
• Shanghai-based humanoid robotics company raised a $513 million seed round led by and HSG. The 1-year-old company was valued at $1.9 billion.听
• Beijing-based , a hardware and software developer of models for robotics using simulated data, raised a $220 million Series B. The 3-year-old company was valued at $1.5 billion.听
• Shenzhen-based , a builder of humanoid and quadruped robots, raised a $200 million Series B led by and . The 2-year-old company robots will be deployed for traffic, security and retail. It was valued at $1.5 billion.听
• Shenzhen-based , a commercial robotics company for delivery and commercial cleaning, raised a $146 million funding led by and . The 10-year-old company was valued at $1.5 billion.听
• Tokyo-based , a humanoid robotics company to address public safety and urban maintenance, raised a Series A led round. The 1-year-old company co-founded by was valued at $1 billion.

Financial services听

• , which automates research for investment banks, raised a $160 million Series D led by . The 4-year-old New York-based company was valued at $2 billion.
• Bangalore-based , a consumer and small business lending service, raised a $220 million Series E led by , , and . The 8-year-old company was valued at $1.5 billion.听
• , a banking and expense management service targeting small businesses and solopreneurs, raised a $100 million Series C led by , and . The 5-year-old San Francisco-based company, founded by college dropouts at the time, was valued at $1.4 billion.听

Defense听

• Space defense company raised a $600 million Series D led by and . The company has built software for space operations and an autonomous orbital vehicle called Jackal. The 4-year-old, Colorado-based company was valued at $2.2 billion.听
• Defense aviation company raised a $200 million Series C led by Khosla Ventures. The 7-year-old El Segundo, California-based builder of autonomous aircraft was valued at $1 billion.听

Developer tools听

• , a web search provider for AI agents used by and , raised a $100 million Series B led by Sequoia Capital. The 2-year-old Palo Alto, California-based company was valued at $2 billion.听
• , an agentic software coding tool for enterprises, raised a $150 million Series C led by . The 3-year-old San Francisco-based company was valued at $1.5 billion.听

贰苍别谤驳测听

• , developer of small nuclear reactors to provide direct power for AI data centers, raised a $340 million Series B funding. The 2-year-old El Segundo, California-based company was valued at $2 billion.听
• , a long duration energy storage battery provider, raised a $58 million Series C led by . The 12-year-old Bayern, Germany-based company that supports energy needs for grids, data centers and industry, was valued at $1.2 billion.听

Health care听

• Shanghai-based , a developer of a model for healthcare that includes computer vision and large language models, raised a $73 million Series A round. The 12-year-old company has built an assistant for doctors for screening, diagnosis and patient care, and was valued at $1 billion.听
• Switzerland-based , a developer of a peptide product to address enamel repair without needing surgery, raised a private equity funding led by . The 6-year-old company was valued at $1 billion.听

Data platform

• has built a semantic layer between data and agents necessary to interpret data and provide guardrails for AI. The 4-year-old San Francisco-based company raised a $120 million Series C led by and was valued at $1.5 billion.听

Manufacturing

• Shanghai-based , a collaboration tool to make factories more efficient, raised a $146 million Series D funding. The 10-year-old Shanghai-based company was valued at $1.3 billion.

Agentic AI

• , which builds agents trained on company data, raised a $80 million funding led by . The 1-year-old San Francisco-based company was valued at $1.3 billion.听

础别谤辞蝉辫补肠别听

• Madrid-based , which is building data from satellites tracking changes in the earth for various commercial needs, raised a $130 million Series B led by . The 6-year-old company was valued at $1 billion.听

Marketing & sales听

• , a provider of booking and customer service for the services industry using AI, has raised a Series B funding led by and . The 4-year-old New York-based company was valued at $1 billion. The company has raised $125 million in funding from seed through its Series B.听

Biotechnology听

• , an AI biotechnology infrastructure platform speeding up drug discovery, raised a $40 million Series E. The 8-year-old Waltham, Massachusetts-based company was valued at $1 billion.听

Waste management听

• converts unused food products into energy. It raised a Series C funding led by strategic partner . The 19-year-old Concord, Massachusetts-based company was valued at $1 billion.听

Related 91精品 unicorn lists:听

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Related reading:

• March Mints 11 New Unicorns, As $200B Is Added Through Up Rounds And Board Posts Strong Exits听
• Billion-Dollar AI Rounds Push April To Third-Highest Startup Funding Month In A Year
• This Is A Momentous Year For Early-Stage Unicorns听
• The Rising Investors Behind The New Unicorn Class听
• While OpenAI Shattered Records, Robotics and Semiconductor Startups Quietly Added The Most New Unicorns In February听

Methodology

The 91精品 91精品 is a curated list that includes private unicorn companies with post-money valuations of $1 billion or more and is based on 91精品 data. New companies are as they reach the $1 billion valuation mark as part of a funding round.听

The unicorn board does not reflect internal company valuations 鈥� such as those set via a 409a process for employee stock options 鈥� 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.听

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

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

Please note that all funding values are given in U.S. dollars unless otherwise noted. 91精品 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 91精品 long after the event was announced, foreign currency transactions are converted at the historic spot price.

Illustration:

When I was a child growing up in Japan, Dragon Ball was 鈥渃ontraband.鈥� My parents were unhappy about me reading manga for hours every day. Teachers confiscated manga magazines at school. But I was fascinated by a universe created from the pure imagination of a single person that went on to shape the aesthetic consciousness of more humans than almost any artist of the twentieth century.

Japan didn’t build Dragon Ball. Akira Toriyama did.

From One Piece, Slam Dunk and Hello Kitty characters to , and , each traces back to a singular, obsessive individual who looked, by Japanese social standards, like a weird outcast.

The country globally perceived as the ultimate collectivist society made its greatest contributions to the world through lone visionaries building what no committee would have approved.

What makes this pattern remarkable is what accumulates underneath it. Each obsessive builder, over decades, pulled behind them layers of precision craft, knowledge and discipline that no bureaucracy could have planned.

Japan’s extraordinary concentration of underleveraged assets, from precision manufacturing expertise, materials science technology, longevity and gastronomical research to a generational cultural content library, is the sediment left by people society once called misfits.

The vault is opening

The global anime market was only 30 years ago and to hit around $88.5 billion by 2033, growing annually at more than 9%. Overseas anime revenue and accounting for 56% of total sales 鈥� confirming that international markets now outweigh Japan’s domestic earnings.

Sources: AJA Industry Reports, Grand View Research, Fortune Business Insights.

has disclosed that more than 50% of its 300 million global members watch anime. Viewership on the platform has tripled over five years, with anime content watched more than 1 billion times in 2024 alone. Naruto, a manga serialization that began in 1999, logged 330 million hours watched on Netflix in the second half of 2024 alone. Out of the top 10 global franchises, five are Japan-originated.

That is critical social infrastructure.

Note: Some other rankings instead have Mario, Harry Potter and/or Sh艒nen Jump, but generally Japan-originated IP accounts for half.

The convergence nobody is pricing

At the same time, there is a louder conversation happening in Japan.

The nation is rearming. Its defense budget has nearly doubled in three years, exceeding for the first time the symbolic 2% of GDP threshold. Under a five-year Defense Buildup Program through 2027, Japan has committed 楼43 trillion (~$275 billion) to defense-related spending.

Globally, VC investment in defense-related startups totaled $7.7 billion in 2025, 91精品 data shows, a record high.

Most observers treat this as a separate story. To me, it is not.

Japan’s manufacturing edge in silicon wafers, photoresists, specialty ceramics, industrial robots, optics and sensors is the same precision culture that made watches accurate to the second and frames hand-painted with obsessive fidelity. The outcast engineers who spent careers perfecting micron-level tolerances for consumer electronics built capabilities that now happen to matter enormously in a world consuming autonomous, high-precision munitions at industrial scale.

The creative and the industrial share the same genealogy: a Japanese individual, largely ignored, building something to an extreme that no one asked for.

This convergence of Japan鈥檚 technological prowess and cultural impact is what makes the country鈥檚 opportunity genuinely unusual. IP that a teenager in Jakarta, Riyadh, Paris or Lagos carries emotionally,听 and precision hardware that only a handful of countries on earth can actually produce, originate from the same national psychology.

One crosses geopolitical lines. The other determines them. Japan鈥檚 soft infrastructure and hard capability are rooted in the same stubborn, misfit tradition.

Manufacturing advantage is learnable. The history of industrial development is a history of production methods moving across geographies, in the past over decades, increasingly over months. Competitors can close the gap.

What is harder to replicate is the cultural depth. A franchise relationship formed in childhood does not transfer by policy or investment. , built by a man who spent years mapping insects on foot and wanted to share that obsession with other children, now lives inside the emotional architecture of an entire global generation.

The window is real, and it will not stay open for long

Wars are hard and exhausting. People do not stop wanting to be moved, amused and alive. If anything, that appetite sharpens during geopolitical turmoil. The world increasingly demands the safety that precision manufacturing enables and the meaning that great storytelling provides.

Japan offers both, not by strategic design, but because its most consequential builders were, for a long time, left alone to be strange.

The assets exist. The global demand is accelerating. What Japan is missing is the cross-border fluency 鈥� legal, cultural and financial 鈥� needed to connect them at the speed the moment requires in the age of AI.

The world is finally ready to pay for what remarkable, overlooked individuals in Japan have quietly been building for decades. The question is whether Japan will be ready to let them and if so, how it can capitalize on its valuable assets quickly enough.

is a seasoned investor, serial entrepreneur and attorney with 25 years of experience bridging law and global business. He currently serves as the inaugural managing director of Japan, where he leads one of the world鈥檚 most active startup accelerator programs. He also serves as a senior adviser at , a U.S. and Canada-based hardtech venture capital firm, and as a venture partner at , an innovation advisory firm. An active angel investor, he has backed more than 50 startups, including several unicorns, and founded , an international angel network connecting investors across Japan, the United States, Europe, Asia and the Middle East. His track record also includes co-founding three venture-backed startups. Previously, Shirato spent a decade at global law firms across New York, Toronto, Abu Dhabi/Dubai, Singapore and Tokyo, and before that, held strategic roles as a management consultant at and as a trade negotiator at . He holds a law degree from the , an MBA from the and , and a bachelor鈥檚 degree in international law and economics from the .

Photo by听听on听

AI infrastructure also added four new unicorn companies focused on data center technology and provisioning. Fintech, including startups in wealth management, payment and digital assets, added four companies, while developer tools and defense each added three.

Twenty of March鈥檚 new unicorns are U.S.-based, including 11 from the San Francisco Bay Area. China added six companies in sectors ranging from robotics to AI and quantum computing.

From Europe, four new March unicorns are U.K.-based, while France, the Netherlands and Belgium each minted one. The UAE, Seychelles, India and Australia also each added one new unicorn to the board.

The most valuable unicorn newcomer last month was Seychelles-based crypto exchange , valued at $25 billion. The largest funding was a $1 billion round raised by AI pioneer 鈥檚 new frontier lab startup, Paris-based .

The board also saw a sizable cohort of very young companies earning their unicorn horns: 18 of the companies that joined the board last month were less than 3 years old. Five were not even a year old.

March鈥檚 new unicorns

AI-centric sectors by far led unicorn creation in March, with 14 of the 36 newcomers hailing from the robotics, foundational AI or AI infrastructure industries:

Robotics

• , a robotics for manufacturing company spun out by , raised a $500 million Series A led by and . The 1-year-old Palo Alto, California-based company was valued at $2 billion.
• Shenzhen-based , an intelligent sensor technology for robotics, raised a $145 million Series B led by , and . The 4-year-old company was valued at $1.5 billion.
• Beijing-based , a humanoid robotics company, raised $145 million in funding. The 2-year-old company was valued at $1.5 billion.
• , a humanoid robotics company for household tasks, raised a $165 million Series B led by . The 2-year-old Mountain View, California-based company was valued at $1.2 billion. The company plans to deploy robots to homes this year.
• Pudong, China-based , an intelligent layer for robotics in manufacturing, raised an $87 million Series D round. The 9-year-old company was valued at $1.2 billion.
• , a provider of simulated data for robotic intelligence, raised a $146 million Series A. The 3-year-old Santa Clara, California-based company was valued at $1 billion.

Foundational AI

• Paris-based raised a $1 billion seed round led by , ,, and . The less than 1-year-old company was founded by LeCun, 鈥檚 former AI lead, and is working to develop models for physical AI. It was valued at $4.5 billion in the round, which is Europe鈥檚 largest seed round on record.
• , a robot foundation model developer trained on internet scale video, raised a $450 million Series A led by . The 2-year-old Palo Alto, California-based company was valued at $1.7 billion.
• , a math foundation model developer for verified AI useful for coding and other applications, raised a $200 million Series A led by . The 1-year-old Palo Alto, California-based company was valued at $1.6 billion.
• Beijing-based , a text-to-video startup with its own AI model, raised a $300 million Series C led by . The 2-year-old company was valued at $1 billion.

AI infrastructure

• , a provider of networking hardware and software for data centers, raised a $500 million Series B led by and . The 2-year-old Santa Clara, California-based company was valued at $4.2 billion.
• , a chip cooling technology, raised a $143 million Series D led by . The 8-year-old San Jose, California-based company was valued at $1.6 billion.
• , which offers GPU rentals for startups, raised a Series A funding led by . The 2-year-old San Francisco-based company was valued at $1.5 billion.
• Redmond, Washington-based , a company building data centers in space, raised a $170 million Series A led by and . The 2-year-old company听 was valued at $1.1 billion.听 It launched its first satellite with a H100 in November 2025.

Financial services

• London-based , an AI-native platform for debt providers including banks, asset managers and advisory firms, raised a $170 million Series C led by . The 9-year-old company was valued at $1.3 billion.
• Mumbai-based , a wealth asset advisory firm for high-net-worth individuals and family offices, raised a $53 million private equity funding led by . The 4-year old, venture-backed asset manager was valued at $1.1 billion.
• Brussels-based , an investment group for digital assets, raised a Series C led by . The 8-year-old company was valued at $1.1 billion.
• Abu Dhabi-based , a payments infrastructure provider for regulated gaming markets, raised a $250 million funding led by . The less than 1-year-old company was valued at $1 billion.

Developer tools

• , which promises to make your app enterprise ready with authentication and other features, raised a $100 million Series C led by and. The 8-year-old San Francisco-based company was valued at $2 billion.
• , an observability platform for agentic AI, raised a $110 million Series B led by . The 3-year-old New York-based company was valued at $1 billion.
• , a software developer for hardware testing and development, raised an $80 million Series B led by . The 3-year-old Austin-based company was valued at $1 billion.

Defense

• , a drone technology company built for defense, raised a $110 million Series B led by . The 7-year-old Huntsville, Alabama-based company was valued at $1.2 billion.
• Sydney-based , provider of advanced navigation beyond GPS for military and industrial capabilities, raised a $112 million Series C led by . The 13-year-old company was valued at $1 billion.
• London-based , a builder of unmanned systems used in the Ukrainian war, raised a $50 million seed听 funding led by and . The 1-year-old company was valued at $1 billion.

Biotechnology

• Austin-based , a biological AI research company spun out of听 , raised a $10 million seed extension. The less than 1-year-old company was valued at $2 billion.
• , a neurotech company focused on brain computer interfaces, raised a $230 million Series C led by and听 Lightspeed Venture Partners. The 5-year-old Alameda, California-based company, whose primary product, an implant to restore vision for those who suffer retinal disease, was valued at $1.5 billion.

Sales and marketing

• Amsterdam-based , a builder of agents for companies to deploy in customer service and business operations, raised a $150 million Series B led by . The 1-year-old company was valued at $2 billion.
• , an agentic layer that monitors customers and researches prospects, raised a Series B led by . The 2-year-old San Francisco-based company was valued at $1.2 billion.

Security

• , native AI security with its own human triage for customers, raised a $250 million Series B led by . The 1-year-old Sarasota, Florida-based company was valued at $1 billion.
• , which uses AI for offensive security, raised a $120 million Series C led by and . The 2-year-old Seattle-based company was valued at $1 billion.

Cryptocurrency

• Seychelles-based , a global cryptocurrency exchange platform, raised a $200 million corporate round led by , the parent company of the . The 12-year-old company was valued at $25 billion.

Telehealth

• Miami-based , ‘s telehealth provider for GLP-1 medications through employers, raised a $200 million Series A led by . The 5-year-old company was valued at $2 billion.

Professional services

• London-based , an AI notetaking startup, raised a $125 million Series C led by . The 3-year-old company was valued at $1.5 billion.

Consumer goods

• , a company with a mattress, thermal blanket and pillow designed to monitor and improve sleep, raised a $50 million Series D led by . The 11-year-old New York-based company was valued at $1.5 billion.

Accelerator

• London-based , an accelerator that sources founders from top schools, raised a $200 million Series D. The 11-year-old company, which hosts its latest cohorts in Silicon Valley, was valued at $1.3 billion.

Quantum computing

• Sichuan, China-based , a quantum computer and chip-production company, raised a $145 million Series B. The 5-year-old company was valued at $1 billion.

Autonomous driving

• Hangzhou-based , an intelligent driving platform, raised a Series A led by , and . The less than 1-year-old company was valued at $1 billion.

Related 91精品 unicorn lists:

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Related reading:

• This Is A Momentous Year For Early-Stage Unicorns
• The Rising Investors Behind The New Unicorn Class
• While OpenAI Shattered Records, Robotics and Semiconductor Startups Quietly Added The Most New Unicorns In February

Methodology

The 91精品 91精品 is a curated list that includes private unicorn companies with post-money valuations of $1 billion or more and is based on 91精品 data. New companies are as they reach the $1 billion valuation mark as part of a funding round.

The unicorn board does not reflect internal company valuations 鈥� such as those set via a 409a process for employee stock options 鈥� 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.

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

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

Please note that all funding values are given in U.S. dollars unless otherwise noted. 91精品 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 91精品 long after the event was announced, foreign currency transactions are converted at the historic spot price.

Illustration: