Twenty-one of last month���s new unicorns are U.S. headquartered. Six new unicorns joined the board from China and three from the U.K., while Canada, Saudi Arabia, Japan, Israel, Italy, Finland, Germany and Bulgaria each added one new unicorn.

Through September, 311 companies have joined the board so far this year, putting 2026 on track to be the second-highest year for new unicorn creation, following only the venture peak year of 2021, when counts topped 600.

Several companies already on the board stand out for significant valuation increases via new raises last month. They include San Francisco-based , developer of AI for software engineering, which saw its value climb to $48 billion, up from $26 billion only four months earlier. Data center provider was valued at $31 billion last month, up from $10 billion a year ago. And Paris-based frontier lab was valued at $24.4 billion in its more recent funding, up from $13.7 billion a year ago.

New unicorns in September

Here are September���s 38 new unicorn companies:

Semiconductors

• , an Austin-based semiconductor manufacturing startup, closed a $500 million Series A at a $3.7 billion valuation, led by . The 3-year-old company builds compact chip factories and develops their manufacturing equipment internally, aiming to make semiconductor production more accessible.
• , an Irvine, California-based semiconductor company, raised a $275 million Series C, valuing it above $3 billion and bringing total funding to $415 million. , and led the round. The 2-year-old company develops digital signal processing chips for high-speed optical connectivity in AI infrastructure.
• , a Hangzhou-based AI chip developer, announced a $149 million Series C. Its IoT inference chips combine memory and computing to reduce power consumption and data movement. The 5-year-old company was valued at $1 billion.
• , a Beijing-based AI chip company, raised $298 million at a valuation of $2.2 billion. The 4-year-old company develops AI computing chips using the open RISC-V architecture.

• , a San Jose, California-based developer of specialized AI chips and software, raised a $150 million Series C at a $1.45 billion valuation, co-led by and , bringing total funding to $500 million. The proceeds for the 8-year-old company will support its software platform and next-generation hardware for robots, vehicles and drones.

Financial services

• , a Texas-based prediction-market platform, announced a strategic partnership with , which will take an equity stake following OG���s separation from . The less than 1-year-old company was valued at $5 billion. The investment amount was not disclosed; the partnership will route Robinhood event-contract trading through OG���s regulated exchange and clearing infrastructure.
• Saudi Arabia-based , a digital payments company, raised a $329.5 million Series A at a $1.85 billion valuation. Investors included , and . The 3-year-old company has processed more than $117 billion in 2 years.
• , a Nevada-based financial software company, raised a $250 million Series E at a $1.43 billion valuation led by founder and chairman . The 8-year-old company provides an AI-based investment management platform for asset and wealth managers.
• , a Miami-based remittance platform for Latino immigrants operating through , secured $200 million in financing: an $87 million Series C equity round led by valued at $1.4 billion and $113 million in debt from ���s Customer Value Fund. The 5-year-old company plans to expand to lending and add to its Latin American reach.

Space technology

• Munich-based space company raised a $450 million Series C, co-led by , and at a valuation of $2 billion. The financing for the 5-year-old company will advance its reusable Nyx spacecraft for an International Space Station mission and support development of its Storm rocket engine.
• , a Seattle-based satellite connectivity company, raised a $200 million Series C at a $1.6 billion valuation, led by , bringing total funding to approximately $300 million. The 5-year-old company enables standard Bluetooth devices to connect directly to satellites for tracking and sensor-data applications.
• Oxfordshire, U.K-based , a satellite company, secured $346 million, co-led by and, valued at $1 billion. The 11-year-old company manufactures satellites and provides infrastructure, connectivity, Earth observation and intelligence services.
• Bulgaria-based , a satellite company, raised $205 million in a round co-led by and , reaching a $1 billion valuation. The 11-year-old company has raised financing that will expand standardized spacecraft production, including new manufacturing capacity in the U.S. and Europe.

Biotechnology and medical devices

• , a Framingham, Massachusetts-based developer of treatments for Alzheimer���s disease and other neurodegenerative disorders, raised around $79 million. The 泭 13-year-old company was valued at $1.9 billion. Investors were not disclosed.
• Shanghai-based , an AI drug discovery company, raised $290 million at a $1.5 billion valuation following its spinoff from . , , and co-led the round. Anew develops tools for biomolecular prediction and drug discovery; ByteDance retained a 56% stake.
• , a New York-based brain-computer interface developer, closed a $250 million Series D, bringing total funding to $430 million and reaching a valuation of approximately $1 billion. and led the round. The 5-year-old company is building a brain���computer interface that is minimally invasive and removable.
• Toronto-based , a biotechnology company, raised $153 million at a $1 billion valuation led by the , with participation from and other investors. The 3-year-old company uses AI to identify abandoned drug candidates that could succeed under different treatment approaches. The financing will expand clinical development and support additional drug acquisitions.

AI and internet infrastructure

• , a San Francisco-based AI cloud infrastructure company, raised a $300 million Series B at a $3 billion valuation, led by . The 3-year-old company distributes AI inference workloads across different types of chips to improve performance and efficiency. It announced in March that its customers include one of the leading frontier labs.
• Helsinki-based , an AI cloud company, raised a $189 million Series B led by . The financing valued the 6-year-old company above $1 billion with total funding over $450 million. The company manages physical data centers along with its cloud platform.
• London-based , an internet infrastructure company supporting content delivery for large streaming, gaming and software companies, raised $570 million in its first external financing led by . The 15-year-old company was valued at $1.9 billion.

AI training

• , a San Francisco-based AI training-data company, raised more than $100 million led by at a $4 billion valuation, an eightfold increase from its valuation in September 2025. The 4-year-old company recruits and vets specialists who create training and evaluation data for AI developers. that participants included two frontier AI laboratories and two co-founders.
• , a San Francisco-based provider of expert-created AI training data, reached a $3.2 billion valuation in September, earlier, according to . The funding amount and lead investor were not publicly disclosed. The 1-year-old company���s datasets capture professional reasoning in fields such as software engineering, law and finance. AfterQuery was part of the Winter 2025 batch.

Robotics and autonomous driving

• , the Shanghai-based operator of Hello���s robotaxi business, raised about $100 million at a valuation close to $3 billion. fund led the round. The financing to the 1-year-old company will support a 10,000-GPU computing cluster, AI model development and commercialization of Level 4 autonomous driving.
• , a Sunnyvale, California-based robotics perception company, raised a $165 million Series C at a $1.6 billion valuation, led by . Founded by former and engineers, the 5-year-old company combines custom chips, sensors and spatial software to help robots perceive their surroundings. The financing will accelerate deployments across logistics, manufacturing and inspection applications.

Health insurance

• , a San Francisco-based health benefits company, announced a $200 million Series C at a $2.7 billion valuation. led the financing. It also includes $400 million in secondary financing for existing investors. The 7-year-old company provides a benefits platform using AI to make healthcare more affordable for small and midsize employers. The company services 5,000 businesses.
• , a San Francisco-based health benefits platform, raised a $108 million Series C at a $1 billion valuation. Investors included , , and . The 5-year-old company helps employers provide individualized health budgets for employees to select their own medical plans.

Energy and EV infrastructure

• China-based , a battery-swapping and charging company, agreed to a strategic transaction that gives a 30% stake. Geely will contribute its Yiyi battery-swapping operation and a $95 million investment. The 9-year-old company was valued around $2.4 billion.
• , an Austin-based developer of off-grid power systems for AI data centers, raised a $120 million Series A at a $1 billion valuation, led by . The less than 1-year-old company builds modular systems for renewable energy and battery systems as data-center operators seek access to electricity.

AI applications

• raised $150 million led by , at a valuation just over $2 billion. The 3-year-old company, headquartered in London with offices in Los Angeles and Mumbai, built an enterprise audiovisual content platform for media, advertising, sports and healthcare customers. The financing will support research, commercial expansion and a larger Silicon Valley presence.
• , a New York-based AI ranking and personalization company, raised a $90 million Series B at a $1.44 billion valuation, led by . The 2-year-old company���s software helps enterprises respond to customer behavior in real time, improving the relevance of recommendations.

Cybersecurity

• Rome-based , a cybersecurity company protecting connected devices and autonomous machines, raised $270 million at a $1.7 billion valuation, led by . The financing to the 8-year-old company will support U.S. and Asia-Pacific expansion and development of AI security models.
• Tel Aviv-based , a consumer cybersecurity company, raised $40 million at a $1.1 billion valuation, bringing total funding to $167 million. co-founder joined existing investors including and , among others. The 8-year-old company protects consumers against phishing, scams, malicious websites and AI-generated fraud.

AI models

• Beijing-based , a language-model startup, raised $120 million reaching a valuation of $1.4 billion. Investors include , , and . The less than 1-year-old company raised $400 million across three rounds so far this year, before releasing its first public model.
• , a San Francisco-based developer of open-weight foundation models, announced a $150 million Series B led by , and , valuing the company above $1 billion. The financing will support the 3-year-old company���s Trinity models and products for customizing and operating them.

Manufacturing and construction software

• , an AI company for manufacturing with dual headquarters in Tokyo and Chicago, raised a $114 million Series D at a $1.2 billion valuation, bringing total funding to $234 million. Investors included and . The 9-year-old company���s platform organizes design and procurement and production; the financing will deepen its technology and accelerate North American expansion.
• , a Georgia-based construction software company, secured a growth investment of $250 million led by , valuing it above $1 billion. The 17-year-old company manages construction projects, with the investment supporting its AI capability build out and commercial growth.

Defense technology

• , a Washington, D.C.-based defense company, emerged from stealth with $250 million raised across three rounds at a valuation above $1 billion. The 2-year-old company develops long-range cruise missiles with manufacturing in Texas, Germany and Israel. Backers who have led across three rounds include , , , 1, and .

Food

• , the New York-based parent of consumer food brands David Protein and HallPass, raised a $250 million Series B at a $2.25 billion valuation. and co-led the round. The financing to the 2-year-old company will expand retail distribution, develop new products and support additional brands.

Related 蹤獲弝け unicorn lists:

• (1,901)
• (666)
• (321)
• (198)
• (119)
• (102)
• (998)
• (547)
• (258)
• (39)
• (489)

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Methodology

The 蹤獲弝け 蹤獲弝け is a curated list that includes private unicorn companies with post-money valuations of $1 billion or more and is based on 蹤獲弝け 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 ��� such as those set via a 409a process for employee stock options ��� as these differ from, and are more likely to be lower than, a priced funding round. We also do not adjust valuations based on investor writedowns, which change quarterly, as different investors will not value the same company consistently within the same quarter.

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. 蹤獲弝け 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 蹤獲弝け long after the event was announced, foreign currency transactions are converted at the historic spot price.

Illustration:

Founded in 2016, Los Angeles-based Fifth Wall has grown into one of the largest investment firms focused on real estate technology, with roughly $3 billion in commitments and capital under management. Its portfolio includes , , and .

Notable exits include , which went public in 2024, and flexible workspace provider , which real estate giant of in January 2025 at a valuation of more than $800 million.

Major real estate and hospitality companies ��� including CBRE, , and ��� are among its investors, giving the startups it backs a direct connection to potential customers.

Wallace, who serves as CEO and chief investment officer, brings experience on both sides of that relationship. He worked in real estate finance at and before co-founding workforce analytics startup , which was acquired by in 2014, and ridesharing company .

As AI makes certain products easier to replicate, Wallace sees growing potential in startups that use technology to own and operate real estate themselves.

In a recent interview with 蹤獲弝け News, we discussed that shift, why proptech funding totals may overlook some of the sector���s biggest investments, what it all means for founders, and the housing problems he believes still need solving.

This interview has been lightly edited for brevity and clarity.

蹤獲弝け News: Our recent proptech funding analysis showed capital on pace to roughly match or slightly exceed last year, but across fewer deals. What does that tell you about the market?

Brendan Wallace: My sense is that statistic might belie the actual amount of funding flowing in, because what was previously characterized as proptech in the narrowest sense is probably representing a smaller share of where proptech investors are deploying capital.

There are increasingly horizontal solutions that are just as good, if not better, than many of the vertical solutions we���re seeing. We recently made a very big investment out of our growth fund into , the visualization software company. Most people reflexively think of that as being for movies or rendering scenes. But we saw real estate agents and commercial leasing brokers using it to represent spaces.

For an unbuilt home, you could feed it blueprints, have it build an entire home, put your family inside and walk through it in a full scene. That had surpassed the industry-specific solutions for space visualization that would have been narrowly defined as proptech.

Another category is investment flowing into full-stack businesses: real estate companies themselves. We just invested $135 million into , and I would be surprised if that fell under the definition of proptech.

Those are probably the two categories that might not be captured: horizontal software, with Higgsfield as an example, and businesses that reimagine physical space based on autonomy, AI or robotics. They���re actually building a physical thing. They���re building a real estate company, directly or indirectly.

How much is AI driving that shift toward software that serves multiple industries?

Wallace: It���s a big part of it. Without something profoundly better that you can���t replicate on your own, there���s less justification for buying outside software. There still is a justification, to be clear. There���s just less of one.

No real estate company can build the kind of visualization software Higgsfield has. I don���t believe they ever will. But a tenant engagement app they might have previously purchased and rolled out to their assets, they can now replicate over a long weekend.

The imperative to buy these third-party solutions has been reduced, and more value has been placed on the best horizontal solutions, whether that���s a foundation model or a specific use case like sound, audio or visual.

I don���t know the statistic, but it would be interesting to know how much real estate companies are spending on foundation models versus proptech applications. If I had to guess, we���re probably close to, or at, an inflection point where it���s passing it.

No one would characterize as a proptech company, but it might be taking a significant amount of the upstream proptech dollars, and an even larger share downstream once you go through the application layer.

Has AI reset the bar for what makes a venture-scale proptech software company? What does a startup need beyond adding AI to existing workflows?

Wallace: We���re still figuring that out, but I think it has to be something that can���t be replicated. Anything where the intellectual property moat is not extremely defensible is very challenged, and I think it will be for some time.

Simple application point solutions are becoming less financeable by venture investors because the capacity of one of the large labs to build that as an interface, or of a company to build it on its own, has caught up so dramatically.

The flip side is that bespoke AI development labs are now building solutions for the real estate industry. We backed one called , which is kind of like a for real estate. Antares works with a number of our strategic limited partners. They go in-house, identify a problem they think can be solved with an AI-based solution, build the intellectual property specifically for the organization, and leave it with them.

It���s more of a fee-for-development model than an intellectual property licensing model. You���re seeing that across industries, and you���re absolutely seeing it in real estate.

In some sectors, founders argue that domain expertise gives specialized AI companies an advantage over broad models. How durable do you think that advantage is?

Wallace: I���m a little more optimistic about foundation models’ and general intelligence’s capacity to adapt rapidly to specific use cases.

I wouldn���t argue that specific legal expertise, for example, is not valuable. But I think that moat collapses over time. You might be on a treadmill.

Think about what ChatGPT looked like in 2023 versus what Claude looks like today. At a basic level, it���s the same thing, but they���re totally different things. The sophistication, memory, capacity to be personalized, and ability to build off natural language instructions are unlike anything I think anyone could have anticipated in 2023.

What will that look like in 2029? I think what you���re saying is true today. It���s less true than it was, and it might become even less true in three years.

Is construction technology still an area of focus for Fifth Wall?

Wallace: It is, but it���s less of a focus today. When we look at our performance, it has generally favored two things: pure software businesses, whether marketplaces, consumer software or enterprise software, and full-stack businesses.

Anytime you get into physically doing things, the risk profile changes pretty profoundly. I don���t think it should be surprising that construction tech broadly is probably the biggest graveyard in all of venture. Maybe there���s a bigger category, but if there is, it���s not obvious to me.

Why do you think construction tech continues to attract significant funding?

Wallace: Because it���s still a massive market and a huge problem. If someone can bring greater efficiency to construction, you���re talking about one of the largest markets on earth. It���s such a massive prize that the largest funds are going to focus on it.

For founders raising seed or Series A funding, what opportunities would you encourage them to pursue that might not have been fundable a few years ago?

Wallace: You can actually build new real estate companies. That hasn���t really been conceptualized as being within a venture mandate, but it���s absolutely something we���d like to see.

For example, we have a better approach to buying multifamily assets, stripping out costs, and running more of the processes, operations and management with AI. That���s something I think is eminently fundable today by Fifth Wall and many venture funds. I don���t think that would have been the case five years ago.

I’d encourage founders to look at building full-stack, capital-R real estate businesses.

The second opportunity is around data. Real estate is characterized by extremely opaque data in a way that���s different from most large financial markets. Nothing that���s happened in proptech in the past 10 years has fundamentally changed that.

Where can generative AI provide signal through that opaque data to make capital allocation decisions? Real estate is generally a cash-flowing asset. We don���t necessarily think of it as comparable to bonds or stocks, but it is, and it should be.

Can you derive signal by looking at more data or different data, or use generative AI to predict what kind of real estate will perform better? The quantitative model that has existed for securities for a very long time now has the potential to affect real estate, because we have computational capacity that wasn���t previously possible.

Are there opportunities you���re interested in that have less to do with AI?

Wallace: We���re intrigued by the intersection of land, real estate and the financial instruments around them. To make most of what we describe as real estate, you usually have to build something on land. Land is an input to almost all real estate, but many real estate owners don���t want to own it or take on that risk profile.

Is there a way to decouple having to own land from owning and operating a building? That���s less about AI and more about financial engineering. There are new financial solutions emerging in that category that interest us.

How could AI, robotics and autonomy change the kinds of real estate businesses founders build?

Wallace: I���m interested in entrepreneurs who can conceptualize real estate through a sociological lens: New catalysts are changing how humans use space compared with the past.

That���s happened for a long time. E-commerce built the modern industrial real estate industry. Cloud computing, the internet and now AI built the data center industry. Cell towers were born out of mobile phones and smartphone technology. Genome sequencing helped create the lab-space real estate asset class.

I think we���re on the precipice of three new catalysts that will spawn entirely new real estate asset classes: AI, robotics and autonomy. In many ways, they���re entangled.

Do you expect fewer dedicated proptech venture firms? What would that mean for founders?

Wallace: I do think you���re going to see fewer vertical funds, in the narrowest sense of where we started this conversation. Dedicated venture capital funds investing in consumer and enterprise software focused on an industry ������ I think you���ll see less of that, and funding will probably continue to go down in that category.

The inverse is venture capital funding real estate businesses themselves. I think that���s about to explode.

If you were starting a company in this sector today, what problem would you most want to solve?

Wallace: Housing drives everything. Housing costs drive our economy, and the U.S. is grappling with a very real housing affordability crisis. It���s unclear how to solve it.

There are multiple approaches. One is building homes better, faster and cheaper ��� that���s construction tech. Another is financing homes at a lower cost. How do you bring efficiency to the housing finance market?

That���s a place where we���ve made a lot of money and invested a lot, but I would argue it���s still unsolved. Getting a mortgage is still painful, archaic, slow and too expensive.

Related to that is making regulation more efficient to improve housing affordability. That���s not something an entrepreneur can solve alone, but there���s potential to bring efficiency to how cities deal with this problem.

There���s an intersection of regulatory technology, policy work and consulting. How do we make it so more people can afford homes in the cities they live in? That problem isn���t going away. Despite everything that���s happened, housing has gotten more expensive, not less.

Related 蹤獲弝け queries:

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• Sector Snapshot: Proptech Funding Holds Up, But Investors Are Placing Different Bets

Illustration:

Per 蹤獲弝け data, a majority of the most active venture investors in Q3 participated in more deals compared to the prior quarter. This includes many of the usual busiest dealmakers, like , and .

The top lead venture investors also largely stepped up the pace this past quarter, even as the highest-spending among them appeared to put less capital to work. At seed stage, meanwhile, the typical top dealmakers largely held their ranks.

For a more detailed look, below we chart and analyze the most active investor ranks across multiple metrics, including venture dealmakers, high spenders, lead backers and seed funders.

Most active venture investors

We���ll start with the most active investors in post-seed rounds. By this measure, topped the ranks with 45 deals. The famed accelerator typically ranks high because it participates in follow-on rounds for startups it incubates.

Next on the list were Andreessen Horowitz, Insight Partners and Sequoia Capital. Overall, as charted below, at least 22 investors participated in 10 or more known venture rounds this past quarter.

Busiest lead investors

Among lead investors in venture rounds, Insight, Andreessen and ranked highest with 18, 16 and 12 rounds, respectively.

Another three investors ��� , Sequoia and ��� had 10 lead deals each in Q3.

Spendiest lead investors

We also attempted to get a sense of which lead investors put the most capital work in Q3. To approximate this, our ranking looks at investors whose lead rounds had the highest aggregate value.1

By this metric, Valor and Atreides tied for the No. 1 slot, with $7.7 billion in led or co-led deals for the quarter. The two had some overlap, with at least listing both firms as lead investors. This included ���s $3.9 billion Series F and ���s $375 million Series C.

Next in the ranking were Andreessen Horowitz and , with $6.5 billion and $6.3 billion in led or co-led Q3 deals. Andreessen���s tally largely stemmed from a $2 billion round for and a $1.7 billion financing for .泭 Nvidia���s standout deal was a $5 billion round for .

Seed investors

Seed investors also kept busy in Q3. Among them, the busiest by far was Y Combinator, which participated in at least 221 known seed rounds this past quarter, per 蹤獲弝け data.

also ranked high, with 31 reported seed rounds, followed by and with 24 and 23 reported deals, respectively.

Overall, another busy, AI-driven quarter

Overall, our active investor rankings paint the picture of another busy quarter for startup funding, with AI driving the bulk of dealmaking.

Mostly, it���s familiar names topping our various rankings. However, we are seeing a few firms significantly scaling up their investments, with Atreides and Valor in particular stepping up their game of late.

Related 蹤獲弝け query:

Related reading:

• North America���s Startup Funding Falls In Q3 As AI Giants Eye The Public Markets
• 蹤獲弝け Data: Q3 2026 Posted A Record Count Of Billion-Dollar Rounds As The Global AI Race Heats Up

Illustration:

蹤獲弝け startup funding reached $25 billion last quarter, well above the $14 billion invested in Q3 2025 and up slightly from the $24 billion invested in Q2. Quarterly funding was up 77% year over year, per 蹤獲弝け data.

While the U.K. continued to lead startup funding totals last quarter, Germany and France both posted their strongest quarters since the boom years of 2021 and early 2022. Last quarter���s funding totals were boosted heavily by a $3.5 billion investment in Paris-based , the largest venture round ever for a Europe-based company.

Table of contents

• Billion-dollar fundings
• Venture expands beyond the UK
• Late-stage rise
• Early stage
• Seed
• Looking forward
• Methodology
• Glossary of funding terms

Billion-dollar fundings

Four 蹤獲弝け companies raised billion-dollar-plus fundings, representing close to 40% of the region���s startup capital raised last quarter.

They include Mistral, which also announced its new open-source model Large 4, an LLM it claims outperforms competing open source models on several vectors.

Data center provider raised a convertible note of $3.36 billion that it says it will convert once it goes public, which it has filed plans to do.

Two defense tech startups also raised billion-dollar-plus rounds last quarter: raised a Series E of $1.8 billion, and raised $1.2 billion.

AI drove 75% of 蹤獲弝け funding this past quarter ��� totaling $18.8 billion ��� the highest proportion on record.

Investments in physical tech in Europe in defense, data centers, energy, aerospace and robotics accounted for roughly half of 蹤獲弝け funding in Q3.

Venture expands beyond the UK

The U.K. led the region���s quarterly funding totals with $7.5 billion even as Germany and France gained market share for venture capital funding in Q3 with $5 billion and $4.8 billion invested, respectively.

The fourth-largest market, Sweden, saw $1.5 billion in venture capital invested while the Netherlands and Spain posted their strongest quarter since the COVID boom years with $1.4 billion and $1.2 billion invested in their startup markets, respectively.

Late-stage rise

A total of $17.3 billion ��� 70% of Europe���s Q3 venture capital ��� was invested in late-stage deals in 83 companies.

Outside of the billion-dollar rounds, large late-stage fundings between $400 million to $700 million were raised by Stockholm-based health scanning provider ; Lisbon-based autonomous drone developer ; Spain-based , which offers model compression technology for enterprise AI adoption; Amsterdam-based AI deployment startup ; Bayern-based space transportation company ; and Stockholm-based AI web application builder .

Early stage

Europe���s early-stage funding totaled $5.7 billion into just over 200 companies in Q3, down quarter over quarter and flat year over year.

The largest Series A funding deals, each $200 million or over, were raised by Eindhoven-based AI semiconductor startup and Z羹rich-based autonomous construction company .

Large Series B rounds were raised by Munich-based fusion energy company and London-based optical computing provider .

Seed

Europe���s seed funding fell quarter over quarter and was flat year over year. Around $2 billion was invested in more than 750 companies at seed stage in Q3.

London-based managed inference company raised the largest seed round at $100 million, followed by Munich-based AI for robotics startup , which raised $55 million.

Looking forward

Europe���s momentum in 2026 continued in Q3, which was the second quarter this year when venture totals topped $20 billion. Those are figures not seen in the region���s startup scene since Q3 2022. Along with growth in AI funding, late-stage funding noticeably increased last quarter with many of the leading rounds sourced across multiple 蹤獲弝け countries.

Europe represented 16% of global venture capital in Q3, although the true impact of its technology and startups is higher, with many of the region���s startups expanding or moving to the U.S. to capitalize on the rapid growth of AI there.

At the same time, Europe���s ambition to build leading deep-tech companies and meet demand for sovereign AI will be tested in the quarters ahead by its ability to mobilize the substantial capital these businesses need.

Related 蹤獲弝け queries:

Related reading:

• 蹤獲弝け Data: Q3 2026 Posted A Record Count Of Billion-Dollar Rounds As The Global AI Race Heats Up
• Reporter���s Notebook: Europe���s Sovereign AI Push Needs Customers As Well As Capital

Methodology

The data contained in this report comes directly from 蹤獲弝け, and is based on reported data. Data is as of Oct. 5, 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. 蹤獲弝け 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 蹤獲弝け 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. 蹤獲弝け 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. 蹤獲弝け 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 ���Series [Letter]��� 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 ���venture��� round. (So basically, any round from the previously defined stages.)

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Historically that wasn���t the case. But more recently, startup investors are putting more capital to work around these themes.

Over the past year, venture backers have poured close to $3 billion into good-sized rounds for marine-related startups in sectors ranging from defense tech to clean energy, per 蹤獲弝け data. Top areas for investment include autonomous sea vessels, water robots, electric watercraft and ocean data.

Lead fundraisers

A single company ��� ��� accounts for most of the past year���s haul. The Austin-based startup, which develops autonomous sea vessels and counts the as a key customer, secured $1.75 billion in Series D funding in March.

The round, led by , set a $9.25 billion valuation for 4-year-old Saronic, which is scaling at a fast clip. The company announced this summer that it plans to invest more than $3 billion to build a next-generation shipyard in Brownsville, Texas, focused on software-defined shipbuilding and autonomous maritime systems.

China-based , a developer of marine robotics technology, was a distant second for equity fundraising. The 3-year-old startup closed on a $150 million Series A round in July backed by a long list of venture investors.

In third place, meanwhile, is Rhode Island-based , a developer of vessels called Seagliders that operate just over the water at the speed of an aircraft. The 6-year-old startup picked up $120 million in Series B equity funding in August led by maritime-focused investor and , plus an additional $120 million in debt financing.

Overall, 蹤獲弝け data showed quite a few maritime-focused startups funded in roughly the past year that have raised significant capital to date. To illustrate, below we put together a sample list of 27 that fit this criteria.

Top investors

Several investors have assembled particularly prolific portfolios of companies focused on the seas.

Among generalist VCs, one standout is , a backer in three companies on our sample list: Saronic, electric-boat maker , and , a developer of small, autonomous craft for undersea environments. In its April Series A lead investment in Ulysses, the firm pointed to promoting U.S. naval supremacy as an investment theme, along with reengineering technologies first envisioned on land to also work at sea.

is another generalist that has emerged as a marine startup serial investor. The firm has backed three companies on our list: Regent, , a builder of battery electric cargo ships, and , a developer of renewable energy systems in the ocean.

Besides cross-sector venture investors, 蹤獲弝け data also shows a growing array of specialized firms with multiple maritime startups in their portfolios. This includes , focused on startups reducing emissions from boats and ships, and , a marine-focused investor with Pentagon backing.

Autonomy, AI and robots

While the sea may be exotic terrain for venture dealmaking, in many ways maritime funding fits pretty cleanly into prevailing investment trends.

Perusing the sample list of funding recipients from the past year, for instance, three sectors account for the vast majority of funding: autonomy, AI and robotics. Notably, these are core areas of strength for venture investments tied to land and space as well.

Moreover, a hefty chunk of marine investment also has defense tech applications. This coincides with the sharp rise overall in recent quarters in venture investment in startups with military applications.

Of course, it remains to be seen whether venture investors��� enthusiasm will continue for what looks to be a capital-intensive space to scale. For now, however, marine-focused startups are managing to convince backers they can do a lot more than just stay afloat.

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• Sector Snapshot: Defense Startup Funding Hits An All-Time Record As VCs Begin To Eye Exits

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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���s 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 蹤獲弝け 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 ���s 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���re 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���t work out while aiming for the outliers. I think that���s 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���ve built the firm around people who are actively working with AI. If you aren���t building, productizing, pricing or taking AI to market regularly, it���s 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���ve encountered many of the same challenges.

We also use AI throughout the firm. We���ve 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���re 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���t 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 ���AI for the real world.��� What does that mean when you���re 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���re doing work that matters to customers in real-world industries.

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

You���ve 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���s 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���re 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���ve seen that buying behavior play out across the majority of the portfolio companies we���ve 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���re doing important work inside a customer���s business, and that work is worth a lot of money, you become difficult to replace. You���re 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���ll 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���t 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���t changed. We���re still asking what will be built on top of AI infrastructure and models. We want to invest while the answer is emerging, before there���s a consensus.

What happens when one of those early bets doesn���t 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���re 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���t work.

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

Related 蹤獲弝け query:

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So far this year, global startups have secured at least 114 Series A rounds泭1 of $100 million or more, per 蹤獲弝け data. That���s the highest annual total in years and on track to top the all-time peak.

Moreover, many of those jumbo early-stage rounds far exceed the $100 million threshold. Collectively, this group of Series A recipients has raised around $33 billion this year, with at least 12 rounds valued at $500 million or more.

An AI thing

The funding bump was mostly an AI-driven phenomenon. Per 蹤獲弝け data, more than 70% of Series A rounds of $100 million or more went to AI-focused startups.

That figure encompasses some of the year���s largest early-stage financings. For instance, it includes a $1.2 billion round for Silicon Valley-based , a platform for developers to train and serve custom models, and a $900 million financing for China-based , a developer of AI-enabled humanoid robots.

Below, we put together a sample of 10 of the largest Series A rounds, including mostly AI but a few other areas as well.

The high preponderance of AI deals reflects what we���ve been seeing across stages. In the first half of this year, venture and growth funding to artificial intelligence startups totaled an estimated $394 billion, roughly 77% of all investment capital. Granted, most of that was for later-stage financings. But our Series A data shows early-stage doesn���t look too different for AI���s share.

US leads for jumbo Series A deals.

Roughly half of this year���s $100 million-plus Series A rounds and funding went to U.S.-based startups, per 蹤獲弝け data. That translates to about 62 deals with a collective value of around $15 billion so far in 2026, which puts it on track for a record tally.

Still, megaround funding at Series A is more globally dispersed than overall venture investment this year. In the first half of 2026, more than three-quarters of global seed- through growth-stage financing went to American companies, largely due to megarounds for Silicon Valley-based and .

When investors like the same things

One can point to several potential causes behind the rise in Series A megarounds beyond AI growth alone. For one, leading startup investors have exceptionally large capital reserves to deploy. Additionally, exit multiples historically, and to an even greater extent recently, reward those who are anything but modest in their ambitions.

At Series A, another factor may be that investors seem to agree more than usual on the sectors, business models and founding teams they want to back. And given that a pricey share of a winner still beats a discounted share of a laggard, they���re piling in to perceived early-stage leaders.

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• 蹤獲弝け Data: Global Startup Investment Hit Record $510B in H1 2026 As AI Boom Accelerates Funding And Exits

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From putting nuclear reactors on barges to grading how well AI models can control robots, this month���s crop of interesting startup deals takes AI and other emerging technologies well beyond the conventional software stack.

Other companies that caught our eye are applying automation to the decidedly old-school worlds of building-material procurement, commercial property maintenance and farm recordkeeping. Let���s take a closer look.

$50M to put nuclear power at sea

Nuclear power plants are famously difficult and time-consuming to build. thinks putting them on barges could offer another way.

The Long Beach, California-based startup raised what it says was an oversubscribed $50 million seed round led by , just two months after emerging from stealth with $10 million in pre-seed funding. The of investors in the deal included , , , and others.

Bluecore is developing compact, water-cooled small modular reactors designed to operate aboard floating barges. Rather than spending years constructing a new power plant and the accompanying infrastructure on land, the idea is to manufacture the systems and move them to where electricity is needed.

���Our focus is simple. Create and deliver zero-emission energy as safely and quickly as possible,��� CEO and founder wrote in a social media . ���Over 3 billion people live within an hour of water. We want to power them all.���

Its first target is the Port of Long Beach, with other ports and power-hungry AI data centers among the potential customers. The company says it���s working with the and as it pursues certification.

Bluecore���s raise comes amid a broader nuclear funding boom. Nuclear fission startups alone pulled in roughly $2 billion in venture funding in 2025, per 蹤獲弝け data, and investors have continued writing enormous checks this year. More broadly, cleantech-, EV- and sustainability-focused startups raised about $15 billion in the first half of 2026, with second-quarter funding reaching its highest quarterly level since 2024.

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$31M to bring AI to the building-materials business

Ordering cement and steel might not sound like an obvious AI use case, but Saudi Arabia-based sees a lot of room for improvement.

The Riyadh startup last week said it had secured $31 million in new capital, consisting of a $13 million Series B equity round co-led by , ���s venture arm, and , plus an $18 million growth-debt commitment from under a previously announced facility. The company has now raised more than $83 million, .

BRKZ operates a marketplace that connects construction companies with suppliers of building materials, while also handling sourcing, logistics and financing. More interestingly, it says it has amassed some 38 million structured data points that power an AI pricing engine trained on roughly 40,000 requests for quotes.

The company says 84% to 89% of its predicted prices come within 5% of the eventual transaction price. Another AI agent reads photos of cement delivery notes sent through , matches them to orders and verifies deliveries ��� with roughly three-quarters processed without human intervention.

BRKZ is riding a in Saudi Arabia even as startup investors remain selective about construction and property technology more broadly. Global proptech startups raised about $6.5 billion via roughly 640 deals in the first half 2026, 蹤獲弝け data shows. That’s on pace to top last year���s dollar figures, even as deal count has dipped this year. Similar to other startup sectors, investors in proptech are increasingly directing capital toward companies using AI and automation to cut costs and streamline operations.

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$24M for robots to take care of commercial properties

Robots are already assembling cars and moving packages around warehouses. wants them to also mow lawns and sweep parking lots ���泭and do security patrols of those properties while they���re at it.

The Santa Clara, California-based autonomous robotics startup last week said it has raised a $24 million Series A led by to scale its fleet of robots designed to handle outdoor property maintenance for commercial real estate owners and operators.

Its machines combine autonomous navigation with attachments that allow them to perform jobs like sweeping, debris removal and landscaping tasks ��� all while conducting ���soft security��� ��� across large campuses and commercial properties.

Rather than trying to build a general-purpose humanoid robot, Viabot is applying autonomy to repetitive jobs that property owners already pay people and contractors to perform. The startup, which operates on a ���robot as a service model,��� sees an opportunity to fill a labor shortage for what���s often considered ���dirty, dull and dangerous��� outdoor work, , founding partner at , told 蹤獲弝け News in 2021, when the company raised earlier funding.

Startup investors are pouring money into those sorts of real-world AI applications. Global venture funding to physical AI companies ��� including robotics, autonomous vehicles, aerospace, drones, industrial automation and sensors ��� reached $47.4 billion across 521 deals in the first half of 2026, 蹤獲弝け data shows. That’s nearly 4x the $12 billion invested in the second half of 2025 and almost 80% above the year-ago period.

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$10M to give AI robots an independent report card

As frontier AI models move from controlling software to controlling robots and machines in the real world, wants the public to have an independent way to understand what they can actually do.

The 3-month-old San Francisco startup announced last week that it raised a $10 million seed round led by , with participation from , , and others.

Robocurve says it wants to act as an independent third-party auditor for physical AI, testing how well frontier models can control real robots and publicly reporting the results. The company says its own research has already found that general-purpose large language models can outperform specialized robotics vision-language-action models on some simple tasks.

Importantly, Robocurve isn’t positioning itself as a conventional robotics benchmarking startup. It is incorporated as a Public Benefit Corporation with a legal duty to independently evaluate the robotics capabilities of frontier AI systems and report those findings to the public.

The company says AI labs don’t dictate its research agenda, evaluation methodology or published results, and it plans to work with governments, policymakers and civil society as robot capabilities advance.

Academia is a big part of that model, too. Rather than developing every benchmark itself, Robocurve funds academic teams and supplies them with robot hardware to create open-source benchmarks. More than 200 institutions ��� including researchers from 19 of the world’s top 20 universities, according to the company ��� have signed up for its benchmarking program. Robocurve is offering a combined $500,000 in funding plus free robotic arms to participating academic groups.

Its funding is timely given the massive influx of capital pouring into robotics and physical AI. Within the broader physical AI sector, robotics startups alone raised more than $21 billion globally in the first half of 2026, 蹤獲弝け data shows, already eclipsing the nearly $16 billion raised in all of 2025 and even the $15.3 billion invested during the venture market’s 2021 peak.

As ever more powerful models move from screens into machines capable of manipulating the physical world, figuring out what those models can ��� and can’t ��� safely do becomes a more consequential problem.

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$5M to let farmers talk instead of type

A lot of agricultural software has one basic problem: Farmers don���t spend their days sitting at desks.

With that in mind, this month raised a $5 million pre-seed round led by for a voice-first AI platform designed specifically for farmers, agronomists and other agricultural workers.

Instead of asking someone working in a vineyard or almond orchard to stop and fill out a form or type notes into a computer, Tellia enables them to leave a voice note, send a message, or even submit a photo to log records, generate reports and set reminders. It says its AI then turns that unstructured information into records associated with the correct field, crop and crew.

For example, for a livestock farmer that might mean a voice prompt like: ���Tellia, the vet just checked Herd 3. All clear, next health check due in 6 weeks, log that.���

Or a vineyard manager might ask: ���Tellia, based on this year’s Brix and pH logs, what’s the projected alcohol level for the Cabernet lot?��� and receive an instant answer based on previously collected data.

San Francisco- and Paris-based Tellia was founded last year and says its technology is already deployed across 1 million acres, including at and wineries in the U.S., as well as agricultural organizations in Europe.

and also participated in its latest funding.

Its raise comes amid a much tougher environment for agtech startups overall. Venture investment in agriculture and farming remains in a correction from its 2021 peak, when startups in the space raised $10.5 billion across more than 1,400 deals, 蹤獲弝け data shows. That makes companies applying increasingly cheap and accessible AI to specific, everyday farming problems an interesting corner to watch. Voice AI, in particular, has emerged as one of the hot spots in artificial intelligence funding in recent years.

Related 蹤獲弝け query:泭

Related reading:

• Sector Snapshot: Robotics Startups On Fire As Venture Funding Surges To Record Numbers In 2026
• VCs Pour Billions Into Physical AI As The Next Wave Of AI Investing Takes Shape
• Sector Snapshot: Agtech Startups Face A Drier Funding Climate
• Why Big Investors Are All Ears For Voice AI Startups

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The highest-valued new entrants were China-based humanoid robotics business , valued at more than $6.3 billion; San Jose, California-based photonics company , valued at $5.5 billion; and Palo Alto, California-based AI model platform , and San Francisco���s semiconductor manufacturing startup , both valued at $5 billion.

AI software featured prominently across model training, assistants, agentic and enterprise workflow automation, coding and voice transcription.

Semiconductors was the second-largest sector, with five new unicorns. Robotics and financial services each added three, while data centers, security and energy each added two.

The U.S. accounted for 16 of August���s new unicorns. China followed with four. South Korea, India, Singapore, the United Arab Emirates, Switzerland, Germany and Turkey each added one. Nigeria and Indonesia also each added one new unicorn ��� for both, their first new unicorn of the year.

Nine companies exited the 蹤獲弝け in August, per 蹤獲弝け data: Three that went public ��� the most notable being ��� and six via acquisition, including , and .

New unicorns in August

Here are August���s new unicorn companies:

AI and software

• , a Palo Alto, California-based platform for training, fine-tuning and deploying custom AI models based on proprietary data, announced $1.1 billion in funding led by and . The less-than-1-year-old company, founded by former co-founder , was valued.
• San Francisco-based , an AI assistant that executes personal tasks, raised a $250 million Series B led by and . The 1-year-old company was valued at $2.5 billion.
• Shanghai-based , a builder of agents for digital and physical environments, raised a $220 million seed round led by and . The less-than-1-year-old company was valued at $2 billion. Its founder, , a researcher, left earlier this year.
• San Francisco-based , which builds AI-powered voice-writing and meeting-transcription tools, raised a $280 million Series B led by , who also led its Series A in 2025. The 5-year-old company was valued at $2 billion.
• San Francisco-based , which provides AI-powered code review and change-management tools, raised a $143 million Series C at a $1.5 billion valuation. and co-led the round. The 3-year-old company said it would commit more than $10 million to keep its tools free for open-source projects over the next year.
• San Francisco-based , which deploys AI agents across calls, email, documents and enterprise systems, raised a $150 million Series C at a $1.2 billion post-money valuation. and led the round. The company is 4 years old, started in logistics and has expanded to insurance, energy, telecommunications and airlines among others and counts 150 enterprise customers.
• Turkey-based , a developer of consumer mobile applications, raised a $50 million Series A led by . The 4-year-old company was valued at $1.25 billion. Its apps include AI chatbot Nova, diagnosing plants with PlantApp, and art generator DaVinci.

Semiconductors

• , a San Jose, California-based developer of photonic interconnects for AI computing infrastructure, raised a $700 million Series C at a $5.5 billion valuation. , , , and led the round. The 2-year-old company is already deployed within data centers.
• raised $400 million in funding led by hedge fund . The 1-year-old company was valued at $5 billion. The San Francisco-based company creates tooling for semiconductor manufacturing and was founded by researchers.
• South Korea-based , which develops edge AI processors for on-device inference, raised about $29 million in the first tranche of its Series D funding from existing investors. The 8-year-old company targeting robotics and electronics was valued at about $2.2 billion.
• Shanghai-based , an AI chip startup for inference, raised a Series A led by local state capital investors and . The 4-year-old company was valued at about $1.5 billion with plans to ship its product in Q4 2026.
• Santa Clara, California-based , which develops low-power silicon and software for AI data centers and physical AI, raised a $110 million Series A led by . The 4-year old company was valued at more than $1 billion.

Robotics

• China-based , which is building the general-purpose IRON humanoid robot, raised more than $900 million in its first outside financing at a post-money valuation exceeding $6.3 billion. led the round, with participation from and support from and Alibaba Group. The company, a subsidiary of public smart electric vehicle company , is 10 years old.
• Singapore-based , which develops robots to operate in real-world environments, raised about $669 million in funding. The 2-year-old company was valued at about $3.3 billion and is set to deploy robots in a Dairy Queen in Shanghai to handle the entire 55-step process of taking orders, preparing the food and handing it to a customer.
• Zurich-based , which develops autonomous technology for heavy construction machinery, raised a $200 million Series A led by . The 4-year-old company was valued at $1 billion and works across multiple construction brands.

Financial services

• Bengaluru-based , a financial-services company spanning payment, lending and insurance, raised $100 million in funding led by . The 7-year-old company was valued at $1.3 billion.
• Berlin-based , a finance AI platform for 蹤獲弝け mid-sized businesses to泭 manage spend, card issuing and expenses, raised a $40 million Series C led by and . The 7-year-old company was valued at around $1.15 billion. The company says it has 5,000 businesses that use the service to give finance teams control.
• Palo Alto, California-based , an AI-native enterprise resource planning platform for accounting, raised a $100 million Series C led by . The 4-year-old company was valued at $1 billion.

Aerospace and defense

• Los Angeles-based , a manufacturer of autonomous military drones and counter-drone systems, raised a $250 million Series C at a $2.5 billion post-money valuation. and the co-led the round. The company is 3 years old. Neros has contracts with the U.S. military as well as half a dozen allied countries.
• Mountain View, California-based , which builds and operates satellite constellations for national security, civil and commercial customers, raised a $250 million Series C led by . The 5-year-old company was valued at $1.5 billion.

Data centers

• Palo Alto, California-based , a vertically integrated AI infrastructure platform, raised a $300 million Series A led by , , and . The less-than-1-year-old company was valued at $2.4 billion. Alongside the equity, Volta secured $5 billion in debt to fund data center buildouts.
• , a full-stack AI infrastructure and neocloud platform, received led by Doha-based broadband provider , which holds a 49% stake. Jakarta-based Zankore is less than 1-year-old and is valued at $1.6 billion. The platform is targeting 1 gigawatt of AI computing capacity.

Security

• San Francisco-based , an AI-native security company that provides autonomous penetration testing, raised a $250 million Series E led by and . The 7-year-old company was valued at $2 billion and is used by 7,000 organizations including defense, Fortune 10, banks and healthcare companies among others.
• Palo Alto, California-based , which provides security for AI agents and third-party applications, raised an $85 million Series D led by . The 9-year-old company was valued at $1.1 billion.

Energy

• China-based , a nuclear fusion company developing small modular reactors, raised about $179 million in seed funding. The 1-year-old company was valued at about $1.5 billion.
• Washington, D.C.-based , which develops software that adjusts AI data-center workloads based on power-grid demands, raised a $150 million Series A at a $1 billion valuation. and co-led the round. The 2-year-old company says the round brings total funding to more than $220 million.

Transportation

• Nigeria-based , a vehicle financing and autonomous fleet management infrastructure, raised a $250 million Series C led by , and . The 7-year-old company was valued at $2.1 billion. It operates a fleet of 42,000 vehicles ��� both human-driven and autonomous ��� across 29 cities, with annual recurring revenue of $420 million.泭

Critical minerals

• Houston-based , which builds mines and refineries using its MarianaOS software platform, raised a $310 million Series B led by . The 2-year-old company was valued at $1.5 billion.

Web3

• Dubai-based , an AI-enabled stablecoin neobanking platform for cross-border payments and tokenized assets, raised a $68 million Series C led by Tokyo-based at a $1 billion valuation. The 7-year-old company says it processes more than $40 billion in annualized transaction volume.

Related 蹤獲弝け unicorn lists:

• (1,862)
• (658)
• (276)
• (195)
• (119)
• (102)
• (961)
• (547)
• (254)
• (39)
• (489)

Related reading:

• Global Venture Funding Jumps 122% In August As Streak Of Billion-Dollar Deals Continues
• Which Investors Have Backed The Most 2026 Unicorns?
• 40 Companies Joined The 蹤獲弝け In July, The Highest Count In 4 Years

Methodology

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

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

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

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

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

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

AI infrastructure dominated the largest venture rounds this week, with two multibillion-dollar deals in the sector taking the top spots. Data center and cloud provider led with a massive $3 billion financing, followed by ���s $1.5 billion raise. Further down the list, AI inference startup landed $300 million, joining a diverse group of big fundings spanning cybersecurity, robotics, food, HR software, payments and healthcare.

1. , $3B, AI infrastructure: Denver-based Crusoe raised a $3 billion Series F co-led by and, with also participating. Originally founded to use stranded natural gas to power cryptocurrency mining, Crusoe has transformed into a major AI cloud and data center provider serving customers including , and . The company has raised nearly $7.2 billion to date, and the latest financing values it at $30 billion ��� triple its valuation less than a year ago ��� according to 蹤獲弝け.

2. , $1.5B, AI infrastructure: New York-based Fluidstack raised $1.5 billion in a private equity round led by, bringing the AI infrastructure company���s total funding to just over $2.6 billion. Fluidstack provides large-scale GPU and data center infrastructure for demanding AI workloads and has emerged as one of a growing group of companies spending heavily to meet soaring compute demand for AI. The financing values the company at $18 billion.

3. (tied) , $300M, AI infrastructure: San Francisco-based Gimlet Labs raised a $300 million Series B led by, with investors including ,, and . Gimlet is building an AI inference cloud that distributes workloads across different types of chips, an approach aimed at making the increasingly compute-intensive process of running AI models faster and more efficient. The company has raised $392 million to date and was valued at $3 billion in the latest round, .

3. (tied) , $300M, cybersecurity: San Francisco-based Upwind Security raised $300 million in new funding co-led by and. Other investors included 1,, and . The company���s platform uses real-time cloud runtime data to identify threats and vulnerabilities, putting it at the intersection of two particularly well-funded areas: cloud security and AI. Upwind has raised $730 million to date and was valued at $3.8 billion in this latest deal.

5. , $250M, food and nutrition: New York-based high-protein food company David raised a $250 million Series B co-led by and., and company co-founder also participated. Best known for its high-protein, low-calorie bars, David has expanded into other protein-focused foods as consumers continue gravitating toward products marketed around protein and metabolic health. The company has raised $335 million and was valued at $2.25 billion in the latest round.

6. , $166M, HR software: New York-based HiBob raised $166 million in a round led by, with also participating. HiBob���s Bob platform combines HR, payroll, benefits and employee-management tools, and the company is increasingly positioning its workforce data as a foundation for enterprise AI applications. The latest deal brings its total funding to $740 million and values the company at $3.2 billion.

7. , $165M, robotics and physical AI: Sunnyvale, California-based Lyte AI raised a $165 million Series C led by, with participation from,, and. Founded by former engineers, Lyte develops custom silicon, sensors and AI software that help robots perceive and understand their surroundings, the kind of technology that underpins the fast-growing physical AI sector. Lyte has now raised $272 million to date, , and was valued at $1.6 billion in the Series C.

8. , $155M, fintech and payments: Mountain View, California-based TabaPay secured $155 million in growth financing led by. The company provides money-movement infrastructure that helps banks and fintech companies instantly disburse, collect and transfer funds. The company announced the latest funding as it also of federally chartered , a move that could deepen its role in payments infrastructure. TabaPay���s new round follows a Series A of an undisclosed amount back in 2022.

9. , $125M, health care and oncology: Nashville, Tennessee-based Thyme Care raised a $125 million Series E led by , the healthcare investment arm of . Other backers included, and, among others. Thyme Care works with health plans, employers and providers to coordinate cancer treatment and manage oncology care, part of a broader shift toward value-based specialty care. The company has now raised $399 million in total and was valued at $2 billion in the latest round.

10. , $100M, AI cybersecurity: Austin-based HiddenLayer raised a $100 million Series B led by.,, and also participated. HiddenLayer builds security tools designed specifically to protect AI models, agents and workflows from attacks and vulnerabilities, a category gaining urgency as enterprises move AI systems into production. The company has raised $156.2 million to date, .

Methodology

We tracked the largest announced rounds in the 蹤獲弝け database that were raised by U.S.-based companies for the period of Aug. 29-Sept. 4, 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.

Related reading:

• Former Apple Engineers��� Physical AI Startup Lyte Raises $165M At $1.6B Valuation
• VCs Pour Billions Into Physical AI As The Next Wave Of AI Investing Takes Shape

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