The Incline Village, Nevada-based company is also acquiring Austin-based agentic AI startup as it looks to automate more of the labor-intensive work involved in investigating financial crime.

led the investment, which includes both primary capital and a secondary tender offer for employees. , , and others also participated. Socure did not disclose the terms of its acquisition of Fravity.

With the latest funding, Socure has raised over $742 million in disclosed funding since its 2012 inception. It was previously valued at $4.5 billion at the time of its Series E round in 2021. The company did not break down how much of its raise was primary and secondary capital.

Rapid growth as fraud surges

The transactions come as Socure says it is seeing both rapid growth in its own business and a sharp rise in increasingly sophisticated fraud. The company is refreshingly open about its financials, telling ������Ƶ News that it ended the second quarter with $364 million in annual recurring revenue, up 63% from a year earlier, and added 95 customers during the quarter, including , , and . It also claims to be growing “profitably.”

Socure uses AI and machine learning to help banks, fintechs and government agencies verify identities so they can “approve real customers instantly while stopping fraud.”

It now has more than 3,000 enterprise customers. They include 19 of the 20 largest U.S. banks, more than 600 fintech companies, major sportsbook and prediction-market operators, and 160 public-sector organizations. Specifically, some of those customers include , , , , and . The company’s revenue model mixes usage- and transaction-based SaaS.

AI creates both an opportunity and a problem

Socure co-founder and CEO said AI is creating both an opportunity and a problem for the business. For example, Socure saw an 8,000% increase in AI-driven fraud across its network last year, according to the company, as generative AI and other tools make it easier to create convincing fake identities and automate attacks.

At the same time, AI could help address one of the more costly parts of fraud prevention: investigating the large number of cases and alerts that automated systems flag for human review.

That is where Fravity comes in.

Automating fraud investigations

Fravity has built an AI-native platform that uses agents to automate fraud, risk and compliance investigations. Its technology will be incorporated into Socure’s RiskOS platform as RiskOS_Agents, initially focusing on watchlist screening and monitoring and know-your-business checks.

Socure and Fravity already share several enterprise customers that use the two products together, according to Socure. Across its existing deployments, Fravity has reduced cost per case by 80%, sped up case resolution fivefold and cut false positives by as much as 70%, the companies say.

The acquisition puts Socure more directly into what identity intelligence company estimates is a $71.1 billion financial crime investigation market. The problem is particularly acute at banks, where 53% spend at least an hour reviewing each alert, and 37% manually review more than 40% of alerts, according to Liminal.

As AI increases the volume and sophistication of fraud, Ayers argues that the identity layer — determining whether people and increasingly AI agents are who or what they claim to be — is becoming more critical to doing business online.

“I believe there are two types of companies that matter in the AI-driven global economy: those that are AI-native, and those that fight the consequences of AI acceleration,” he said in a statement.

Expanding beyond financial services

The investment follows a period of expansion for Socure beyond its financial services roots. In May, the company won a five-year, $163 million federal contract to provide identity-proofing technology for Login.gov. It is also pushing further internationally.

Socure had more than 550 employees as of March 2026, more than 100 more than it had about a year ago, according to Ayers.

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So far this year, more than 500 seed- or venture-backed private companies across the globe have sold to other private, venture-backed companies, per ������Ƶ data. The most prolific acquirers include many of the most famous and valuable unicorns, including , and .

Overall, the pace of dealmaking in 2026 looks relatively flat��1Reported deal counts are down slightly this year from the comparable period, but are likely to even out more over time as some acquisitions, particularly smaller deals, are added to the dataset weeks or months after they close.2 compared to last year. That’s not entirely surprising given that overall market conditions haven’t changed dramatically. The number of tech startup IPOs remains below normal. Hot venture-backed AI companies are still sustaining unheard-of valuations. And the rise of megarounds means favored startup acquirers are flush with cash.

Startups buying startups in recent years

In total, at least 440 funded startups sold to other startups in the first half of this year. The second half is shaping up to be a bit slower, meanwhile, with fewer than 100 deals so far.

For a more expansive chronological view, below we charted startup M&A deal counts by half-year beginning in 2021.

The pace of M&A dealmaking peaked about four years ago and fell afterward, in tandem with a broader dip in startup investment. But activity has picked up over the past couple of years with the rise in AI investment.

Startups that buy a lot of other startups

A few startups have proven particularly acquisitive.

The standout in this category is probably OpenAI, which has acquired eight startups this year, most of them seed- or early-stage companies. To date, the generative AI giant has bought at least 19 companies, per ������Ƶ data.

Anthropic has also been a busy buyer. It’s snapped up at least five startups so far this year, including the $400 million purchase of AI biotech startup .

In the fintech space, meanwhile, has been on an M&A spree. The crypto transactions platform acquired five funded startups focused on cryptocurrency or blockchain between April and July.

Others with multiple funded startup M&A deals this year include AI infrastructure unicorn , security provider , and the legal tech startups and .

No big slowdown in sight

While prediction can be a fool’s game, there’s not much in the immediate set of indicators pointing to a slowdown in startups’ appetite for acquisition. Amid fierce competition for an edge in the AI race, well-funded startups commonly find it’s simply faster to buy another company than try to build out certain technologies themselves.

Same goes for talent. Through acquihire transactions, startups can bring on board not just top-tier individuals but experienced teams with a track record of building impressive things together.

Concentration of capital is another factor driving M&A deals. While overall startup funding has risen this year, it’s increasingly spread across a smaller pool of companies. That leaves one large cohort of startups struggling to raise funding while another has plentiful capital for acquisitions.

Go-to-market expenses also factor into M&A considerations. A startup might produce a compelling offering in-house but find it costly to bring it to market. The process may look more feasible under the wing of a larger, more mature startup.

Bottom line: Given the high number of willing sellers and well-funded buyers, expect the startup-to-startup acquisitions to continue.

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spent much of his childhood in his family’s St. Paul, Minnesota, convenience store, where he packed cigarette cartons and watched his father run a business seven days a week, 365 days a year.

Hussain was the son of a first-generation immigrant who arrived from Karachi, Pakistan, and worked his way from employment at a to owning his own corner store. That experience instilled in Hussain a work ethic that stuck with him. But his father made a clear trade-off with him in high school.

“My dad didn’t want me to necessarily come back to the store,” Hussain recalls. “He’s like, ‘Look, like this is what I did and built. Go use school as a mechanism to leave.’ ”

Ultimately, Hussain went on to form , a New York-based AI startup that automates parts of finance and accounting. Founded in 2023, the company has raised around $90 million, employs about 180 people, and was last valued at $400 million, according to Hussain.

But unlike many tech startup founders, Hussain didn’t study computer science in college. Instead, he earned a humanities degree at , won a Marshall Scholarship to , left academia abruptly to work at , and spent six years learning the operational ropes at early-stage startup before launching Tabs in 2023.

From St. Paul to Oxford

Hussain leveraged a scholarship from the to attend Cornell, where he fell in love with comparative politics and history. Fixated on academia, he graduated and immediately headed to Oxford to pursue a Ph.D. Two months in, reality hit.

“I realized this is a terrible idea,” Hussain admits. “I grew up … way too scrappy packing the cooler to survive through a postdoc and potentially a very structured 10-year career, which seemed very hard and long and not in my control.”

Deciding to reset his trajectory at 23, Hussaini took a chance on management consulting at BCG in the Midwest. Though it provided an intensive crash course in business operations, spreadsheet modeling and corporate processes, the structured corporate hierarchy lacked the agency he had seen in his father’s store.

By 2015, he decided to embed himself directly into tech, taking a massive pay cut to join Latch — then a 10-person seed-stage startup — as its first operations hire.

“Had I tried to do this directly out of Oxford or out of BCG, I think [it] would have been impossible,” Hussain told ������Ƶ News in an interview. “One of the things that often keeps many non-traditional founders out is … the ability to access capital, but also understand the playbook of how to build, how to design around a real problem, and build a team.”

Over six years at Latch, as the company grew to tens of millions in revenue, Hussain picked up a few lessons about building venture-backed companies. He learned to pursue large markets, to surround himself with people whose strengths complement his own, and to build for major shifts in technology.

Humanities vision meets deep tech

In 2023, Hussain applied those principles to start Tabs, an AI platform that automates revenue recognition, billing and collections. From the beginning, the founder knew he had to leverage his strengths. He also knew his weaknesses. Hussain recognized that he brought commercial vision and operational execution, not the ability to write code, to the table. So he partnered with a deeply technical co-founder, , to balance his own background.

“I came from the humanities,” Hussain noted. “Tabs is a deeply technical and complex problem to solve, and so having someone who could augment my vision … was a very important part.”

Investors took notice. Early relationships and the operational credibility Hussain built during his “apprentice” years paid off. Tabs quickly raised a $4 million pre-seed round co-led by and . Since then, the startup has grown to roughly 180 employees, raised about $92 million in total capital, reached a $400 million valuation in its last round, and maintained triple- to quadruple-year-over-year revenue growth.

To Hussain, non-traditional backgrounds in tech are a strategic advantage that fosters the resilience required to survive early-stage uncertainty.

“I think a lot of non-traditional folks … have to embrace a ton of volatility, even ahead of being a founder, to make the sacrifices to learn,” Hussain said. “Sometimes it’s just the non-traditional background that allows you to embrace non-traditional ways of learning that ultimately get you into entrepreneurship.”

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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.

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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)

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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.

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

Startup investors poured capital into a varied lineup of large rounds this week, targeting sectors including physical AI, biotech, cybersecurity, AI infrastructure and fintech. By far the largest financing of the week was a $1.7 billion round for founder ’s physical AI startup, , followed by sizable investments for 3D AI model developer and battery technology company .

1. , $1.7B, physical AI: Atoms, the physical AI startup founded by founder , raised $1.7 billion in a funding round led by . Kalanick touted the Los Angeles-based company’s vision as “about the coming industrial revolution where large industrial economic sectors get completely digitized.”

2. , $400M, AI for 3D: Silicon Valley-based Meshy AI, a startup developing foundation models for AI-powered 3D generation, closed on $400 million in Series B funding at a $1.5 billion valuation. Lead backers include , and , per ������Ƶ data.

3. , $300M, battery technology: Battery technology company Sila secured $300 million in a new round led by and . The Alameda, California, company will use the funding to expand its silicon anode plant in Moses Lake, Washington.

4. , $300M, inference technology: Etched, a co-designer of chips, racks, software and manufacturing methods for use in frontier models, picked up $300 million in Series C funding. led the round, which set a $10 billion pre-money valuation for the San Jose, California-based company.

5. , $180M, fintech: Augustus, a startup aimed at providing financial institutions around the world direct access to dollar accounts, secured $180 million in Series B funding. led the round, which set a $1 billion valuation for the San Francisco-based company.

6. , $160M, defense tech: Cathedral, a startup aimed at expanding U.S. military cyber capabilities, reportedly $160 million with backing from Sequoia Capital and Andreessen Horowitz. The Washington, D.C.-based startup was reportedly founded by a ​team of former DOGE employees.

7. , $130M, biotech: Crystalys Therapeutics, a biotech developing therapies for people living with gout, closed an oversubscribed $130 million Series B round. led the financing for the San Diego-based company.

8. , $120M, healthcare software: San Francisco-based Candid Health, developer of a revenue cycle management platform for the healthcare industry, landed $120 million in Series D funding led by .

9. , $100M, cybersecurity: Glow, a Palo Alto, California-based AI-powered endpoint security startup, launched from stealth and announced it has raised $180 million to date, of which, per ������Ƶ, $100 million comes from its newest financing. Lead backers include Sequoia Capital, , , and .

10. , $75M, cybersecurity: Boston-based Neo Security, a startup working on an agentic software control platform for enterprises, picked up $100 million in a new round led by and Andreessen Horowitz.

Methodology

We tracked the largest announced rounds in the ������Ƶ database that were raised by U.S.-based companies for the period of July 18-24. Although most announced rounds are represented in the database, there could be a small time lag as some rounds are reported late in the week.

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Notably, the quarter also marked the busiest one for General Catalyst since 2021 in terms of investing in rounds of $5 million or above. The firm’s next-busiest fintech investing quarter in rounds of that size was the fourth quarter of 2025, when it participated in 10 raises of $5 million or above.

Overall, fintech startups raised $28.6 billion globally in the first half of 2026, a 22.7% increase from the first half of 2025, but down 17.3% compared to the $34.6 billion raised in the second half of last year. (It’s important to note that H2 2025 marked the strongest six-month funding period for fintech startups since the second half of 2022.)

Over the past year, startup accelerator Y Combinator has routinely ranked as the most active investor in the fintech space. And overall, it was still the most active investor in the second quarter of this year, participating in 41 deals.

But this time, it ranked behind General Catalyst in terms of backing fintech rounds in the $5 million or more category. General Catalyst participated in 12 of those deals, while YC and each invested in 11.

In overall fintech dealmaking, General Catalyst still ranked far behind YC’s 41, with 13 deals. participated in 12, Index Ventures in 11, and in 10.

Top lead investors at $100M or more

For megarounds — those deals of $100 million or more — we once again saw private equity firms topping the list of lead or co-lead investors. , , , and topped that list, according to ������Ƶ data.

The largest rounds in Q2 were raised by a geographically diverse bunch of fintech startups. They include:

• Expense management startup was the fintech sector’s largest recipient of capital in the second quarter, raising a massive $750 million Series F round in June co-led by Ontario Teachers’ Pension Plan, Iconiq Capital and GIC that valued the company at over $50 billion post-money.
• , a London-based cross-border payments and foreign-exchange fintech majority-owned by , was a close second — landing $748 million in a private equity financing led by Centerbridge Partners in April.
• Also in April, Indian consumer lending startup raised $220 million in a Series E round co-led by , and that valued it at more than $1.5 billion.
• Paris-based insurtech landed a $545 million Series G led by Prosus that valued it at $6.2 billion.

Top fintech investors at seed

When it comes to investing in seed rounds, unsurprisingly, Y Combinator again topped the list — by far, with 33 fintech deals. Next up was with seven investments at the seed stage, and then with six.

The investor base shifted when we looked at who led or co-led post-seed rounds in the second quarter. General Catalyst topped that list, with five deals. , , , Index Ventures, and all tied with three investments each.

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Related reading:

• Fintech Funding Surges 23% In H1 2026 As Investors Concentrate Their Bets On AI And Financial Infrastructure

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While financings of a few million haven’t gone away, today most venture capital actually goes to rounds of a billion dollars or more. Moreover, it looks like a rising trend.

So far this year, 60% of global startup funding across stages��1 ��— around $320 billion — went to rounds of $1 billion or more, per ������Ƶ data. Such rounds were instrumental in pushing global funding for the first half of the year to record levels.

The U.S. funding tallies are even more tilted to megadeals this year, with 73% of funding going to billion-dollar-plus rounds. Of the $290 billion invested in these deals, just two rounds for AI leaders and account for more than half the total.

As you can see, the notion of billion-dollar-plus rounds accounted for a minority of funding before this year. The lone exception was the first quarter of 2025, when OpenAI closed a $40 billion financing.

Not just bigger deals, more of them too

Giant rounds aren’t just getting more ginormous. They’re happening with greater frequency too.

So far this year, U.S. startups have closed 23 known rounds of $1 billion or more, per ������Ƶ data. That puts 2026 already on par with 2025, a record-setting year, and we’ve still got about five months left.

Not surprisingly, these megarounds are generally later-stage rounds or corporate financings. Only two of this year’s billion-dollar-plus rounds — and — were seed or early-stage rounds, per ������Ƶ data.

Lessons from the first crop of billion-plus financings

In the history of startups, meanwhile, the billion-dollar-plus venture funding round is a fairly contemporary phenomenon.

The first American example, per ������Ƶ data, was ’s $1.2 billion Series D, in 2014. Over the next three years, a handful of others pulled in 10-figure rounds as well, including , , , , , , , and .

Most of those companies went on to go public and reach valuations that well-exceeded levels set for prior megarounds. SpaceX ($1.6 trillion recent market cap), Uber ($148 billion) and Airbnb ($87 billion) were the standout success stories.

Two of the megafund recipients — Argo AI and WeWork — did not fare so well, while a third, cancer diagnostics provider Grail, has been up and down. Fanatics, meanwhile, remained private and is still thriving.

If these early billion-plus fundings taught investors anything, it was that pouring unusually large sums into well-regarded unicorns can be quite lucrative but is far from a sure bet.

Uncharted territory

In the current funding cycle, it’s not enough to ask whether billion-dollar rounds have potential for high returns. With Anthropic and OpenAI, the question now applies to rounds in the tens of billions or even over $100 billion. As both have already filed confidentially to go public, it may not take us long to find out.

Related ������Ƶ query:

Related reading:

• ������Ƶ Data: Global Startup Investment Hit Record $510B In H1 2026 As AI Boom Accelerates Funding And Exits
• ������Ƶ Data: Q2 Brought The Most Billion-Dollar Startup Exits Since 2021
• The $100M+ Round Is Now Just Your Typical Late-Stage Financing

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