On the ������Ƶ ������Ƶ, we track active investors over all time. Here, we look at the investors in the companies that gained horns in the most recent funding cycle to see which firms predominate.

New unicorn counts have picked up significantly year over year. So far this year, 250 companies have joined the board through Aug. 15, up from 2025’s 193 companies. Leading sectors included robotics, AI labs, healthcare and biotech, financial services, AI infrastructure, and AI deployment, among others. Of the companies, 139 (56%) are U.S.-headquartered, and 47 (19%) are from China.

An analysis of ������Ƶ data finds that most of the funding these companies raised came in 2026: a whopping 75% of all funding — $74 billion out of $98 billion. By contrast, 30% of deals took place in 2026, the highest count so far by year, with 329 deals. Nonetheless, most deals occurred in prior years, with seed investments starting in 2012, Series A in 2014, and Series B rounds in 2017, though the pace has picked up since 2024.

The Top 10 most active investors in this cohort by investment count were Sequoia Capital, Khosla Ventures, Y Combinator, , , , , , , and .

Y Combinator is the only accelerator on this list and BoxGroup the single seed investor to make the Top 10. (formerly Sequoia Capital China), headquartered in Hong Kong with offices across China, is the notable investor from Asia on this leading list of 29 investors. Private equity firms and are in this leading list, and on the corporate venture capital front and are featured.

Seed portfolio

Y Combinator and Sequoia Capital had the largest seed portfolio counts, with investments of $20 million or less. Seed investor BoxGroup, headquartered in New York, had the third-largest count of seed portfolio companies, a significant achievement since it invests in far fewer companies than Y Combinator and its funds are a fraction of what Sequoia Capital raises.

Also impressive were with five companies at seed, and , Lux Capital and Founders Fund, each with four portfolio investments at seed. Among this cohort, Lux Capital and Founders Fund had the largest crossover, sharing three portfolio companies out of four.

Series A leaders

The most active Series A lead investors were Andreessen Horowitz, with Khosla Ventures and tied with Sequoia Capital at six investments each. Series A investment sizes show a wide range, from $6 million to $500 million. Larger Series A rounds were not dominant but noticeable for many of these firms, except for , Founders Fund and Bessemer Venture Partners.

As funding activity, unicorn creation and valuations accelerated in 2026, the investors with the largest portfolios were those with early-stage access and the resources to continue backing companies as they scale. Established multistage firms dominate the rankings, while only a handful of accelerators, seed specialists, corporate investors, private equity and Asia-based firms break into the leading group.

The next test will be whether this year’s newly minted unicorns can turn rapid capital formation and lofty valuations into durable, category-defining businesses.

Related ������Ƶ queries:

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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.

is back raising another $5 billion, after it raised that amount eight months ago. The largest fundings also went to an AI neolab, data center and electricity storage, defense, coding and biotech. Let’s take a look.

1. , $5B, data platform: Databricks has surpassed a $7 billion revenue run rate, with more than 80% year-over-year growth in Q2. The San Francisco-based company raised $ 5 billion in a funding round led by with participation from , , and new investor . Databricks was valued at $134 billion back in December 2025 when the company announced it had surpassed a $4.8 billion revenue run rate. From its Series A funding of $13 million in 2013, the 13-year-old company has raised around $25 billion in funding over all time, per ������Ƶ data.

2. , $1.1B, AI reinforcement learning: Founded earlier this year, River AI raised $1.1 billion across its seed and Series A rounds led by and , with strategic investment from and . Its founder, , has been at the center of AI developments at , and over the past decade. The Palo Alto, California-based company seeks to build AI that is personalized and trained directly on what a company or person needs to accomplish, giving the end user control.

3. , $750M, electric grid: Form Energy raised a Series G funding round led by . The Massachusetts-based company builds longer-lasting 100-hour batteries for grid electricity storage. A host of investors participated, including private equity, venture and angels, and infrastructure and climate-focused investors , , , , , , and the .

4. , $250M, defense: Neros Technologies, a defense drone manufacturer and drone interceptor, raised a $250 million Series C led by and . The Los Angeles-based company, founded in 2023, has raised $370 million to date, per . The company announced that by 2028 it will be building 1 million drones per year. It has contracts with the U.S. military and half a dozen allied countries across Europe, Asia and the Middle East.

5. , $143M, AI code review: CodeRabbit, which has developed an open-source AI code review technology used by 150,000 open-source projects and 17,000 customers, according to the company, is on a roll. London-based and Los Angeles’ led its Series C, and the Walnut Creek, California-based company plans to set up a London office based on customer interest across Europe. As coding becomes increasingly automated, code review is critical to determine which projects meet production standards.

6. , $136M, datacenter networking: Point2 Technology, which builds interconnect solutions for AI data centers, raised an extension of its Series B led by Korea-based , including a strategic investment from and participation from existing investor . The San Jose, California-based company raised $136 million in the Series B.

7. , $110M, organ preservation: Bridge to Life, a 21-year-old organ preservation company, raised a $100 million Series C funding led by and . The Illinois-based company is developing an organ viability assessment tool to expand the market and will use the proceeds to extend its VitaSmart technology to U.S. transplant centers.

8. (tied) , $100M, protein therapeutics: Aureka Biotechnologies, an AI-native drug discovery platform, raised $100 million in Series B funding led by . Based in Shanghai and California, the 3-year-old company has raised $200 million to date. Proceeds will go toward training its model with its lab-in-the-loop feedback mechanism.

8. (tied) , $100M, loyalty rewards: PointsKash, a loyalty reward mobile app, raised private equity funding led by . The Florida-based company provides in-store kiosks for cash, loans and rewards.

10. , $90M, biotechnology: Epicrispr Biotechnologies, a developer of genetic medicines, raised a $90 million Series C led by and . The San Francisco-based company develops treatments for neuromuscular disease through modulating genes.

Large non-US deals:

Several startups based outside the U.S. also raised notable rounds this week. They include:

, $400M, automated applications: Lovable raised a $400 million Series C funding led by and , valuing the company at $13.3 billion. The Stockholm-based company claims 900 million visits each month and 60 million projects created. Lovable’s Series B raise in December 2025, co-led by Menlo Ventures, valued the company at $6.6 billion.

, $300M, defense: Cambridge Aerospace, a U.K. defense tech company, raised a $300 million Series C led by . The 2-year-old company raised a $200 million Series B in April led by and . Since its Series B funding, the has committed to purchasing its Skyhammer air defense system to intercept drones and low-speed missiles.

Methodology

We tracked the largest announced rounds in the ������Ƶ database that were raised by U.S.-based companies for the period of Aug. 8-14. Although most announced rounds are in the database, there may be a small time lag, as some rounds are reported late in the week.

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Leading sectors by count were financial services, robotics, AI orchestration, multimodal AI, energy and the semiconductor industry.

In the past two months, the board added more than $100 billion each month in value from newly minted unicorns. Three companies joined the board at decacorn values. , and together added $49 billion in the past month.

The U.S. counts 19 new unicorn companies, just under half of the newly minted unicorns in July. China, the second-largest country, numbered eight. From the U.K., there were three companies, and from Singapore, two. Lithuania, Germany, Spain, Hungary, Australia, India, Israel and Hong Kong each count one.

Among the newly minted unicorns, 15 were less than 3 years old. And seven companies were more than 10 years old.

So far this year, the count of new unicorns has accelerated. A total of 195 companies joined in H1 this year, already exceeding the total for all of 2025.

New unicorns in July

Here are July’s new unicorn companies:

Financial services

• Singapore-based , an affiliate of the private payments company , raised a $1.2 billion Series A funding round with participation from Ant Group and . Ant International was spun out in 2024 and was valued at $11.2 billion in this recent funding.
• , a digital banking platform for banks and credit unions, raised $115 million in private equity funding led by . The 9-year-old San Ramon, California-based company that supports customer retention and services was valued at $1.6 billion.
• Budapest-based , an auto insurance provider using AI, raised a $23 million Series B funding round led by . The almost 2-year-old company, founded by a Serbian team, was valued at $1.6 billion.  Ominimo reports $350 million in gross written premiums and is approaching 1 million customers. It operates in Hungary, Poland, the Netherlands and Sweden, and plans to expand across Europe and to the U.S. in 2027.
• , an AI-native private bank for high net worth business owners, raised a $70 million Series B led by . The 4-year-old San Francisco-based company was valued at $1.2 billion.
• , a membership and savings app for U.S. consumers, raised $65 million in Series D funding led by . The 10-year-old San Francisco-based company was valued at $1.2 billion. Surpassing $200 million in net revenue in 2025 from membership and transactional revenue, the company says it is growing 50% year over year and is approaching 1 million members.
• London-based , a savings app which has become a digital wealth management platform, raised a $60 million secondary market transaction led by . The 11-year-old company was valued at $1.1 billion. The secondary sale is to provide liquidity for long-term employees. The company is profitable and has helped 200,000 people buy their first home.

Robotics

• Guangdong-based humanoid robotics company raised $200 million in pre-IPO funding. The 4-year-old company is focused on entertainment, hospitality, and service for humanoid robotics, not manufacturing, with half of its orders coming from outside of China. The company was valued at $2.2 billion.
• Shenzhen-based , a builder of precision tactile sensing technology for robotics, raised $148 million in Series E funding. The 10-year-old company was valued at $1.5 billion.
• London-based , a humanoid robotics company for manufacturing, retail and logistics, raised a $152 million Series A funding led by . The 2-year-old company was valued at $1.4 billion and plans to roll out its wheeled beta version robots to customers in Q4. It has also developed a software brain, KinetIQ, to reason and execute complex tasks alongside humans.
• Full-stack physical AI company emerged from stealth with a $300 million seed funding led by and . The less-than-1-year-old Cambridge, Massachusetts-based company focused on manufacturing and logistics was valued at $1.1 billion.
• , an embodied intelligence company, raised a $147 million seed funding round led by and . The less than 1-year-old Nanjing, China-based company is focused on closed-loop learning, building robotics for manufacturing with the ultimate goal of building a general-purpose robot for the home. The company was valued at $1 billion.
• Dexterous hand robotics company raised a $74 million Series A funding led by . The 1-year-old Hangzhou, China-based company was valued at $1 billion.

AI

• Lithuania-based , a public data web scraping service useful for AI applications and agentic AI, raised its first external financing, a $130 million Series A led by . The company reports $350 million in ARR serving 350,000 tech teams. The 11-year-old company was valued at $3.6 billion.
• Spain-based , a compression technology for AI that improves efficiency and cost, whether on device or in the cloud. It raised a $570 million Series C led by , and . The 7-year-old company was valued at $2.3 billion.
• , creator of synthetic users for consumer research, raised a $200 million Series B led by and . The company raised a $100 million Series A five months earlier. The 1-year-old Palo Alto-based company was valued at $2 billion.
• runs a full-stack platform for companies to train models and agents. It raised a $130 million Series A funding led by . The 2-year-old San Francisco-based company was valued at $1 billion.
• , an enterprise infrastructure management platform for AI, raised a $100 million Series D led by . The 7-year-old San Jose, California-based company was valued at $1 billion.

Multimodal AI

• Beijing-based , a text prompt-to-AI short video startup, raised a $2.8 billion funding round led by , , , , and . The 2-year-old company, a subsidiary of with plans to spin out, was valued at $18 billion.
• , a company that creates 3D visualization from text or image prompts, raised a $400 million Series B funding led by , and . The 5-year-old Sunnyvale, California-based company, used in gaming, 3D printing and design, was valued at $1.5 billion.
• , which provides access to leading models for text, video, image and audio while retaining user privacy, raised a $65 million Series A led by . The service stores communication on a user’s device. The 2-year-old Wyoming-based company was valued at $1 billion.
• Beijing-based , a multimodal model developer, raised a $222 million Series C led by ,, and . The 3-year-old company, used for film, marketing, and social media content creation, was valued at $1 billion.

Energy

• Munich-based nuclear fusion company raised a $470 million Series B led by , , and . The company has offices in Munich, Zurich and Oxford. The 3-year-old company was valued at $2.7 billion.
• a provider of thermal energy storage for data centers, raised a $550 million Series C funding led by and. The 8-year-old San Jose, California-based company was valued at $2.5 billion.
• , a hydrogen-boron fusion company, raised an undisclosed seed round led by , and . The less-than-8-year-old China-based subsidiary of the was valued at $1.6 billion.

Semiconductor

• Israel-based , a fabless semiconductor company building data processing units and chips for data centers and computing systems, raised a $300 million Series E led by . The 9-year-old company was valued at $2.8 billion. The next generation of will be routing via the company’s X2 chip, according to VP of Starlink engineering, .
• Shanghai-based developer of a satellite communication baseband chip for 6G communications, raised an undisclosed amount following a $216 million Series C round earlier this year. The 6-year-old company was valued at around $1.5 billion.
• , a chip company that connects smaller chips to make them more efficient, raised a $145 million Series C led by . The 5-year-old Santa Clara, California-based company was valued at $1 billion.

Cryptocurrency

• Singapore-based , a regulated app for buying, trading, and spending cryptocurrencies, raised a $400 million corporate round. Led by , this marks the company’s first institutional funding. The 10-year-old company was valued at $20 billion.
• , a U.S. stablecoin digital clearing bank for international financial institutions, raised a $180 million Series B led by . The 4-year-old San Francisco-based company was valued at $1 billion.

Defense

• Former Doge employees founded to provide AI-driven cyber capabilities to the U.S. military. Cathedral raised a $160 million Series A led by and . The less-than-1-year-old Washington, D.C.-based company was valued at $1.4 billion.
• London-based , a maritime defense company, raised a $175 million Series B led by . The 6-year-old company was valued at $1 billion.

Marketplace

• , a technology platform for service businesses, raised a $44 million Series D led by . The 10-year-old New York-based company was valued at $1.2 billion. Genius AI operates in the wellness, beauty and health sectors and is approaching a $200 million revenue run rate.

• , a platform for travel advisers, raised a $60 million Series D led by and . The service has 15,000 travel advisers and has booked more than $3 billion in travel over time. The 5-year-old New York-based company was valued at $1 billion.

Data center

• Mumbai-based , a data center service hosting GPUs, one of the largest GPU compute providers in India, raised $150 million in funding. The 7-year-old subsidiary of the was valued at $3.9 billion.

Insurance

• , an insurance platform for some of the largest e-commerce customers, raised $100 million in funding. The 12-year-old New York-based company was valued at $1.9 billion. Its customers include , , , , and , to name a few.

Quantum

• Quantum computing company raised a $300 million Series A led by , and . The less than 1-year-old South Pasadena, California-based company was valued at $1.5 billion.

AI coding

• Autonomous app building startup raised a $130 million Series C led by , and . The 2-year-old Pleasanton, California-based company was valued at $1.5 billion. The company launched a year ago and has enabled non-coders to build applications, with 12 million built on the platform.

Legal

• , an AI legaltech firm that pairs lawyers with agentic AI, raised a $120 million Series C led by . The service is client-oriented, with payments based on outcomes rather than billable hours. The 3-year-old New York-based company was valued at $1.2 billion.

Security

• , an endpoint security firm for the AI era, emerged from stealth, announcing a $100 million Series B led by , , and . In 2025, ahead of launching out of stealth, Glow raised large seed and Series A rounds. The 1-year-old Palo Alto, California-based firm with offices in Tel Aviv was valued at $1.2 billion.

Wearables

• Hong Kong-based smart glass company raised a $150 million Series B led by and . Founded by ex- engineers, the startup is not camera-based but rather a display that beams information visible to the wearer.  The 2-year-old company was valued at $1 billion.

Related ������Ƶ unicorn lists:

• (1,850)
• (644)
• (245)
• (193)
• (117)
• (102)
• (953)
• (546)
• (251)
• (39)
• (491)

Related reading:

• Global New Unicorn Counts In The First Half Of 2026 Have Already Surpassed 2025’s Totals

Methodology

The ������Ƶ ������Ƶ is a curated list that includes private unicorn companies with post-money valuations of $1 billion or more and is based on ������Ƶ 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. ������Ƶ 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 ������Ƶ long after the event was announced, foreign currency transactions are converted at the historic spot price.

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We spoke with to talk through the firm’s evolution and how it is meeting this AI moment. She is a partner at the firm who relocated to Silicon Valley from Mexico City.

When the firm was founded in 2005, Brazil didn’t yet have a startup ecosystem — there was no network of founders, no LPs backing VC firms based there, and no follow-on investors. That has changed drastically in the couple of decades since, with the country emerging as LatAm’s startup powerhouse and a place where U.S. investors and tech giants are increasingly courting business.

Brazil is an exceptionally digitally savvy market. It is the for and the third-largest . Its real-time payment rail , created by the , was rolled out in 2020 and is used by more than 90% of adults in the country.

Latin America has also become an important market for U.S. AI labs and technology companies. Monashees recently announced a partnership with called the in which the two companies co-invest up to $2 million in AI-native and deep tech pre-seed or seed-stage startups in Brazil. Its first summit is planned for later this year in San Francisco, where it will gather Latin American startup founders building businesses with AI.

Monashees makes around eight to 10 new investments per year and is finalizing the deployment of its $370 million fund into roughly 35 companies.

The firm opened an office in Mexico City in 2022 and in September 2025 set up an office in San Francisco.

The interview has been edited for brevity and clarity.

Gené Teare: To set this up, tell me about Monashees.

Fabiola �ϳܾ��Գ���ñ�Dz�: Monashees is the pioneer of venture capital in Latin America. It started 20 years ago, in 2005, with the premise that what had happened in Silicon Valley with tech could also happen in LatAm — that many of the structural problems could be solved with tech.

and , Monashees’ co-founders, were crazy enough to believe this could happen, so that’s when they started Monashees. Just to give you a little context, back in the day there was nothing. It really took time for this flywheel to get started, because if you don’t have funding, you don’t have great talent.

Finally, after five years, they managed to crack that. In 2010, you started to have the first wave of tech companies in the region, and Monashees started positioning Brazil on the global tech map.

As a second phase, the team realized that what was happening in the Brazilian ecosystem was also starting to happen in other countries in the region. Great teams were starting to build great companies. That’s when Monashees decided to expand across Latin America and back these teams. That’s when we led ’s seed round, one of the flagship companies of Latin America.

The third wave, which is what we’re focused on right now, is Global LatAm: backing Latin American founders who are building global businesses, regardless of whether they are building in Latin America or globally.

That has also been the rationale for opening an office in San Francisco. In the context of AI, you have many Latin American founders starting businesses from here because you have to be close to the labs and the talent.

We’re early-stage investors. We invest at pre-seed, seed and Series A. Seed and Series A are our sweet spot, and we are lead investors. We’re also generalists. We’re not sector-specific, we’re mostly sector-agnostic.

I see this trend when I talk to a lot of ������Ƶ VCs with earlier-stage investors, establishing a U.S. presence. It seems fairly recent, and it seems to be driven by this AI wave. Do you think it’s the VCs coming here and the founders following, or are the founders coming first and the VCs realizing they need more of a presence here?

�ϳܾ��Գ���ñ�Dz�: I think initially it was mostly founders. Now, it’s a little bit of both; they’re feeding each other.

The reason we started the office in San Francisco is that the pace at which AI evolves is unseen, even compared with other technology paradigms in the past. If you’re not here, it’s very difficult to keep pace and stay up to speed with where the AI frontier is going. You even have a gap with Wall Street, so imagine the gap with Latin America.

If you want to build an AI-native company as a Latin American founder, part of that is coming to San Francisco and Silicon Valley. San Francisco is now the magnet for all of this. It’s highly dense and concentrated. You have to be here to absorb the tools and understand what other people are doing.

I also think it’s super important because founders realize that Silicon Valley is the champions league. In Latin America, you do have great talent, but you don’t know what great looks like if you’ve never worked here.

The reason we opened an office here is to bridge that gap: to help founders be here, see what is happening at the frontier, and understand what the best companies are doing so they can replicate that back in LatAm.

The talent in the region is now sophisticated enough. It has been a 20-year process to get to a point where you have great, ambitious founders who believe they can build global businesses.

You already have success stories like from or from . Founders realize they can build globally.

In the context of AI, many of these global companies have to be based here because you have access to AI talent, but also to funding. Being close to all the Silicon Valley funds is also crucial for them.

I do think several founders are coming here to build, but that also creates some issues. One important thing to note is that many of these founders are building for the Latin American market, where your revenue is in Brazilian reais or Mexican pesos. In terms of headcount, you need to be very careful that you don’t have a U.S. cost basis when your revenue is in Brazilian reais or Mexican pesos.

These very early-stage startups also cannot compete with the big labs here that are paying a lot of money for talent. Right now in San Francisco, finding AI talent is really difficult and it’s very expensive.

I think it’s more about coming here, learning and bringing back the best practices. That’s where the real arbitrage opportunity comes from. You have amazing talent in LatAm, and you can teach them. Now, in the context of AI, you have much better ways to do that and you can operate with a smaller headcount.

That’s the rationale for founders coming here and for us being here as a bridge. We help our portfolio companies stay close to AI innovation, but we also get access to Latin American founders who are building from the U.S.

We hired a researcher for the Monashees team. Andrés [Campero] has a Ph.D. from in AI. He’s one of the disciples of , who is a very renowned researcher. The rationale for having Andrés, who is Mexican, on the team is to help us connect with the research diaspora here in San Francisco. It’s very different to talk about business than it is to talk to researchers.

This is important because most researchers from Latin America don’t stay in Latin America. They come to the U.S. and work at the different universities here. It’s important for us to be connected to where most of the innovation is happening. Andrés also helps us identify the best companies emerging in the region from a technology standpoint.

Of those, how many are coming to the U.S. at the earlier stages? What proportion do you expect to come here?

�ϳܾ��Գ���ñ�Dz�: Some of the companies we’re seeing start in LatAm and then expand to the U.S.

We have a portfolio company called . It’s AI-native, and it develops preventive-maintenance software. The company started in Brazil.

Its customers were global businesses, and those customers started pulling the company into the U.S. Its product was much better than what was available here. The company is now headquartered in Atlanta, so you could say it’s a U.S. company now.

Most of its revenue comes from the U.S. I think examples like that — companies born in LatAm that expand globally — will tend to be around 30% of the portfolio.

Companies we invest in from the U.S., where most of the revenue will be U.S.-based, will probably be around 20%, because we continue to be a LatAm-focused fund. But we’re also going to see more LatAm-born companies coming here.

You mentioned the focus on Latin America, and talent is obviously very difficult to find here in the U.S. right now. For the companies that are based here, do you see them setting up offices in LatAm to attract talent? Are most of them using a hybrid model, or are some completely U.S.-based?

�ϳܾ��Գ���ñ�Dz�: It depends on the stage they’re at. Later-stage companies — think Series C or Series D — tend to have most of their technology teams in Brazil, Argentina or elsewhere in LatAm.

Another example is . It’s headquartered in Salt Lake City, but most of its technology team is in Brazil, in a smaller city called João Pessoa.

The company is building very sophisticated AI infrastructure. It was able to do that because it was very good at hiring a senior team that could teach and transfer knowledge to the local team.

We’re seeing more of that. You start with senior people, senior researchers or senior data scientists in the U.S., while much of the junior team is in LatAm.

Now, with AI, you can have fewer junior people. But you also have talent in Latin America that is strong enough to act as the senior engineers.

What are the standout companies in the Monashees portfolio that you would highlight?

�ϳܾ��Գ���ñ�Dz�: I’ve shared a couple. One is Tractian, the preventive-maintenance software company. The company has been growing. It’s a success story for us because it started in Brazil, and it has proprietary technology. It combines software and hardware, and it owns the patents for its hardware.

Today, it is really conquering the U.S. market. It’s a perfect example of an AI-native company born in Brazil, where the AI lab lives in Brazil, but the company is competing at the global level.

We also have Music.AI, which is in a fun industry. If you’re an amateur musician, its platform allows you to play whatever song you want and play with the instruments in the background. You can play the drums, the flute or whatever you want while having the other instruments behind you. The company has both a B2B and a B2C business. It has more than 50 million users or downloads and is growing very fast. It won iPad App of the Year two years ago. It’s another success story. It is based in Salt Lake City, but has its technology team in Brazil.

We recently invested in a company called . It’s an accelerator, so it’s similar in some ways to what we’re doing with Google. Shiva is trying to capture this new wave of entrepreneurs who might not have pursued entrepreneurship if Shiva and AI didn’t exist. , the founder, is a second-time founder. He was one of the early co-founders of one of our portfolio companies, which later went public. You can think of Shiva as the of Latin America in the sense that it is very community-driven. It is also trying to capture these solopreneurs: companies started by just one person that can go global from day one and have revenue from day one.

I think it’s a super-interesting and very different investment. It speaks to how we’re always trying to keep pace with how the ecosystem is going to evolve, because this ecosystem is also likely to be disrupted by AI.

I can also tell you about some of the companies in the portfolio that are focused specifically on Latin America.

We have a company called . It’s an HR platform. It’s very specific to the Brazilian ecosystem because regulation requires employers to provide certain benefits to employees. Flash managed to build a technology product around that, and now the company is expanding into a full HR platform. It’s one of the flagships of Fund IX. It’s growing very fast, and it has become a flagship company in Latin America. Fintech is one of the largest and most important markets in Latin America.

Another company was actually the first investment I made at Monashees. It’s a payment-orchestration platform called . The company is at the Series B stage. We invested at seed back in the day. It gives an e-commerce company a single integration through which it can manage all of its payment methods. If you’re a multinational company — think about — and you want to enter Brazil, Colombia and Peru, you have to deal with so many payment methods. With Yuno, you have just a single integration. In the context of AI, Yuno has developed a very strong agentic platform that helps with fraud and conversion. Fraud in LatAm is a big issue, and the platform helps companies manage fraud and increase conversion across these marketplaces.

Related ������Ƶ queries:

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In this bifurcated funding environment, we also see a wide range in valuations, as well as select companies that raised multiple rounds at a significant valuation increase in the space of months.

Among this cohort, robotics and AI neolabs were the leading sectors for new unicorns. Other industries that stand out were in financial services, healthcare and biotech as well as AI infrastructure, AI deployment and devtools, defense, semiconductor and aerospace.

H1 new unicorns have added roughly $440 billion in value to the board — 5% of the board’s current value. These companies have raised $80 billion over time, representing 5% of funding raised by still-private, unicorn-valued companies.

The most valuable new unicorn this year is China-based open-source model developer , which was valued at $50 billion in its first external financing. Seychelles-based crypto exchange , valued at $25 billion, is the second most valuable company to join in the first half of this year.

San Francisco-based , majority owned by and valued at $14 billion when it raised $4 billion from private equity, is in the third spot.

From this cohort, four companies were valued as decacorns in H1, and a further five were valued above $5 billion, as of early August 2026.

Based on trends for 2025 companies, we expect valuations for this cohort to climb significantly in the next year. For the 193 new unicorns that joined in 2025, 12 were decacorns and another 18 were valued above $5 billion. Nine of those decacorns for this cohort became $10 billion-plus-valued companies in 2026.

US leads, China picks up

The U.S. leads with 110 companies — 56% of new unicorns in H1. China was in second place with 38 companies, a significant surge from 10 new unicorns in 2025. The U.K. was the third-largest market with 13 companies joining.

By continent, North America accounts for 115 new unicorns, Asia with 50 and Europe with 27. Latin America, Oceania and Africa each count for one.

Fast raises

In the current frenzied funding environment, 19 of H1’s new unicorns raised fast follow-on rounds, often in six months or less, and doubled on an earlier valuation to reach at least $2 billion or more.

Notable among the fast fundraisers are semiconductor startup , which doubled its prior valuation to $10 billion from $5 billion just six months earlier; defense tech unicorn , whose valuation vaulted to $7.9 billion, up from its prior $1.6 billion valuation seven months earlier; and , building nuclear energy reactors for AI, was valued at $6 billion, up from $2 billion four months earlier.

AI momentum

Trillions in value were added to The ������Ƶ ������Ƶ in the first half of the year, including from some of the largest-ever venture funding deals. The first six months of 2026 also notched the largest venture-backed exit of all time: ’s IPO.

Taken together with the rapid follow-on raises at ever-larger valuations some of those companies have achieved, it’s clear that the momentum around the fastest-growing companies has picked up significantly in this AI cycle.

Related ������Ƶ unicorn lists:

• (195)
• (1,839)
• (643)
• (232)
• (192)
• (117)
• (102)
• (947)
• (542)
• (250)
• (39)
• (489)

Related reading:

• A Record 14 Billion-Dollar Rounds In July Pushed Venture’s Historic Run Higher
• Led By DeepSeek, 10 Frontier Labs Rush Onto The ������Ƶ ������Ƶ In June
• ������Ƶ Data: Global Startup Investment Hit Record $510B In H1 2026 As AI Boom Accelerates Funding And Exits

Methodology

The ������Ƶ ������Ƶ is a curated list that includes private unicorn companies with post-money valuations of $1 billion or more and is based on ������Ƶ 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. ������Ƶ 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 ������Ƶ long after the event was announced, foreign currency transactions are converted at the historic spot price.

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July ranked as the third-largest funding month of the year, up 10% over June, following on the heels of a record-breaking first half of 2026, when startups raised $515 billion globally.

Fourteen startups raised billion-dollar rounds in July, the highest count in a single month, though not the largest amount raised in such deals, an analysis of ������Ƶ data shows. The tally includes nine U.S.-based companies, two each from Germany and China, and one company headquartered in Singapore.

The largest startup funding deal last month was a $10 billion investment in , the first external financing for the -founded space exploration company.

, a frontier lab founded by former Chief Scientist , reportedly raised $5 billion from . The next two largest deals were Beijing-based frontier lab ’s $3.5 billion raise after releasing its latest Kimi K3 model, and raising $2.8 billion for short-video generation.

Two Germany-based companies in defense tech also raised billion-dollar rounds: and . In the U.S., companies that raised billion-dollar-plus rounds spanned the energy, industrial robotics, AI training, security and semiconductor industries.

Funding to AI

A total of $35 billion, or around 53% of global venture funding, went to AI-focused companies in  July. Other leading sectors were aerospace, defense and energy.

U.S.-based companies raised a total of $39 billion, or around 59% of global venture capital, last month with roughly half of the capital invested in its AI-focused companies.

Exits

July was also a robust month for startup exits, including via acquisition and public-market debuts.

Venture-backed M&A totaled more than $9 billion in July, with five companies exiting at prices  over $1 billion, ������Ƶ data shows. Notable acquisitions included London-based data center provider ’s roughly $1.65 billion acquisition of software layer , which was built to manage AI workflows, and in the security sector, AI-native security company ’s $1 billion acquisition of , a service to manage non-human identities.

Twelve venture-backed companies went public above $1 billion in value in July, including five from China, six U.S.-based companies, and one from Italy. The largest was Chinese chipmaker , which went public at around $85 billion and . Italy-based , an acquirer of software companies including and , went public at a value of $18.5 billion. And last-mile transportation company , founded in 2017, went public at $1.6 billion in value, raising $167 million in the process.

In closing

If the first half of 2026 established that venture has entered a new era of mega-financings, July reinforced that the trend is broadening rather than fading. Record numbers of billion-dollar rounds in both hardware and software, alongside a healthy IPO and M&A market, point to an ecosystem where capital is not only concentrating in category leaders but is also beginning to recycle through exits.

Related ������Ƶ queries:

Methodology

The data contained in this report comes directly from ������Ƶ, and is based on reported data. Data is as of Aug. 3, 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. ������Ƶ 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 ������Ƶ 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. ������Ƶ 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. ������Ƶ 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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has spent nearly two centuries adapting to successive industrial revolutions — evolving from a 19th century steel and heavy machinery company into a global leader in energy management and automation. Now, through its 1 billion Euro venture fund, , the company is betting that the next transformation will be driven by AI’s collision with the physical world, from data centers and power grids to robotics and industrial automation.

For , who joined SE Ventures in 2022 after leading corporate investments at , AI’s biggest opportunities extend well beyond software. As demand for compute strains energy infrastructure and accelerates reindustrialization, the firm is backing startups building the technologies that underpin the AI economy — investing in everything from data center infrastructure and grid resilience to robotics and industrial AI.

������Ƶ News spoke with Chaturvedy about where those opportunities are emerging, why energy has become AI’s defining constraint, and how industrial technology is being reshaped by the AI era. “We were set up with the intent to figure out where the market is headed,” he said.

The significance of the energy and industrial sectors has grown with AI, and that has led even traditionally tech-focused venture investors to rush into the space. “Today, the scarce resource in this entire space is the capacity to build — building, real estate, energy, power and electrification gear,” Chaturvedy said.

SE Ventures , and has notched 12 exits including its most recent, , a 3D metal printing technology acquired by Tokyo-based electronic manufacturer

The firm will often take board seats or board positions and work to bring value to its portfolio companies.

Around 80% of the startups in its portfolio have some level of commercial relationship with a business unit of Schneider Electric. Most often that’s as a partner servicing Schneider’s customers, which is the holy grail, according to Chaturvedy. Sometimes it’s as a vendor, although that remains a smaller set of use cases.

In our conversation, we spoke about power scarcity, the electrical grid, workforce training, reindustrialization and notable portfolio companies.

The interview has been edited for length and clarity.

Gené Teare: Which sectors or investments are you focused on? Where there is a lot of drive or interest because of what is happening in AI?

Chaturvedy: Three things come to mind, especially in terms of the areas we invest in versus the broader construct of the market.

First, AI is getting embedded, and you need to train models, whether open source or proprietary. Model training has upleveled to inference so you need AI infrastructure. is a great example of that.

Five years out, when this CapEx cycle starts to come down and new data centers are perhaps not getting created, data center efficiency will become a hot topic. We are also investors today in a company called , which focuses on that problem. That will come three, five or seven years out. It is going to come. It is not a problem today because we are on the upswing of the CapEx cycle.

Together AI and Hammerhead AI are very interested in partnering with Schneider Electric, because Schneider Electric is a leading electrification player in the data center space. It makes a lot of gear and equipment that go into these data centers. Today, the scarce resource in this entire space is capacity to build: buildings, real estate, energy, power and electrification gear.

The other market impacted by the emergence and growth of AI is the interplay with the grid. There are more demands on the grid beyond the electrification of vehicles, and it is 100x or 1,000x bigger than what we saw with vehicles needing to get charged from inside houses. The grid could not keep up with that capacity in the past, and it certainly cannot keep up with these demands today.

More project developers are coming in and setting up renewables or other types of capacity, but again, the interplay is still with the grid. Anything that helps with grid resilience is clearly an area for us to invest in.

The third thing is the transformative impact of AI on the world of industrials. That is where we are quite excited. Robotics is one clear area where a general-purpose model can allow the same robotics hardware to do multiple different tasks that were not possible in the past, because cognition and inference were not possible at the edge before the advent of large language models.

Companies like in our portfolio — which is one of the most exciting companies at the intersection of robotics and AI — are market-leading indicators of where this world is headed.

There is also an element of using AI to deliver better use cases in the field. Companies like in our portfolio essentially capture warranty data, analyze it and feed results back to design engineers in big corporations. There are a lot of OEMs and hardware companies looking for select use cases where AI can actually be very transformative.

That is what customers are looking for: How can AI be transformative for my business? Whichever startup is working with me in that transformation journey is the startup that will move from POC to adoption overnight. That is essentially the world of successful startups.

Overlaying on top of this is a confluence that we see and watch from our vantage point. When you think about the energy efficiency that needs to happen in these industrial worlds, energy technologies and industrial technologies have to collaborate and deliver those use cases while being energy efficient. That was not the case in the past. Energy was cheaper and more readily available.

Now industrial is taking off. There is more AI adoption. The workforce is getting older, and there is no way to overnight train a workforce in America, so you have to rely on AI. You are going to consume more and more AI for industrial use cases, which was never a business imperative in the past.

This is where the worlds of enterprise and industrial are colliding very quickly in the world of AI.

Increasingly, what I hear is that the bottleneck for AI at this point is energy. Are you seeing some short-term solutions that help with this? What about longer-term technologies?

Chaturvedy: It’s very clear that from a short-term basis — and this isn’t quite an energy-related solution — it’s more about tokens. If you think about the unit economics of an AI data center, it’s the tokens. To generate a token, it costs electricity. To train your model, or infer from a model, you need a lot of tokens. The bigger the model, the bigger the data set, and the more complex the use cases, the more tokens.

Ultimately, it’s a battle of producing tokens cheaply and also consuming fewer tokens through the models that exist today. That’s where optimization is happening, but that’s more in the enterprise space: How can I write clever versions of software that allow me to do essentially that?

The longer-term solution is going to be about — actually, maybe there is a middle layer also — beyond the tokens: When I’m running my data center, can I push inference to a different point in time so I’m not consuming peak electricity rates? Can I manage my HVAC better? You need cooling systems to cool your data center environment, and there are techniques that work really well there. Schneider has also bought some assets in the past.

Then the longer-horizon cycle is really about creating new generation capacity, largely through renewables, hopefully. That’s where I think the whole renewable story, at least in the U.S., becomes very interesting going forward. Related to renewables is storage, which we haven’t touched upon, but BESS — battery energy storage systems — is another space that we look at very closely.

There is a huge discussion in Europe and in America around reindustrialization. How do you see that playing out, given the sectors you’re focused on, industrialization and energy?

Chaturvedy: I don’t think America or Europe really have a choice other than to reindustrialize, given the geopolitical situation and a variety of other factors that I’m sure you fully track as well.

We know that technologically, the U.S. has a competitive advantage. We produce great software engineers, we move fast, and innovation is the lifeblood of U.S. society. There is a lot of innovation happening here, whether it’s robotics, newer models, setting up data centers, energy generation, and so on. That’s where the U.S. is going to lead as we think about reindustrialization: training the workforce, doing things more automatically, with the holy grail being AI startups that result in lights-out manufacturing facilities.

That becomes more of a possibility now. We are never going to be able, in my opinion, in the next three to five years, to replace an aging workforce and expect them to be trained to the same level that a technician with 30 or 50 years of experience was at. But it is now possible that every blue-collar worker with AI in their hands as an assistant becomes a knowledge worker.

Earlier, we used to think about knowledge workers as IT people or white-collar jobs. I think that’s changing. Everybody will be a knowledge worker. AI will be such an equalizer in that sense. There will be different use cases in different environments, but that doesn’t change the business reality. Everybody becomes a knowledge worker.

The second thing to note is that not every job will come back. There is a reality of inflation, cost of living, and the quality of living in America that people are used to, whether it’s base pay, hazardous environments, number of shifts or what have you. As a society, we’ve made certain choices. We’ll be smart about how we leverage more AI and more robotics to get what we want, and not try to emulate other manufacturing-heavy geographies.

But as an economy, as more AI comes, we will move to a different level in terms of what constitutes the GDP of America and the goods and services underneath.

How long do you think that takes to play out?

Chaturvedy: There are certain industries where it’s already happening, data centers being at the forefront. Mainly because the need is very urgent, and there are significant dollars at play today in the data center space, where people are willing to spend the money. In a capitalistic society, everybody is going to chase money. The data center happens to be that today.

But in the next three to 10  years, depending on the CapEx refresh cycle of different industries, we will see more greenfield projects emerge that are natively robotics-oriented and natively industrial automation-oriented, because AI has already caught up.

Right off the bat, every new factory that gets online in the next seven to 10 years will have a basic level of productivity that is way higher than a new factory set up 30, 20 or 15 years ago. The ROI from that factory would be so strong that you would have to expand more capacity there. And by the way, capacity would also be more scalable.

On reimagining or thinking through the data center stack: is there anything you want to say about that as we close out?

Chaturvedy: We specifically invest in AI for energy and industry, looking across the full stack from data infrastructure to training and inference, through to AI agents solving real-world use cases. We also consider the enabling layers around that stack, like multi-cloud, multi-LLM, cybersecurity, and data governance.

Ultimately, every industry is going to build its own version of this stack, and we believe the most compelling companies will be the ones who drive tangible outcomes in enterprise and industrial environments.

Related ������Ƶ queries:

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Ten of those companies were AI labs, collectively valued at $65 billion. The most well-known was Beijing-based open source model developer — at $50 billion, the highest valued new unicorn to join the ������Ƶ this year.

The new unicorn frontier labs are focused on new architectures in AI model development in robotics, physics and self-learning, as well as on open source development, and in the case of one India-based startup, sovereign AI.

Other leading sectors with multiple companies were in robotics and AI infrastructure, with four companies in each.

Of the new unicorns, 16 are U.S-based, while eight are from China. Two new unicorns joined the board from India, Germany and the United Kingdom and one each from Netherlands, Belgium, Canada and Saudi Arabia.

Big exits remove a trillion

Despite the influx of newcomers, the total value of The ������Ƶ ������Ƶ dropped by more than $1 trillion in June as , its most valuable company, went public.

Other notable exits from the board last month were , the maker of AI coding tool Cursor, which was acquired by SpaceX for $60 billion after last being valued at $29.3 billion. , an AI infrastructure company that operates as a layer on top of GPUs, was acquired by , and customer experience agent was purchased by 1, both for well above their last private valuations.

New unicorns in June

Here are June’s new unicorn companies:

AI labs

• Hangzhou-based raised a $7.4 billion Series A, its first external financing, in a deal led by CEO . The 2-year-old company was valued at $50 billion and is said to be planning to list in as early as Q2 2027.
• is building a new AI architecture based on neuroscience called Cortex AI that promises lower power use. It raised a $500 million Series A from , , and . The less than 1-year-old New York-based company was valued at $2.5 billion.
• London-based , an AI for physical product design in aerospace, defense, energy, automotive and semiconductors, raised a $300 million Series C led by . The 6-year-old company was valued at $2.4 billion.
• , a model developer for robotics trained on gaming videos from its sister company , raised a $320 million Series A led by . The 1-year-old New York-based company was valued at $2.3 billion.
• , an embodied robotics intelligence company, raised a $400 million Series B led by . The 2-year-old San Mateo, California-based company with researchers from and was valued at $2 billion.
• Shanghai-based , a  robotics intelligence company, raised a $220 million seed round led by and . The less than 1-year-old company founded by an researcher was valued at $2 billion.
• , a builder of world models to simulate the real world impacting robotics, science, healthcare and defense, raised a $310 million Series B led by . The 2-year-old Menlo Park, California-based company was valued at $1.5 billion.
• Bengaluru-based , an Indian sovereign AI developer, raised a $234 million Series B first close led by . The 3-year-old company was valued at $1.5 billion.
• , an AI lab seeking to automate AI research for scientific use cases, raised a $200 million seed funding led by and . The less than 1-year-old San Francisco-based company was valued at $1 billion.
• Hangzhou-based , a 3D model developer used in gaming, entertainment and product design, raised a $200 million Series A led by . The 3-year-old company was valued at $1 billion.

Robotics

• Germany-based , a physical AI company building intelligent machines to to work alongside humans, raised a $1.4 billion Series C led by stablecoin issuer among other strategic and growth investors. The 7-year-old company, with $1 billion in its order pipeline and strategic deployments, was said to be valued at $7 billion.
• Shenzhen-based , a builder of humanoid robots, raised a $148 million Series B led by . The 3-year-old company was valued at $1.5 billion.
• Guangdong-based , a humanoid robotics company, raised a $147 million Series B. The 5-year-old company, which projects 1,000 shipments in 2026, was valued at $1.5 billion.
• , a builder of industrial arm robotics for manufacturing that said its technology learns through demonstration, raised a $200 million Series C led by and . The 9-year-old New York-based company was valued at $1 billion.

AI infrastructure

• , which pivoted from crypto mining to data center build out for AI, raised a $400 million funding led by , and . The 2-year-old Coral Gables, Florida-based company was valued at $2.4 billion. The company has filed for a direct listing on .
• Las Vegas-based , a cloud operator that offers customer AMD chips, raised a $350 million Series B led by and . The 2-year-old company was valued at $1.6 billion.
• Beijing-based , an inference solution offering customers API access to hundreds of models, raised a $296 million Series B. The 2-year-old company was valued at $1.2 billion.
• , an AI developer cloud to train, fine-tune and deploy AI, raised a $100 million Series A led by . The 4-year-old New Jersey-based company valued at $1 billion has 1 million developers using the platform.

Defense

• , a precision weapons company enabling existing weaponry to defend against unmanned drones, raised a $200 million Series B led by . The 4-year-old Austin-based company was valued at $2.2 billion.
• , a manufacturer of unmanned aerospace and defense systems, raised a $300 million Series C led by and . The 3-year-old Huntington Beach, California-based company was valued at $1.8 billion.
• , a cyber intelligence company building products for the U.S. military, raised a $100 million Series B led by , and . The 1-year-old Arlington, Virginia-based company was valued at $1 billion.

Proptech

• Montreal-based , a mortgage financing platform, raised a $217 million Series E round. The 8-year-old company was valued at $1.1 billion.
• India-based ,  a property brokerage that also owns a mortgage marketplace, a property management platform, and a home interior brand raised a $95 million private equity and debt financing led by . The 13-year-old company was valued at $1 billion.

Data analytics

• Belgium-based , an intelligence platform for global physical trade, raised a $1 billion secondary market funding led by . The 12-year-old company was valued at $3.7 billion.

Biotechnology

• , a biotech company focused on reverse cellular aging, raised a $435 million Series C led by . The 4-year-old San Francisco-based company with plans for clinical trials next year for human liver cells, was valued at $3.1 billion.

Materials

• Cambridge, U.K.-based  , building a network of labs using AI for new material discovery, raised a $450 million funding led by and . The 2-year-old company was valued at $2.6 billion.

Cryptocurrency

• , a blockchain and smart contract solution for global financial institutions, raised a $355 million Series F led by . The 12-year-old New York-based company was valued at $2 billion.

Image generation

• Beijing-based , a video generation company, raised a $300 million Series B led by , and . The 3-year-old company was valued at $2 billion and says it has built a creator community of more than 30 million users. As of May 2026 the company has $300 million in annual recurring revenue.

Financial services

• Saudi Arabia-based , a mobile banking company, raised a $400 million Series A. The 6-year-old company was valued at $1.6 billion.

Semiconductor

• Rotterdam-based , a 3D metrology inspection tool for semiconductor manufacturing, raised a $380 million Series D led by . The 10-year-old company was valued at $1.6 billion.

Aerospace

• Beijing-based , a space infrastructure and satellite company, raised a $207 million Series D. The 10-year-old company was valued at $1.5 billion.

E-commerce

• , an e-commerce provider that supports customer interactions post purchase, raised an $81 million Series B led by . The 4-year-old Utah-based company supporting 4,100 brands and 1,750 merchants was valued at $1.3 billion.

AI healthcare

• , an AI agent built for a patient’s healthcare journey and used by healthcare providers, raised a $120 million Series C led by . The 3-year-old San Francisco-based company was valued at $1.2 billion.

Transportation

• Munich-based , a car subscription platform operating in Germany and partnering with 25 brands, raised a $113 million Series D led by . The 7-year-old company was valued at $1.1 billion.

Related ������Ƶ unicorn lists:

• (1,822)
• (637)
• (213)
• (190)
• (118)
• (102)
• (935)
• (539)
• (248)
• (39)
• (488)

Related reading:

• ������Ƶ Data: Global Startup Investment Hit Record $510B In H1 2026 As AI Boom Accelerates Funding And Exits
• AI Services And Robotics Lead Diverse Crop Of 29 New May Unicorns As SpaceX, Anthropic And OpenAI Line Up Blockbuster Exits

Methodology

The ������Ƶ ������Ƶ is a curated list that includes private unicorn companies with post-money valuations of $1 billion or more and is based on ������Ƶ 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. ������Ƶ 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 ������Ƶ long after the event was announced, foreign currency transactions are converted at the historic spot price.

Illustration:

Within the region, U.K. startups gained significant share in Q2, raising more than $10 billion. That marked the third-largest funding quarter for the U.K. on record, and came in at less than $500 million below its peak quarter in 2021.

������Ƶ startup M&A activity also picked up in Q1 and continued that momentum in Q2, even as public-market exits stayed subdued.

Table of contents

• Large rounds drive gains
• H1 2026 up 50%
• UK momentum builds
• By stage
• Looking ahead
• Methodology
• Glossary of funding terms

Large rounds drive gains

Four companies raised venture fundings of a billion dollars or more last quarter, accounting for 25% of all startup investment in the region in Q2, ������Ƶ data shows.

Those billion-dollar-plus rounds were raised by an AI-centric group: -owned AI drug developer , which was spun out of ; green steel production manufacturer ; , which is developing robots for home and industrial applications; and , an AI lab founded by former DeepMind researchers.

However, most of the growth in funding year over year and quarter over quarter was driven by rounds of $100 million and over. The majority of funding — 65% — went to a group of 42 companies that raised rounds of $100 million-plus. Sectors that stood out for these companies include  biotech, quantum, financial services, AI labs, aerospace, semiconductor, robotics and energy.

H1 2026 up 50%

Funding to Europe-based startups in H1 was up 50% year over year to total $42 billion, ������Ƶ data shows. Still, the region’s startup investment for the first half of the year remained well below the 2021 H1 peak, when VC funding in Europe totaled $60 billion.

It’s also drastically lower than the $392 billion raised in North America’s record-setting H1, with that region’s funding up 158% year over year.

Europe’s funding deal count subsided last quarter, but mostly at the seed stage. Late-stage rounds were up a bit, while early-stage deals dipped slightly year over year. (It’s worth noting, seed stage rounds are often added to the ������Ƶ data set after the close of the quarter, so those numbers will increase over time.)

UK momentum builds

The United Kingdom widened its venture-funding lead last quarter, as startups based in the country raised $10.4 billion — not far from the peak in 2021 at $10.8 billion.

The region’s No. 2 startup market, Germany, trailed with $3.2 billion raised by its startups in Q2, and France followed in third place with $2.4 billion. Sweden was Europe’s fourth-largest startup market last quarter, with its companies raising $2 billion.

������Ƶ data shows funding to Europe’s AI-focused companies reached more than $10 billion in Q2 — the largest quarterly amount so far — but slightly below the Q1 percentage, when those companies raised more than half of the region’s startup investment.

By stage

Europe’s late-stage funding totaled $12.1 billion in Q2, up 90% year over year. Large Series C and D rounds were raised by Germany-based robotics developer Neura Robotics; Netherlands-based , which makes inspection tools for semiconductor manufacturing; U.K.-based quantum computing startup ; and Germany-based satellite launcher .

Early-stage funding reached $8.6 billion across 250-plus Europe-based startups last quarter, ������Ƶ data shows. Large Series A and Series B rounds were raised by London-based Isomorphic Labs, London-based AI self-learning lab , Germany-based fusion energy company , London-based semiconductor developer , and London-based quantum processor provider .

������Ƶ seed funding totaled $3.2 billion last quarter, with a billion dollars of that raised by just one company: Ineffable Intelligence.

Other large seed rounds were raised by , a London-based AI lab for science; Italy-based autonomous driving technology producer ; and Stockholm-based defense tech company .

M&A increase

While IPO activity for ������Ƶ startups was muted, M&A showed strong momentum following increased activity in Q1. A total of 154 Europe-based, venture-backed companies were acquired for a cumulative $11.5 billion or more in Q2, ������Ƶ data shows. That includes three companies acquired for more than $1 billion each in biotech, industrial AI and micromobility.

Looking ahead

������Ƶ startup investment has now steadily increased since the fourth quarter of 2024, with increased momentum in the just-ended quarter, driven by larger rounds of $100 million and over. The region’s startup ecosystem shows particular strength in deep tech and financial services as well as the formation of new AI labs, and M&A activity has fueled liquidity for the next batch of startups.

Now the question remains: Will it be enough to keep Europe competitive with the frontrunners, the U.S. and China?

Related ������Ƶ queries:

Related reading:

• ������Ƶ Data: Global Startup Investment Hit Record $510B In H1 2026 As AI Boom Accelerates Funding And Exits
• North American Startup Funding Shattered Records In First Half Of 2026, Driven By AI

Methodology

The data contained in this report comes directly from ������Ƶ, and is based on reported data. Data is as of July 6, 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. ������Ƶ 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 ������Ƶ 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. ������Ƶ 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. ������Ƶ 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.)

The data also illustrates how capital is concentrating into a handful of companies at unprecedented scale while IPOs and acquisitions have returned in force, with the second quarter notching one of the strongest periods for venture-backed exits in years.

and alone accounted for $217 billion — 43% of all startup funding in H1 — underscoring how a small handful of frontier AI companies is reshaping venture markets. At the same time, other massive funding deals across industries including AI infrastructure, defense, robotics and healthcare — combined with record IPO and M&A activity — signal that the AI investment boom has grown well beyond a select few top foundation labs.

Q2 2026 was the second-largest quarter on record for global venture investment, following on the heels of the largest quarter in Q1. All told, investors poured $205 billion into more than 5,000 startups in Q2, following $305 billion invested in Q1.

Table of contents

• Exits peak in Q2
• Capital concentration
• Beyond Anthropic
• Late-stage funding
• Early-stage funding
• Seed
• Record exits market returns
• A new venture cycle takes shape
• Methodology
• Glossary of funding terms

Exits peak in Q2

Record funding defined the first half of the year as the period topped the previous half-year peak, reached in H2 2021, of $375 billion.

The second quarter also marked a turning point for liquidity. IPOs and startup acquisitions accelerated alongside venture investment, producing the strongest exit market since the 2021 boom, ������Ƶ data shows.

The largest IPO ever for a venture-backed company and the largest startup acquisition ever both took place in Q2. Both deals involved , as it went public at a value of $1.77 trillion, raising $75 billion, and less than a week later confirmed its intent to acquire , maker of the AI coding tool Cursor, for $60 billion.

Capital concentration

Despite the resurgence in exits, the defining characteristic of venture investment in the AI boom remains its extraordinary concentration in terms of companies, industries and geography.

Close to a third of Q2 global venture funding went to just one company: Anthropic. The now-leading foundation lab raised $65 billion last quarter and became the most valuable private company on The ������Ƶ ������Ƶ as SpaceX exited and Anthropic surpassed OpenAI on the leaderboard.

The U.S. also again dominated global funding. Two-thirds of startup capital in Q2 went to U.S.-based companies, down from 83% in Q1 and in line with proportions in Q2 2025.

And more than 70% of global startup capital in Q2 was invested in AI-focused companies, up from just under 50% a year earlier.

Beyond Anthropic

Anthropic accounted for a significant share of global funding, but the quarter also produced a sizable cohort of other megarounds. A total of 16 companies raised billion-dollar rounds in the quarter, totaling  $108.6 billion, or 53% of second-quarter funding, ������Ƶ data shows.

Seven of those billion-dollar fundraisers are frontier labs. They include the China-based foundation companies , and , U.K.-based , and the U.S.-based labs and .

Eight of the companies in the cohort in Q2 are U.S.-based, while Asia and Europe each have four.

Alongside foundation model companies, large funding rounds were raised by startups working on defense, AI infrastructure, robotics and healthcare.

Late-stage funding

Late-stage venture funding totaled $134 billion in Q2, down from Q1 but up 141% from Q2 2025, ������Ƶ data shows.

Early-stage funding

Early-stage funding totaled $589 billion in Q2, up more than 100% from a year earlier. The number of companies raising Series A and B rounds at $100 million have picked up in the past two quarters, with 91 companies on a global basis raising large rounds in Q2.

Seed

Seed investment likewise remained elevated, although the market continued to show a widening gap between a handful of exceptionally large financings and the broader population of traditional seed rounds.

All told, global seed funding totaled $12 billion in Q2, ������Ƶ data shows. Of that, $2.8 billion went to seed rounds of $100 million and over, with $5 billion in seed rounds at $10 million and under.

Record exits market returns

Q2 exit amounts were the highest on record for venture-backed companies for both acquisitions and IPOs, ������Ƶ data shows.

A total of 32 companies went public at values above $1 billion in Q2. After SpaceX, the next two largest listings were inference chipmaker and quantum company .

Twenty-four companies were also acquired at prices at or above $1 billion in Q2, totaling $113 billion in value — the highest quarter on record — per ������Ƶ data.

A new venture cycle takes shape

H1 2026 established a new benchmark for global venture investment, but the record comes with an important caveat: an unprecedented share of capital flowed to just two companies. OpenAI and Anthropic together attracted more than 40% of all venture funding during the first half, highlighting the extent to which the current market is centered on the biggest players in the frontier AI race.

Even so, the broader venture ecosystem is showing signs of strength. Startup funding increased across every investment stage, the public markets have reopened, and billion-dollar financings expanded beyond foundation model developers into adjacent sectors such as AI infrastructure, defense, robotics and healthcare.

Perhaps the biggest shift is the return of liquidity, via both IPOs and M&A. If those trends continue, 2026 may be remembered not only as the year venture funding reached a new high, but as the beginning of a cycle in which record private investment and a functioning exit market reinforce one another.

Related ������Ƶ queries:

Related reading:

• ������Ƶ Data: Q2 Brought The Most Billion-Dollar Startup Exits Since 2021
• Cursor Deal Puts US On Track For Record Startup M&A Year

Methodology

The data contained in this report comes directly from ������Ƶ, and is based on reported data. Data is as of July 1, 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. ������Ƶ 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 ������Ƶ 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. ������Ƶ 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. ������Ƶ 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.)

Illustration: