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

As the AI startup boom progresses, investors appear to be leaving few niches unfunded. That was apparent in this week鈥檚 lineup of large funding rounds, which featured AI infrastructure providers, a foundational model developer, a content protection platform for the AI age, and other AI-focused startups among the top investment recipients.

The biggest investment, $2 billion, went to , a spinout focused on cloud and power infrastructure that is hoping to benefit from the AI buildout. Other large rounds went to , developer of a fast-growing new model, and , a quantum computing startup.

1. , $2B, cloud and power infrastructure: Axiom Solutions International, a private cloud and power infrastructure company spun out of manufacturing services provider , secured $2 billion in new financing. and provided the strategic investment by purchasing shares of Austin-based Axiom from Flex at an initial enterprise value of $37.5 billion. Flex says it plans to separate Axiom into an independent publicly traded company early next year.

2. , $870M, foundational AI: TypeSafe AI, developer of Jev, a recently launched AI model with a large and growing early following, raised $870 million in new funding with as the largest investor, according to a . also participated in the round, which reportedly set a $7.5 billion valuation for San Francisco-based TypeSafe.

3. , $475M, quantum computing: Pasadena, California-based Oratomic, a startup working on fault-tolerant quantum computers, raised $475 million in fresh funding led by , , , , and . The company previously raised $300 million in a July financing.

4. , $400M, data and content protection: SignSplit, a provider of tools for protecting, licensing and contributing real-world human data and other forms of human contribution, emerged from stealth with $400 million in seed funding. backed the round, setting a $1 billion valuation for the New York-based company, which was founded in 2024.

5. (tied) , $250M, AI for engineering: Vinci, developer of an AI computational platform for hardware engineers to design products, closed on $250 million in Series B funding at a $1.5 billion valuation. , and led the round for the Palo Alto, California-based company.

5. (tied) , $250M, micro-manufacturing: Emeryville, California-based Atomic Machines, a startup working on AI-native digital manufacturing systems to build micro-machines directly from code, emerged from stealth and said it has raised $250 million to date from a long list of investors.

7. , $225M, energy distribution: Voltus, provider of a distributed energy platform aimed at bolstering grid flexibility, picked up $225 million in Series D funding. , and led the financing for the San Francisco-based startup.

8. (tied) , $200M, fusion: Knoxville, Tennessee-based Type One Energy, a developer of fusion energy technology, secured $200 million in Series B financing led by and .

8. (tied) , $200M, insurance: Ledgebrook, an AI-powered specialty insurance platform, closed on $200 million in equity financing co-led by and . The round brings total funding to date for Boston-based Ledgebrook to around $315 million, per .

8. (tied) , $200M, AI evaluation: Arena, provider of a platform for evaluating AI models, pulled in $200 million in Series B funding and said it has exceeded a $100 million annual revenue run rate. and led the round, which set a $3.1 billion valuation for the company.

Methodology

We tracked the largest announced rounds in the 萝莉视频 database that were raised by U.S.-based companies for the period of Oct. 3-9, 2026. Although most announced rounds are in the database, there may be a small time lag, as some rounds are reported late in the week.

萝莉视频 AI-focused startups raised $23 billion in the first half of 2026, up 130% year over year and accounting for 55% of the region鈥檚 venture funding, according to a joint 萝莉视频 and HumanX . That investment surge is sharpening a question at the heart of the sovereign AI debate: Where should countries concentrate their resources to capture the technology鈥檚 economic value and retain control over their data?

But sovereignty does not require owning every layer of the AI stack, according to two executives I spoke with onstage at the conference: founder and CEO and , 鈥檚 chief product and technology officer.

Their perspectives from Europe and the United Arab Emirates, respectively, pointed to opportunities in specialized chips and applications and underscored how purchasing decisions, government mandates and access to computing power can determine whether AI ambitions translate into growth.

Five-layered cake

, CEO and president of chip giant , has detailed a 鈥溾�� to deliver AI that includes聽 energy, chips, infrastructure, models and applications.

For Del Maffeo, whose company develops chips for inference, the opportunity lies in the semiconductor layer, as more AI processing moves beyond centralized data centers and onto devices.

鈥淎rtificial intelligence will expand from cloud computing, from centralized data centers, to devices closer to us in the physical world,鈥� he said. 鈥淭o enable this, you need specific chips which can run efficiently, at a lower cost, to connect these networks that today are running in the cloud. We are here to solve this problem.鈥�

Five-year-old Axelera AI has two generations of chips it sells to around 600 customers. The company next plans to expand to products for decentralized cloud computing.

AI transformation

Abu Dhabi-based AI71 partners with large organizations and government agencies to help them benefit from AI transformations.

The United Arab Emirates has the largest compute per capita in the world and has a three-month mandate for every government agency to set up agentic processes for its citizens, according to Ghissassi. Energy is abundant and cheap. Over the next two years, the goal is to reach half of every citizen鈥檚 interactions with the government with an AI agent, he said.

Competing at the model layer does not make sense, said Ghissassi. He believes there will be two, three or four companies that can afford to be in the race, given the amount of capital required and the fact that it commoditizes very quickly.

The application layer is the one that is really important, for sovereignty where you want to own your data, said Ghissassi, who previously led product development at . 鈥淵ou want to make sure that it stays with you, be it that you鈥檙e a government or an enterprise. If you鈥檙e giving away your trade secrets and know-how, nobody stops whoever is being a provider to you today, from replacing you.鈥�

In the UAE, 鈥渨hat helps is the mandate, the pace at which things happen, the availability of compute, both in terms of sovereign clouds, or on-prem, or global clouds, and then the amount of capital that is being invested to help transform these companies to benefit from these technologies,鈥� Ghissassi said.

By contrast, Europe struggles as it is a net importer of energy. It has strengths in the semiconductor industry but lacks all the real compute for AI, in neural networks and frontier labs.

鈥淲e should not be obsessed with controlling the entire stack,鈥� said Del Maffeo. In Europe we have to create value instead of just paying for a service, he added. 鈥�Creating value means creating a wealthy economy.鈥�

Europe鈥檚 strengths include its large pools of research talent and its population of 440 million people who can benefit from AI. However, the culture of large businesses purchasing from startups is less established, meaning it doesn鈥檛 have the same flywheel for growth seen in the U.S., said Del Maffeo.

鈥淲hat worries me is that we are a little bit lagging behind, and therefore we are missing this value creation, and this will weaken the economies of Europe,鈥� he said.

Related 萝莉视频 query:

Related reading:

• Europe Posted Its Strongest Venture Funding Quarter In 4 Years As UK Gains, M&A Holds Up

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She later became a general partner at , where she led early institutional investments in AI chipmaker , and later invested at . Now she鈥檚 founder and managing partner of , a $52 million fund backing startups that use AI to do work in industries such as construction, industrials and insurance.

In an interview with 萝莉视频 News, Venkatachalam discusses why she looks beyond familiar founder profiles, what makes an AI company durable, and how an early investment in Groq shaped her approach.

This interview has been edited for clarity and brevity.

You invested at Khosla Ventures before starting Axiom. What did you take from that experience, and what did you want to do differently?

Venkatachalam: One thing I took was 鈥檚 open view of where great founders can come from. Silicon Valley has gravitated toward a fairly narrow idea of who can build the next great AI company: Someone with a computer science or machine learning background, or experience at . We鈥檙e looking for more nonobvious founders, particularly in nonobvious industries.

The other thing was how we think about risk. Instead of asking a company every conceivable diligence question, we focus on the risks that matter for its next set of milestones. Can this team do what it says it will do? And if it can, could the result be massive?

That means accepting that many bets won鈥檛 work out while aiming for the outliers. I think that鈥檚 what my investors are backing me to do: identify categories of the future, rather than participate in the categories everyone already recognizes.

At Axiom, the biggest difference is that we鈥檝e built the firm around people who are actively working with AI. If you aren鈥檛 building, productizing, pricing or taking AI to market regularly, it鈥檚 very hard to keep up. Our team includes people doing exactly that in their other roles. They help keep our investment thinking current, and founders want to work with them because they鈥檝e encountered many of the same challenges.

We also use AI throughout the firm. We鈥檝e built what we call the Axiom Brain to help us make sense of market trends, identify interesting people and companies, and move faster on diligence and other work. For me, the value is the ability to act quickly.

You mentioned that some of those AI practitioners have other jobs. How does their role at Axiom work?

Venkatachalam: They have dedicated time to Axiom and work with us part time. They also receive carry in the fund. They鈥檙e partners in the work, rather than people whose names appear on an adviser list.

Their other jobs are central to the model. Some of the best angel investors are people who are still operating and building. I don鈥檛 need these people full time. In fact, they would be less valuable to Axiom if they left the work that keeps them close to the market.

Axiom says it invests in 鈥淎I for the real world.鈥� What does that mean when you鈥檙e evaluating a startup?

Venkatachalam: Our view is that AI should benefit a much broader population than the early adopters who are already using it. We look at industries underserved by technology, where AI can produce an outcome rather than simply provide another software tool.

That may lead us to construction, industrials or insurance. Some of those companies involve hardware, sensors or robotics; others are entirely software-based. What connects them is that they鈥檙e doing work that matters to customers in real-world industries.

We generally don鈥檛 invest in products that look like conventional enterprise software tools. We want to see AI delivering a result.

You鈥檝e described a shift from software people use to digital workers that perform jobs. Are customers actually paying for AI from labor budgets?

Venkatachalam: Yes, and that鈥檚 one of our investment criteria. Even when a portfolio company is at an alpha or design-partner stage, we do diligence to understand whether customers are willing to buy it that way. We鈥檙e often seeing contract values in the hundreds of thousands of dollars, rather than the much smaller contracts you might expect for a midmarket software tool.

We鈥檝e seen that buying behavior play out across the majority of the portfolio companies we鈥檝e invested in.

AI products are becoming faster to build and easier to imitate. What makes one durable enough to become a large company?

Venkatachalam: If you鈥檙e doing important work inside a customer鈥檚 business, and that work is worth a lot of money, you become difficult to replace. You鈥檙e handling what we call the last mile of the job.

In industrial settings, for example, delivering an outcome means integrating deeply with the systems customers use. You have to understand their data, train on it, learn the workflows that matter, and stand behind the result. That takes more than putting an interface on top of a model.

Those relationships and capabilities can become difficult for another startup to replicate. They also involve work that the large AI model companies may have little interest in doing themselves.

Before Axiom, you backed Groq when AI inference was far from an obvious investment category. What led you to it?

Venkatachalam: I came from both hardware and software. At one point, I became interested in why was building its own networking switches when it could buy them from existing suppliers. As I looked into that, I learned it was building its own chips, too.

That led me to , who had been involved in that work and had left to start Groq. I began learning why large technology companies were building chips to train models. Then Jonathan made the case that the much larger future market would be inference.

I鈥檒l be honest: In 2016, I barely understood inference. But if you believed these models would spread, it made sense that people would build on top of them and need the infrastructure to support that. That insight drove my investment.

How did that experience shape what you look for now?

Venkatachalam: It taught me the value of being a little early and having some patience. You don鈥檛 have to be wildly contrarian, but you do have to see the opportunity before it becomes obvious to everyone else.

In a way, our thesis hasn鈥檛 changed. We鈥檙e still asking what will be built on top of AI infrastructure and models. We want to invest while the answer is emerging, before there鈥檚 a consensus.

What happens when one of those early bets doesn鈥檛 work out?

Venkatachalam: We plan for it. We have a $52 million fund and expect to make 35 investments. We fully expect about half of them to fail, whether that means a company shuts down or simply never reaches the growth trajectory we鈥檙e looking for.

The model depends on finding an exceptional outcome. We need one outstanding investment to return the fund. If you invest early enough and the company becomes very large, that can offset many bets that didn鈥檛 work.

That willingness to accept losses is part of making investments before an opportunity is obvious. It鈥檚 built into how we approach the fund.

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led the round, with participation from co-leads Scaleup Europe Fund, managed by , and existing investor .

The financing comes nearly one year to the day after Mistral鈥檚 $2 billion Series C, which valued the company at $13.7 billion. Mistral has now raised $7.5 billion since its 2023 inception.

Mistral鈥檚 new raise means it retains its spot as the most highly valued foundation model company out of Europe. There are currently seven private frontier labs valued above $20 billion on The 萝莉视频 Unicorn board 鈥� eight including China鈥檚 , which is also building its own model 鈥� though the rest are all based in the U.S. and China.

In a statement, the company says the new capital will 鈥渟ignificantly expand Mistral’s frontier research鈥� and help it 鈥渆xpand infrastructure and accelerate鈥� its commercial growth and international footprint. Mistral currently operates across 20 countries and counts more than 125 global enterprises as customers, including , , and .

Mistral builds AI models for tasks such as generating text, writing code and analyzing documents, putting it in competition with U.S. companies including , and .

However, unlike many of its U.S. rivals, Mistral touts greater control for businesses by offering models they can customize and run on their own systems rather than relying entirely on a third-party cloud provider.

Europe鈥檚 VC momentum

This year has marked a turning point for 萝莉视频 venture funding. In Q2, Europe posted its strongest quarter in four years for venture funding, 萝莉视频 data shows. All told, Europe-based startups raised $24 billion in the quarter, up around a third quarter over quarter and two-thirds higher than the $14.4 billion raised in Q2 2025.

At the time of Mistral鈥檚 $2 billion Series C, that raise represented the largest venture round ever raised by a 萝莉视频 AI company.

This latest round has now eclipsed that, and several other large AI-related deals in Europe have also closed this year. They include London-based Google spinoff , which raised a $2.1 billion Series B in May led by and AI data center provider , which raised a $2 billion Series C at a $14.6 billion valuation in March co-led by and . (It has also since raised several billion in debt financing, per 萝莉视频.)

Related 萝莉视频 queries:

Related reading:

• Europe Posted Its Strongest Venture Funding Quarter In 4 Years As UK Gains, M&A Holds Up
• Mistral鈥檚 $2B Series C Is Europe鈥檚 Largest AI Round By A Lot

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Looking broader into the entire market, I can see how this makes a lot of sense. Companies are becoming increasingly uneasy about where critical infrastructure and sensitive data live. AI fraud is getting better. Voice cloning is becoming more convincing. Vibe coding is allowing less experienced developers to build faster, but not always more securely. Quantum computing is still over the horizon, but serious companies are already thinking about what it may mean for encryption and long-term data protection.

For the past decade, cloud migration was treated as the obvious strategy. It gave companies speed, scale and lower upfront costs. Startups could launch without buying servers. Enterprises could modernize without rebuilding their own infrastructure.

That logic still holds. But we are witnessing an interesting shift where progress is happening so fast, security cannot keep up, thus creating an uneasy feeling causing decision-makers to revert back to older, and perhaps safer perceived strategies.

Here are three trends that I believe are pushing on-prem back into the limelight.

AI fraud is changing the security conversation

In many cases, cloud providers are more secure than what a company could build internally. The issue is that thanks to AI, attackers are becoming more sophisticated, and quick. AI makes phishing more polished, fake invoices more believable, and voice impersonation harder to detect. A call that sounds like the CFO or CEO asking for a payment approval is no longer far-fetched.

That changes how companies think about exposure. The attack surface is not only servers. It is identity systems, SaaS tools, APIs, employee workflows, permissions, contractors and support portals.

For sensitive systems such as communications, payments, identity and customer data, control becomes more valuable. On-prem does not guarantee security. But it can reduce dependency on outside platforms and give companies clearer ownership over the systems they cannot afford to compromise.

Enterprise AI may favor private infrastructure

Cloud AI APIs are excellent for testing. A company can launch a pilot quickly without buying GPUs, managing models, or hiring a large infrastructure team.

But enterprise AI is moving into production. That changes both the economics and the risk.

The most useful enterprise AI applications require proprietary data: contracts, source code, customer records, financial reports, support tickets, security logs, medical files and internal communications. This is the data that gives AI business value. It is also the data companies are most careful with.

For these use cases, on-prem or private AI infrastructure becomes more attractive. The model can run closer to the data. Access can be controlled more tightly. Retention, compliance and audit requirements become easier to manage.

There is also a cost angle. Token pricing is convenient in a pilot, but expensive at scale. When thousands of employees or customers use AI every day, paying per query can become a serious recurring cost. For stable, high-volume workloads, owning or controlling the infrastructure may be cheaper than renting every interaction forever.

Quantum risk is making long-term data protection more strategic

Quantum computing is not breaking enterprise encryption today. But the risk is already part of serious security planning.

The concern is that the minute quantum becomes commercial, all encrypted data sitting in the cloud will be transparent. No existing encryption will hold against a quantum computer. That matters most for companies holding long-life sensitive data: banks, healthcare providers, telecom companies, governments, defense-related organizations and infrastructure providers.

Regardless of whether or not on-prem is the best solution for all this, it is perceived as such. Hence, I believe it will drive higher demand for the legacy on-prem strategy. This early shift is also an opportunity, but that鈥檚 for another article.

is a strategic adviser to tech companies, investors, CEOs and boards, specializing in strategy, growth and M&A. He is a guest contributor to 萝莉视频 News and a university lecturer on strategy, finance and entrepreneurship. Learn more at and connect with him on .听

Photo by on .

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

Big fundraising deals did not take a pause for summer this week. In the U.S., the largest financings went to enterprise software company and blockchain technology provider . The largest deals of the week, however, were for 萝莉视频 companies, with Germany鈥檚 pulling in $1.4 billion and Finnish space tech company landing $520 million.

1. , $400M, enterprise software: NinjaOne, provider of an IT operations and endpoint management platform, raised over $400 million in Series C extension funding at a $12.3 billion valuation. The Austin-based company said it grew revenue over 70% in 2025 and posted a profit in the first quarter of this year.

2. , $355M, blockchain technology: Digital Asset, a provider of blockchain technology geared for financial institutions, secured $355 million in a later-stage financing led by 鈥檚 crypto fund, . Founded in 2014, the New York-based company has raised at least $847 million in known funding to date, per .

3. , $350M, AI cloud infrastructure: Las Vegas-based TensorWave, an AMD AI cloud technology provider for training and inference workloads, closed on $350 million in Series B funding. and led the financing.

4. , $300M, biotech: Beren Therapeutics, a developer of therapeutics for conditions characterized by defective cholesterol trafficking, raised $300 million in equity and debt funding. The financing for the Thousand Oaks, California-based company includes $165 million in debt funding from as well as $135 million in equity investment.

5. , $200M, robotics: Standard Bots, a manufacturer of AI-native industrial robots, picked up $200 million in Series C funding. and were lead investors in the round, which set a $1 billion valuation for the New York-based company.

6. , $125M, genetic medicines: SonoThera, developer of an ultrasound-mediated genetic medicine platform, secured $125 million in Series B funding. led the financing for the San Francisco-based company.

7. (tied) , $100M, medical devices: Tempe, Arizona-based GT Medical Technologies, developer of a form of radiation therapy called GammaTile that is used at the time of brain tumor removal surgery, picked up $100 million in Series E funding led by .

7. (tied) (aka Genspark), $100M, agentic AI: MainFunc, the company behind Genspark, a developer of agentic AI tools for the workplace, reportedly $100 million in Series B extension funding at a $2.6 billion valuation. Investors reportedly included , and South Korea’s .

9. , $99.5M, biotech: Cambridge, Massachusetts-based City Therapeutics, a developer of RNA interference (RNAi)-based medicines, closed on $99.5 million in Series B funding from backers including new investors and .

10. , $85M, tools for the deaf and hearing-impaired: Rylo, developer of an app for hearing-impaired people, raised $85 million in growth funding from , and existing investors.

Outside the US

, $1.4B, robotics: Germany鈥檚 Neura Robotics, a developer of AI infrastructure for robots to learn, collaborate and operate across real-world environments, says it secured up to $1.4 billion in Series C funding.

, $520M, space tech: Helsinki-based Iceye, operator of a satellite constellation for monitoring conditions on Earth, raised $520 million in a Series F funding round led by , at a valuation of over $12 billion.

Methodology

We tracked the largest announced rounds in the 萝莉视频 database that were raised by U.S.-based companies for the period of June 6-12. 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.

Illustration:

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

Startup investors kept up the busy dealmaking pace this week with a number of big rounds. Top among them was a $1.75 billion Series D for , developer of autonomous vessels. Other big funding recipients hailed from sectors including fitness wearables, energy tech, cybersecurity and AI infrastructure, among others.

1. , $1.75B, autonomous ships: Austin-based Saronic, a defense tech startup focused on autonomous sea vessels, raised $1.75 billion in Series D funding, bringing total funding to around $2.6 billion. led the round, which set a $9.25 billion valuation for the聽 company, more than double its Series C level in 2025.

2. , $575M, fitness wearables: Whoop, a provider of wearable fitness technology and a subscription platform that tracks physiological data, secured $575 million in Series G funding. led the financing,which set a $10.1 billion valuation for the Boston-based company.

3. , $450M, nuclear energy: El Segundo, California-based nuclear energy startup Valar Atomics, raised fresh capital at a valuation of $2 billion, according to a citing unnamed sources. The financing reportedly included $340 million in equity funding and $110 million in debt.

4. , $300M, battery technology: EnerVenue, a developer of grid-scale energy storage technology, says it closed on a $300 million extension of its Series B preferred round led by . The Fremont, California-based company also appointed a new chief executive officer, Henning Rath.

5. , $250M, cybersecurity: Sarasota, Florida-based AI-enabled cybersecurity startup Tenex picked up $250 million in Series B funding led by . The company said it plans to use the funds to hire more than 250 people and supplying them with AI technology that makes them 鈥渢en times more efficient.鈥�

6. , $200M, micromobility: Also, an electric mobility company spun out of , raised $200 million in a Series C round 鈥媌acked by , , and . The Palo Alto, California-based startup鈥檚 product lineup includes bikes, small autonomous EVs for deliveries, and associated gear.

7. , $170M, space tech: Starcloud, a space infrastructure startup focused on building orbital data centers, secured $170 million in Series A funding led by and . The financing sets a $1.1 billion valuation for the Redmond, Washington-based company, making it the fastest alum to achieve unicorn status after demo day, which was 17 months ago.

8. , $130M, cloud infrastructure: New York-based cloud and AI infrastructure startup ScaleOps landed $130 million in Series C funding. led the financing, which set聽 a valuation of over $800 million for the 4-year-old company.

9. , $100M, biotech: Boulder, Colorado-based Ambrosia Biosciences, a developer of next-generation oral therapeutics for obesity and related cardiometabolic diseases, picked up $100 million in Series B funding led by , and .

10. , $94M, money transfer: OpenFX, provider of a platform to move money across borders, secured $94 million in Series A funding from backers including , , , and .

Methodology

We tracked the largest announced rounds in the 萝莉视频 database that were raised by U.S.-based companies for the period of March 28-April 3. 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.

Illustration:

A total of 27 companies joined the 萝莉视频 last month, including six robotics companies and four semiconductor-related startups. Healthcare minted three new unicorns, while foundation AI, cloud services, aerospace and financial services each accounted for two companies that joined.

The U.S. once again dominated, with 19 companies joining the board. China tallied four new unicorns, the U.K. contributed two, and India and Germany each added one new unicorn.

Soaring valuations

Overall unicorn values soared in February as raised $110 billion at a value of $840 billion, making it the most highly valued private company of all time. Its closest rival, , raised $30 billion at a valuation of $380 billion, making it the fourth-largest valued company on the list. , the autonomous driving technology company, was valued at $126 billion, positioning it among the top 10 most highly valued private companies.

February鈥檚 new unicorns

Here are February鈥檚 newly minted unicorns.

Robotics

• , a solution for automating building equipment for autonomous construction, raised a $270 million Series B led by and . The 1-year-old company, based in San Francisco, was valued at $1.8 billion.
• Beijing-based , a physical intelligence foundation model and humanoid robotics company, raised a $290 million Series A led by and . The 2-year-old company was valued at $1.5 billion.
• , a builder of intelligent robots for industrial and service industries, raised a $145 million Series B round. The 2-year-old Beijing-based company was valued at $1.4 billion.
• Humanoid robotics company raised a $145 million Series B led by . The 2-year-old China-based company was valued at $1.4 billion.
• , a testing and control software layer for aerospace, defense, robotics and industry, raised a $150 million Series B led by . The 1-year-old Los Angeles-based company was valued at $1 billion.
• , a company that transforms 5G and Wi-Fi into spatial awareness for connective devices, an underlying layer necessary for physical AI, raised a $100 million Series B from well-known investors , , , and . The 9-year-old Belmont, California-based company was valued at $1 billion.

Semiconductor

• China-based , developer of a chip for advanced autonomous driving, raised a $330 million Series A led by and . The company, which is less than a year old and spun out of automaker , was valued at $1.5 billion.
• London-based , a photonic chip company for more efficient AI inference, raised a $220 million Series A led by . The 2-year-old company, valued at $1 billion, has plans to ship its first product in 2027.
• Reno, Nevada-based , builder of memory chips for AI, raised a $230 million Series B led by , and . The 3-year-old company was valued at $1 billion.
• , a chip developer for AI training, raised a $500 million Series B led by and . The 3-year-old company, based in Mountain View, California, was valued at $1 billion. It plans to ship its first product in 2027.

Healthcare

• New York-based , a platform that helps employers and employees source the best doctors with improved costs, raised a $118 million Series D led by . The 7-year-old company was valued at $1.4 billion.
• Palo Alto, California-based , a women’s telehealth provider, raised a $100 million Series D led by . The 4-year-old company was valued at $1 billion.
• , a Redwood City, California-based digital platform that helps medicare customers connect with advocates to navigate healthcare, raised a $130 million Series C led by . The 4-year-old company was valued at $1 billion.

Cloud services

• , a cloud platform for application development teams, raised a $100 million Series C led by . The 8-year-old San Francisco-based company was valued at $1.5 billion.
• Mumbai-based , a cloud service GPU provider, raised a $600 million round led by . The 3-year-old company was valued at $1.4 billion.

Foundational AI

• , builder of an AI model to analyze large databases, raised a $225 million Series A led by . The company also says it has signed a partnership agreement with ‘s to offer the model to its customers. The 2-year-old, San Francisco-based company was valued at $1.4 billion.
• , a model developer to debug and understand AI, raised a $150 million Series B led by . The 1-year-old San Francisco-based company was valued at $1.3 billion.

Aerospace

• , a space-based communications infrastructure player to support commercial satellite and government missions, raised a $100 million Series B led by and. The 4-year-old Livermore, California-based company was valued at $1.3 billion.
• , an aviation hardware and software company for automated flights, raised a $300 million Series C led by and . The 10-year-old El Segundo, California-based company was valued at $1.2 billion.

Financial services

• London-based , a U.K.-based digital bank for small and medium-sized businesses, raised a $155 million Series D led by , and . The 8-year-old company was valued at $1.2 billion.
• , an agentic platform for accountants, raised a $100 million Series B led by , and . The 3-year-old company, based in New York, was valued at $1.2 billion.

E-commerce

• Brooklyn-based , a marketplace for creators to sell digital products, raised a $200 million round led by . The 5-year-old company was valued at $1.6 billion.

Coding

• , a Boston-based code translation service for legacy code, raised a $125 million Series B led by 1. The round valued the 2-year-old company at $1.3 billion.

Defense

• Berlin-based , a developer of strike drones and autonomous defense systems, raised an undisclosed sum in a round led by that valued the 1-year-old company at $1.2 billion.

Forecasting

• Boston-based , an AI-native weather satellite constellation, raised a $175 million Series F led by and . The 9-year-old company was valued at $1 billion.

Sales & marketing

• New York-based , a brand marketing platform geared for AI search, raised a $96 million Series C led by that valued the 1-year-old company at $1 billion.

Web3

• , a blockchain intelligence platform to detect crime networks, raised a $70 million Series C led by . The raise valued the 8-year-old company, based in San Francisco, at $1 billion.

Related 萝莉视频 unicorn lists:

• (1,703)
• (604)
• (65)
• (187)
• (115)
• (102)
• (878)
• (500)
• (228)
• (38)
• (471)

Related reading:

• Massive AI Deals Drive $189B Startup Funding Record In February While Public Software Stocks Reel
• 萝莉视频 Data: The AI Boom Has Drastically Changed Who鈥檚 Funding The Hottest Companies In 2025 Vs. 2021
• January Delivers Highest New Unicorn Count In More Than 3 Years

Methodology

The 萝莉视频 萝莉视频 is a curated list that includes private unicorn companies with post-money valuations of $1 billion or more and is based on 萝莉视频 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. 萝莉视频 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 萝莉视频 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鈥檚 top 10 announced funding rounds in the U.S. Check out last week鈥檚 biggest funding deal roundup here.

This week鈥檚 largest U.S. funding rounds once again featured an AI-heavy cohort, along with sizable financings around fintech and energy tech. By far the largest deal was a $1 billion financing for , developer of AI models that interact with the 3D world, followed by a $385 million round for savings platform .

1. , $1B, spatial AI: San Francisco-based World Labs, a startup founded by AI pioneer that develops foundational models to generate and interact with the 3D world, raised $1 billion in fresh funding. Investors in the round include , , , , and .

2. , $385M, fintech: Vestwell, an online provider of multiple types of savings accounts and tools, raised $385 million in Series E funding at a reported $2 billion valuation. and led the financing for the 10-year-old, New York-based company.

3. , $300M, workflow management and fault tolerance: Bellevue, Washington-based Temporal Technologies, a provider of tools that allow developers to make workflows more reliable and fault-tolerant, closed on $300 million in Series D funding. led the financing, which set a $5 billion valuation for the 7-year-old company.

4. , $140M, energy tech: Heron Power, a developer of hardware designed to move electricity from renewable sources into the grid and data centers, picked up $140 million in a funding round backed by and . The Scotts Valley, California-based company is founded by former SVP .

5. , $125M, AI coding: Code Metal, a provider of verifiable code translation tools, raised $125 million in Series B financing led by 1. The round comes just three months after the Boston-based startup secured its Series A.

6. (tied) , $100M, cloud for developers: Render, a cloud provider for application development teams, secured $100 million in Series C extension funding. led the financing for the San Francisco-based company, which said it now has over 4.5 million developers on its platform.

6. (tied) , $100M, clean energy: Houston-based Utility Global, developer of a technology to produce hydrogen and capturable carbon from industrial gases, raised $100 million in Series D funding. and led the financing for the 8-year-old company.

6. (tied) , $100M, location tracking: ZaiNar, developer of a technology for wireless networks to sense the location of things without satellites, cameras or heavy compute power, emerged from stealth and disclosed that it has drawn over $100 million in investment to date and a valuation of over $1 billion. Backers in the Belmont, California-based company include , , and .

9. , $80M, fintech: Salt Lake City-based Jump, developer of an AI agent for financial advisers and financial services providers, raised $80 million in a Series B round led by .

10. , $80M, AI observability: San Francisco-based Braintrust, a developer of AI observability software for development teams, raised $80 million in a Series B round led by .

Methodology

We tracked the largest announced rounds in the 萝莉视频 database that were raised by U.S.-based companies for the period of Feb. 14-20. 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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While Europe鈥檚 venture investment did not grow significantly year over year, the region saw a shift to deep tech funding in 2025. Startup investment has also now maintained well above pre-COVID levels for the past three years.

Still, Europe notably has not seen the same AI-driven boost that North America has. Venture investment in North America-based companies last year soared 46% year over year, with mega rounds into AI-related companies leading the way.

Table of contents

• Quarterly uptick
• AI led for the first time
• UK leads but other countries gain
• Late stage grew in Q4
• Leading investors
• Above pre-COVID funding
• Methodology
• Glossary of funding terms

Quarterly uptick

萝莉视频 venture funding did gain steam in Q4, reaching $16.6 billion 鈥� up 20% quarter over quarter and 27% year over year 鈥� per 萝莉视频 data.

The largest rounds in Q4 were raised by London-based energy software provider , Finland-based smart ring , Paris-based customer engagement platform , Dutch online grocer , and London cloud GPU provider .

AI led for the first time

Last year, artificial intelligence was the leading sector for venture investment in Europe for the first time, with around $17.5 billion in funding to AI in 2025 compared to just over $10 billion in 2024.

Paris-based frontier lab raised the largest round in the year, close to $2 billion led by Dutch chip machine manufacturer . Other large 萝莉视频 funding rounds raised last year in AI went to Nscale and Brevo as well as Munich-based defense manufacturer , London-based AI drug discovery , and Freiburg, Germany-based image frontier lab .

The second-largest sector in Europe in 2025 for startup investment was healthcare and biotech, with companies in the space raising around $13.4 billion.

The third-largest sector was hardware with around $10.8 billion invested. The total demonstrates Europe鈥檚 renewed focus on deep tech including investment in data centers, wearables, defense, quantum, aerospace, robotics and energy.

Financial services, once the leading sector in Europe鈥檚 venture scene, was only the fourth-largest sector for funding in 2025, with around $7.4 billion invested.

UK leads but other countries gain

The U.K., the leading country in Europe, raised around $17 billion. That represents about 29% of total 萝莉视频 venture funding in 2025, down from a third of all funding in 2024.

Startups based in France raised $8.5 billion and Germany-based companies came in a close third with $8.4 billion. Each nation鈥檚 startups represented about 15% of funding to the continent last year.

Switzerland was the fourth-largest 萝莉视频 country for venture investment in 2025, with $3.6 billion invested in its startups last year. The Netherlands was the fifth largest at $3.4 billion, and was followed by Spain ($2.9 billion) and Finland ($2.2 billion).

With the exception of the U.K., each of those countries raised more venture funding in 2025 than in 2024.

Late stage grew in Q4

Late-stage funding in Q4 reached the highest amount in two years. A total of $9.2 billion was invested across 87 deals, up 65% by amounts year over year.

Early-stage funding reached $5.3 billion in Q4 across more than 250 funding rounds, down 4% year over year.

Seed funding reached $2 billion in Q4 across more than 750 deals, inline with totals year over year.

Leading investors

Investors that led or co-led the largest fundings into the region鈥檚 startups last year were dominated by Europe-based venture and private equity firms. Firms that led or co-led from outside of Europe included a mix of venture or private equity firms from the U.S. or Asia.

Above pre-COVID funding

Funding in Europe did not grow significantly year over year in 2025, but was well above pre-COVID funding levels and growing in deep tech and AI. With a renewed focus on science, funding has also shifted toward cities across Europe with leading research institutes.

Methodology

The data contained in this report comes directly from 萝莉视频, and is based on reported data. Data is as of Jan. 4, 2026.

Note that data lags are most pronounced at the earliest stages of venture activity, with seed funding amounts increasing significantly after the end of a quarter/year.

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

Glossary of funding terms

Seed and angel consists of seed, pre-seed and angel rounds. 萝莉视频 also includes venture rounds of unknown series, equity crowdfunding and convertible notes at $3 million (USD or as-converted USD equivalent) or less.

Early-stage consists of Series A and Series B rounds, as well as other round types. 萝莉视频 includes venture rounds of unknown series, corporate venture and other rounds above $3 million, and those less than or equal to $15 million.

Late-stage consists of Series C, Series D, Series E and later-lettered venture rounds following the 鈥淪eries [Letter]鈥� naming convention. Also included are venture rounds of unknown series, corporate venture and other rounds above $15 million. Corporate rounds are only included if a company has raised an equity funding at seed through a venture series funding round.

Technology growth is a private-equity round raised by a company that has previously raised a 鈥渧enture鈥� round. (So basically, any round from the previously defined stages.)

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