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 ĀÜĄņŹÓʵ 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 flatĢż1Reported 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. Thatā€™s not entirely surprising given that overall market conditions havenā€™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 ĀÜĄņŹÓʵ data.

Anthropic has also been a busy buyer. Itā€™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, thereā€™s not much in the immediate set of indicators pointing to a slowdown in startupsā€™ appetite for acquisition. Amid fierce competition for an edge in the AI race, well-funded startups commonly find itā€™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, itā€™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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Related reading:

• Why More Startups Are Buying Other Startups In 2025
• Anthropic Nears $1T Valuation And Leapfrogs OpenAI On ĀÜĄņŹÓʵ With Massive Funding Round
• The Rise And Rise Of Billion-Dollar-Plus Rounds

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On the ĀÜĄņŹÓʵ ĀÜĄņŹÓʵ, 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 ĀÜĄņŹÓʵ data finds that most of the funding these companies raised came in 2026: a whopping 75% of all funding ā€” $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 yearā€™s newly minted unicorns can turn rapid capital formation and lofty valuations into durable, category-defining businesses.

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This is a weekly feature that runs down the weekā€™s top 10 announced funding rounds in the U.S. Check out last weekā€™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. Letā€™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 ĀÜĄņŹÓʵ 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 Angelesā€™ 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. Lovableā€™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 ĀÜĄņŹÓʵ 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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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 didnā€™t yet have a startup ecosystem ā€”Ģżthere 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 LatAmā€™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.

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

Fabiola ²Ļ³Ü¾±²Ō³ś²¹Ć±“Ē²õ: 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 ā€” that many of the structural problems could be solved with tech.

and , Monasheesā€™ co-founders, were crazy enough to believe this could happen, so thatā€™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 donā€™t have funding, you donā€™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. Thatā€™s when Monashees decided to expand across Latin America and back these teams. Thatā€™s when we led ā€™s seed round, one of the flagship companies of Latin America.

The third wave, which is what weā€™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.

Weā€™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. Weā€™re also generalists. Weā€™re not sector-specific, weā€™re mostly sector-agnostic.

I see this trend when I talk to a lot of ĀÜĄņŹÓʵ 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 itā€™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?

²Ļ³Ü¾±²Ō³ś²¹Ć±“Ē²õ: I think initially it was mostly founders. Now, itā€™s a little bit of both; theyā€™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 youā€™re not here, itā€™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. Itā€™s highly dense and concentrated. You have to be here to absorb the tools and understand what other people are doing.

I also think itā€™s super important because founders realize that Silicon Valley is the champions league. In Latin America, you do have great talent, but you donā€™t know what great looks like if youā€™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 donā€™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 itā€™s very expensive.

I think it’s more about coming here, learning and bringing back the best practices. Thatā€™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.

Thatā€™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. AndrĆ©s [Campero] has a Ph.D. from in AI. Heā€™s one of the disciples of , who is a very renowned researcher. The rationale for having AndrĆ©s, who is Mexican, on the team is to help us connect with the research diaspora here in San Francisco. Itā€™s very different to talk about business than it is to talk to researchers.

This is important because most researchers from Latin America donā€™t stay in Latin America. They come to the U.S. and work at the different universities here. Itā€™s important for us to be connected to where most of the innovation is happening. AndrĆ©s 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?

²Ļ³Ü¾±²Ō³ś²¹Ć±“Ē²õ: Some of the companies weā€™re seeing start in LatAm and then expand to the U.S.

We have a portfolio company called . Itā€™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 itā€™s a U.S. company now.

Most of its revenue comes from the U.S. I think examples like that ā€” companies born in LatAm that expand globally ā€” 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 weā€™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?

²Ļ³Ü¾±²Ō³ś²¹Ć±“Ē²õ: It depends on the stage theyā€™re at. Later-stage companies ā€” think Series C or Series D ā€” tend to have most of their technology teams in Brazil, Argentina or elsewhere in LatAm.

Another example is . Itā€™s headquartered in Salt Lake City, but most of its technology team is in Brazil, in a smaller city called JoĆ£o 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.

Weā€™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?

²Ļ³Ü¾±²Ō³ś²¹Ć±“Ē²õ: Iā€™ve shared a couple. One is Tractian, the preventive-maintenance software company. The company has been growing. Itā€™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. Itā€™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 youā€™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. Itā€™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 . Itā€™s an accelerator, so itā€™s similar in some ways to what weā€™re doing with Google. Shiva is trying to capture this new wave of entrepreneurs who might not have pursued entrepreneurship if Shiva and AI didnā€™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 itā€™s a super-interesting and very different investment. It speaks to how weā€™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 . Itā€™s an HR platform. Itā€™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. Itā€™s one of the flagships of Fund IX. Itā€™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. Itā€™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 youā€™re a multinational company ā€” think about ā€” 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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Among lead investors, topped the ranks last month, while was by far the busiest backer by deal count. The highest-spending investors for the period, meanwhile, appear to be and .

For more detail, below we ranked active investors for July by several metrics. These include most prolific venture dealmakers, most active lead backers, biggest spenders and highest-volume seed investors.

Active lead investors

Weā€™ll start with active lead investors for the month, which, as usual these days, featured a heavily AI-centric lineup of deals.

Khosla Ventures ranked as the most active lead investor in rounds of $5 million or more, with eight deals in July. The largest were a $300 million Series A for quantum computing startup and a $120 million Series C for AI-enabled legal tech provider .

took the No. 2 slot, with six lead deals, followed by , with five. Below, we charted the top eight lead investors for the month by deal count.

Busiest venture investors

The ranks looked quite different when we widened the category to include both lead and non-lead investments in rounds of $5 million or more.

By this metric, repeat frontrunner Y Combinator once again took first place, participating in at least 19 such rounds. The storied accelerator typically takes a non-lead stake in follow-on rounds for startups it incubated.

Insight Partners and Andreessen Horowitz were next on the list, with 10 deals each, followed by Khosla and , with nine each. For a bigger-picture view, below we ranked the top 18 busiest venture investors for July.

Highest spending investors

When we focus on investors who led the most expensive assortment of startup financings last month, the lineup shifts once again.

For July, Coatue ranked as the apparent highest-spendingĢż1 lead investor, backing a $10 billion financing for ā€™ rocket company, . (It should be noted though, that Blue Origin, founded in 2000, is probably too old to be considered a startup, although it is still a private company.)

Nvidia also stepped up, backing a $5 billion financing for foundational AI startup . Index Ventures and Andreessen Horowitz ranked high as well, each leading or co-leading rounds collectively valued above $2 billion.

Below, we rank 18 of the highest-spending lead investors for the month.

Seed dealmakers

Seed dealmakers were a bit more challenging to rank for July, in part because thereā€™s often a time delay before smaller deals enter the dataset. One thing that is apparent is that Y Combinator was the most prolific investor at this stage, while other ā€œusual suspects,ā€ like and , also ranked high.

Related reading:

• A Record 14 Billion-Dollar Rounds In July Pushed Venture’s Historic Run Higher

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That was the intent of our latest ĀÜĄņŹÓʵ News data dive into seed-stage trends. For this installment, we focused on mid-sized rounds of between $5 million and $10 million, analyzing around 800 global seed financings that closed this year.Ģż

Why this range? In a startup investment climate characterized by the ascendance of megarounds, the idea was to focus on rounds more representative of the classic seed deal: a risky bet on unproven founders, technologies or business models.

Using this methodology we identified multiple popular investment themes and zeroed in on five. The first ā€” cybersecurity ā€” we tackled in a separate piece. Here we delve into the other four: proptech, cancer therapeutics, space tech and robotics.

No. 1: Proptech

Real estate is the worldā€™s most valuable asset class, providing startups a huge and varied addressable market. By one estimate a few years ago, real estate accounted for a staggering two-thirds of global net worth.

Given the size of the space, actual venture investment tied to real estate and construction looks comparatively meager. Last year, per ĀÜĄņŹÓʵ analysis, proptech startup investment totaled just over $10 billion, far below peaks hit several years ago.

Seed investors seem to believe thereā€™s a good case for startup driven growth ahead. In particular, theyā€™re funding a lot of rounds in the $5 million to $10 million range for companies looking to add efficiencies to the planning and building process, streamline rental operations, reduce building power consumption, and more.

To illustrate, below we put together a sample set of 15 companies that closed seed rounds in our target range this year:

A few standouts include , an AI-powered home management system, , a developer of software to support real estate decarbonization, and , an AI-enabled construction supply chain platform.Ģż

No. 2: Cancer treatments

Startup founders donā€™t need persuasive superpowers to convince investors that cancer is a sufficiently serious area to address. Today, itā€™s that 39% of Americans will be diagnosed with cancer at some point in their lives. Cancer also ranks as the second leading , behind heart disease.Ģż

Seed-stage companies arenā€™t expected to bring down numbers in the near term, but as they progress, itā€™s increasingly plausible. Thatā€™s the apparent mindset for investors at this stage, whoā€™ve backed a good-sized number of rounds in the $5 million to $10 million range this year for developers of cancer therapeutics and diagnostics, charted below:

Three California startups secured $10 million, the largest financing in our sample set. They include: , which is working on AI-driven discovery of undetected cancer targets, , a developer of targeted therapies for solid tumors, and , which is focused on cancer diagnostics.

No. 3: Space and satellite tech

This yearā€™s most attention-getting event in space tech finance was obviously the IPO of sector pioneer . But while that debut may have dominated headlines, quite a few smaller, earlier, lower-profile deals were also getting done.

Per ĀÜĄņŹÓʵ data, space tech was a popular area for seed financings in the $5 million to $10 million range. To illustrate, below we put together a sample set of nine such companies that raised rounds this year:

The largest fundraiser in our target range was , which is focused on developing reusable satellites. Next was , focused, as its name implies, on in-space propulsion systems, followed by , developer of an ML-native operations platform for satellite fleets.

No. 4: Robotics

Robotics is a perennial favorite in our seed-funding data dives, including the last one, focused on AI. This time, the sector made the ranking again, thanks to a bevy of intriguing seed-stage companies that met our parameters.

Turns out, you can jumpstart some highly ambitious ventures on a $5 million to $10 million seed round. To illustrate, below we aggregated a sample of 18 funded this year:

Robotics was also the most geographically dispersed sector in our lineup, with startups hailing from Asia, North America, Europe and Australia. A few that stood out include , a developer of what it calls ā€œintimacy robots,ā€ , a maker of autonomous underwater robots, and , focused on robots for greenhouse harvesting.

Big picture: Midsized seed rounds for outsized ambitions

Overall, seed funding trends reviewed above may tell us more about the kinds of companies investors are willing to bet on than about the sectors attracting interest, which are already well-established.

Clearly, startup investors still believe that small, modestly funded teams with grand missions remain a worthwhile and viable wager. Thatā€™s particularly encouraging these days, when the venture and seed financings we most commonly hear about tend to be the largest ones.

Thatā€™s not to diss large rounds. Startups that are led by prominent serial entrepreneurs or have established traction hold obvious appeal, even at pricier terms. But for those of us who enjoy rooting for the underdog, itā€™s encouraging to see lower-profile companies with outsized ambitions are still in the game.

Related ĀÜĄņŹÓʵ lists:Ģż

Related reading:

• AI Seed Investors Flock To CybersecurityĢż
• In Charts: Seed Deals Keep Getting Bigger As Odds Of Reaching Series A Fall DramaticallyĢż
• AI Seed Trends: More Multimedia, Backend Automation, Agentic Security, And Yes, Robots

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Before that, Larco had spent nearly eight years as a partner at (NEA), one of the world’s largest venture capital firms.Ģż

There, she served on the firm’s investment committee and led investments across enterprise software, developer tools, and consumer technology, including , , , , and . She also served as a board observer at leading up to its 2021 IPO.Ģż

Known for her sharp product intuition and hands-on operational experience, Larco focuses heavily on helping founders evaluate market dynamics, navigate product-market fit and scale resilient teams.

Before transitioning to venture capital, she built a career as a product leader and founder. After earning a degree in computer science with honors from the , she began her career at working on and , before leading core product teams at companies like and . She also founded an app development startup that she successfully ran and sold before joining NEA.

ĀÜĄņŹÓʵ News recently sat down with Larco to discuss how changing founder preferences and the (SVB) collapse drove her to launch a specialized pre-seed and seed fund designed to make early-stage founders a top priority.Ģż

Among other topics, we also discussed how she evaluates startups based on founder potential rather than initial ideas, looking for teams that leverage AI to make products dramatically faster, cheaper, or easier to use while avoiding rigid, single-model wrappers.

This interview has been edited for clarity and brevity.

ĀÜĄņŹÓʵ News: You were at New Enterprise Associates for nearly a decade before branching out on your own. What led you to start your own firm? Was there a specific gap in the market, or was there a premise you felt couldn’t necessarily be fulfilled at a fund that size?Ģż

Larco: There were a lot of things. At a multi-billion-dollar fund, writing $2 million checks is never going to be a top priority. They invest across all stages, but when you have to deploy between $3 billion and $6 billion depending on how you look at it, itā€™s impossible to do that $2 million at a time with standard team sizes.

Even if you still write those checks, founders have gotten wiser to what it feels like when they are a top priority versus when they aren’t. One founder put it to me this way: ā€œI want my investor at every round to feel like the check size hurt ā€“ that it’s a big percentage of their fund ā€“ because thatā€™s how I know Iā€™m going to be a top priority when push comes to shove.ā€

So, for a pre-seed round, they want a pre-seed fund where the check size hurts. For a seed round, they want a seed fund where the check size hurts. For a Series A, they want a mid-sized fund where the check size hurts.

That frank conversation put a lot into perspective. Founder preferences have shifted over the past few years. Emerging funds over the last three to four years are winning very competitive deals, securing lead slots against more established, bigger firms. This was virtually unheard of before.

How has that happened?

A side, unintended consequence of the SVB collapse was this change in founder preference. When SVB was going under, every single founder called everyone on their cap table saying, ā€œI can’t make payroll on Wednesday. Can you help me?ā€

Every VC was getting dozens to hundreds of calls. Depending on portfolio size, you can’t help everybody or be on the phone with every single company. Everyone had to prioritize. If firms scraped together money to help cover payroll, they couldn’t cover everyone across the entire portfolio. Very quickly, founders got to see where they sat on the priority list.

That’s interesting. As I cover rounds lately, Iā€™ve noticed the lead investors aren’t as often the big mega-funds.

Not at pre-seed or seed.

Even Series A. You’re seeing less of it happening.

Part of it is that fund sizes got really big, so they are writing bigger checks, which inevitably leads to more calculated ROI risk and moving to later stages. Part of it is that founders want to be a top priority, and they saw what happens in a crisis.

Founders are on WhatsApp channels, hacker houses, and communities, so one bad story spreads faster than ever. It used to be just repeat founders who wanted specialized, focused firms at the earliest stage for signaling risk and other reasons. Now, even first-time founders hear those stories and want a specialized investor.

When customer preferences change in any market, you realize there’s an opportunity. We asked ourselves: ā€œCan we capitalize on this shift? If you were to build something from the ground up targeting this specific ICP, what would you build?ā€

We did what we tell our founders to do: a listening tour. We interviewed people in our ICP and asked: What do you wish you had? What works, what doesn’t, what taglines are you skeptical of, and what is tangibly helpful? We doubled down on what we could provide well and cut out things people assume are best practices that founders don’t actually value.

We think of Premise as a startup, and our product happens to be a fund, so it still has to be something people want.

Do you invest strictly at those very early stages, or across other stages?

Strictly pre-seed and seed. Check sizes range from $500,000 to $3 million.

Itā€™s noisy out there. How are you able to cut through that noise to identify real potential versus people riding the AI bandwagon? As a journalist, I struggle with that, so I imagine investors do, too.

We spend a lot of time with founders before backing them. During diligence, we talk one to three times a day for three to five days, alongside extensive reference and back-channel checks. Because of that, most of our investments are in cities where we have strong networks, like SF, New York, and Atlanta.

We try to get a deep sense of who the person is, what motivates them, and what key attributes they possess. Mercedes and I looked across all the best founders we saw at our previous firms and identified seven core attributes. There isn’t one single persona; founders have different strengths and weaknesses. We look for founders who are world-class in at least two of those seven attributes. In our investment memos, we justify those choices with anecdotes and reference feedback. Nobody is the best at all seven ā€“ some attributes even contradict each other.

At the pre-seed and seed stages, whatever idea you pitch ā€“ while we want it to be a good idea because it shows your ability to plan and generate ideas ā€“ the likelihood that it’s what the company looks like in five to ten years is very slim. A lot of it is gauging the potential of the person to find the right market and product fit to build an iconic company.

It is tough, but it’s not that different from the crypto, Web3, or early AI waves. Tailwinds always attract fair-weather founders. The core tactics to figure out who really wants to build something interesting, who has unique insight, and who is tenacious enough to endure the ups and downs haven’t changed in the last decade.

I’ve seen you discuss AI as a concierge service, shifting from “do-it-yourself” tools to “do-it-for-me” agents. You’ve also mentioned that an AI agent shouldn’t just be a wrapper; it needs to significantly re-architect the cost structure. When looking at a seed-stage deck today, what stands out as evidence that a team actually knows how to fundamentally change that cost structure?

Those can actually be two separate things. If a traditional wedding planning concierge service costs $20,000, and you offer it for $1,000, you’ve blown the cost structure out of the water ā€” even if you’re just a wrapper using $100 in API credits. You can be a wrapper, pay for APIs, and still charge a fraction of traditional costs because the legacy price anchor is so high.

What I look for in any company to be competitive is whether it is faster, cheaper, or easier than existing options. A 10% discount isn’t enough, but at 50% off, people will switch. If a tool reduces a weekly five-hour administrative task to five minutes, sign me up. The bar now is enabling people to do things they couldn’t do before or lacked the confidence to do. For instance, I can build a cap table in Excel, but it takes me forever. If a tool makes that effortless, I’m in.

So ideally, a startup delivers on at least two of those three pillars: faster, cheaper, or easier.

I’m not against wrappers, but founders must understand the underlying mechanics. If you scale and the wrapper gets too expensive, or the model degrades, you need to know how to split tasks across open-source, closed, Google, or other models to deliver the best product at the best price.

Technical founders obsessively optimize models for specific features across their product. Less technical founders often use a single model for everything, which doesn’t guarantee the best price or performance. My hesitation with wrappers isn’t that a team launched quickly; it’s when they don’t know how to continue innovating because they’re wedded to a single model.

The counter-argument to my own point is (AWS). When AWS came out, critics said, ā€œAnyone can start a company over a weekend on AWS; it’s not defensible, there’s no moat, you don’t own servers.ā€Ģż

Yet many great companies were built on it. Itā€™s the same argument. People said the same things about the cloud and mobile waves ā€“ that mobile was a toy and no one would buy a $1,000 phone or pay for subscriptions. Looking back, those criticisms sound funny.

You mentioned you look for seven distinct founder attributes, and that a founder needs to be world-class in at least two or three. Without giving away the whole secret sauce, what is one attribute on that list that would surprise people?

The one that catches people off guard is what we call ā€œurgently dissatisfied.ā€ These founders can come across as disagreeable: they’re more focused on the goal than on making people feel good, and their standards can be genuinely difficult to work around.Ģż

But the people who’ve worked with them tend to say the same thing: that the founder pushed me to accomplish things I didn’t think were possible. This shouldnā€™t be confused with ego. It’s about managing hustler, relentless energy and pointing it at the right problems. The best founders I’ve backed have this quality. They have a high bar for themselves and their teams ā€“ as in everything should have been done yesterday, and they should have acted accordingly.

On the flip side, given how fast the tech landscape is shifting right now, is there an attribute that used to be a ‘must-have’ for a Series A founder five years ago that you now consider a nice-to-have at the seed stage?

The attributes themselves are pretty universal truths about what makes a great founder. What’s changed is the intensity and pace at which they have to show up. Five years ago, shipping an exceptional product, not just features, every six to twelve months was the bar. Now it’s every three to four months.Ģż

So being a decisive execution machine still matters enormously, but what we’re evaluating is whether a founder can operate at this new compressed pace without sacrificing quality. That’s a harder thing to assess early, but it’s become one of the most important signals.

Right now, a huge portion of the VC ecosystem has completely retreated from consumer tech to chase B2B enterprise AI. Are you still actively looking at consumer behavior change as an investor? Do you think the rest of the market is miscalculating the size of the consumer AI market, and if so, why?

I think the retreat is short-sighted. Consumer software has historically produced some of the most important companies ever built, and it doesn’t make sense to vacate that entirely because the sector has been in a lull the past few years.Ģż

The first principles of what makes a disruptive consumer company are exciting again because consumer behavior is rapidly changing with AI. We price in that risk. Fintech is another space where I’ve seen a meaningful pullback, and we’re still active there for the same reason. If everyone is running from a category, that’s usually worth paying attention to in case new tailwinds emerge.

You spent years as a product leader at places like and . Weā€™re hearing a lot of talk about how AI will automate the tedious parts of product management ā€“ writing tickets, reviewing specs, tracking bugs. If AI absorbs the execution workload of a PM, what does a top product leader actually do day-to-day in 2026?

The job of a PM has always been consumer empathy: understanding what someone is trying to accomplish and why, and then making sure the product actually gets them there.Ģż

AI only changes the artifacts you produce. A few years ago, you were writing specs. Now the best PMs I talk to are writing evals to define what ā€œgreatā€ looks like for the agents they’re building and testing whether the agents actually deliver it.Ģż

Someone somewhere still has to care deeply about the end user, ask the hard questions about what success means, and hold the bar. That’s still a human job.Ģż

I love the analogy that AI wrappers are just the new AWS. But with AWS, the ā€œmoatā€ eventually became workflow stickiness and data accumulation. In a world where technical founders are constantly swapping models to optimize cost and performance, what does a ā€œmoatā€ actually look like for an early-stage company? If it’s not the underlying model, then what is it?Ģż

I think itā€™s still workflows and data accumulation. I donā€™t think the moats changed much. The real question is how you retain your customers when competitors can clone you in three days. There are small non-durable moats you can lean on before you build out the data/workflows/network effects/integrations/etc moats.Ģż

You made an interesting distinction between how technical and non-technical founders approach model selection. Given that, are you leaning heavily toward funding purely technical, AI-native architectures right now, or can a world-class product-and-distribution founder still win you over if they hire the right engineering talent?Ģż

Never say never, but I am heavily biased towards a founder or founding team that has exceptional AI talent. I find that these folks enjoy being at the cutting edge, staying up to speed on the latest breakthroughs, and donā€™t mind blowing up their roadmap to move fast on a new functionality that enables them to build better products for their customers.Ģż

You talked about AI shifting from ‘Do It Yourself’ to ‘Do It For Me,’ like giving everyone a concierge wedding planner or a financial analyst. When an agent moves from just giving advice to actually executing transactions and making decisions on behalf of a user, what is the biggest hurdle you see startups face? Is it a trust problem with the user, or is it an execution infrastructure problem?

Few people want ā€œDo it entirely for me, and I have no idea what you did or how you did itā€ right now. Most concierge services do the research, ask you questions to personalize the recommendations, and then filter down the options they present. If you have questions, you can dig into their reasoning, what they ruled out, etc. If you donā€™t like the options, they can go and find a new set. Rarely do wedding planners, travel agents, etc just go off and book everything for you without your input. I think thatā€™s where we are with agents. Itā€™s not just a trust problem, but more that people still want to make the decisions themselves ā€“ just not do all the research.Ģż

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Itā€™s a worry that spilled over into headlines last week, after an agent the open-source AI platform . Turns out rogue AI agents causing mayhem is no longerĢż a hypothetical problem.

Seed investors apparently saw this coming, judging by the plethora of good-sized rounds for companies at the intersection of AI and security. Startups in this cohort have raised $855 million across more than 150 reported seed-stage rounds this year, per ĀÜĄņŹÓʵ data. That puts investment on track for an all-time high.

A large cluster of deals in the $5M to $10M range

Here at ĀÜĄņŹÓʵ News, we took a particular interest in seed rounds in the $5 million to $10 million range, an area where cybersecurity investment was particularly robust.

Why this size range? It started as a broader data dive focused on top themes for mid-sized seed rounds, an often overlooked subset in a startup funding climate dominated by AI megadeals.Ģż

An initial perusal indicated cybersecurity warrants a standalone analysis. We found both a high number and a wide breadth of funded companies in the space, with missions ranging from identifying AI hallucinations to building adversary simulations to verifying agents in finance.

To illustrate, below is a sample list of 14 AI-focused security companies that raised seed financings this year in our target range.

Big seed and early-stage bets too

We also had some large rounds in the mix, indicating investors saw risk-reward compelling enough to write big checks for newly minted startups. Some of the biggest included:

• , a developer of identity intelligence technology for the AI era, secured $60 million in a seed financing this month.
• , a Silicon Valley startup working on an AI-native cybersecurity platform that doesnā€™t depend on the public cloud, raised $45 million in a March seed round.
• , an upstart developing an AI governance and security platform for enterprises, in March with $34 million in a seed round it described as massively oversubscribed.Ģż

When investors place larger bets at seed, thereā€™s usually at least one of two core reasons. The first is that the founder or founding team is impressive enough that backers are willing to invest primarily on the mission and people. The second is that the startup has demonstrated impressive traction with its earliest efforts.

For larger rounds, weā€™re seeing a number of the first category. Cylakeā€™s founder and CEO, for example, is , founder of . JetStream, meanwhile, has drawn veterans of , and other security leaders.Ģż

A solid year for overall security funding

Notably, the strong cybersecurity seed funding environment coincides with solid overall venture investment levels. In the first half of the year, per ĀÜĄņŹÓʵ data, startups in the sector pulled in $10.6 billion in financing across stages, roughly in line with recent prior comps.

That said, seed may be where excitement is greatest. With hundreds of billions flowing into building AI infrastructure and applications in recent quarters, someone will have figure out innovative ways to keep myriad real-life and hypothetical AI security nightmares from coming true.Ģż

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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 firmā€™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. (Itā€™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 YCā€™s 41, with 13 deals. participated in 12, Index Ventures in 11, and in 10.

Top lead investors at $100M or more

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

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

• Expense management startup was the fintech sectorā€™s largest recipient of capital in the second quarter, raising a massive $750 million Series F round in June co-led by Ontario Teachersā€™ 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 ā€” 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 ā€” 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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• Fintech Funding Surges 23% In H1 2026 As Investors Concentrate Their Bets On AI And Financial Infrastructure

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In 2026, conversations about Black founders and venture capital have focused on access to funding. But as AI reshapes startup economics, the bigger challenge is no longer simply getting a first check, it’s raising enough capital at the seed stage to successfully reach Series A.

AI has fundamentally lowered the cost of building software companies. Founders can launch products faster, automate operations and accomplish with five employees what once required teams of 30. Yet while AI has reduced the cost of building a startup, it has not reduced the cost of scaling one. Companies still need resources to acquire customers, hire experienced talent, invest in go-to-market strategies, and generate the revenue and growth metrics institutional investors expect before leading a Series A round.

For Black founders, who continue to receive a disproportionately small share of venture capital, the inability to secure fully funded seed rounds has become one of the greatest barriers to building venture-scale companies.

AI is making seed capital more valuable, not less

One of the biggest misconceptions about AI is that startups simply need less money. In reality, AI has shifted when capital matters most. Because startups can now build products more efficiently, investors are increasingly rewarding founders who demonstrate real traction instead of polished ideas. Seed funding is no longer financing an experiment, it is financing proof.

That means founders need enough capital to move beyond building a product and toward building a business. Today’s Series A investors are looking for recurring revenue, customer retention, capital efficiency and repeatable growth. Those milestones require time, execution and sufficient capital.

The startups that reach them are increasingly those that raised enough capital early to stay focused on customers instead of constantly fundraising.

The numbers tell a stark story

The challenge is particularly acute for Black entrepreneurs. According to ĀÜĄņŹÓʵ data, U.S. startups with a Black founder or co-founder received just $942 million in venture funding in 2025, only 0.32% of all venture capital invested in the nation. That represents one of the lowest funding shares in years and a dramatic decline from 2021, when Black founders raised $5.2 billion during the post-George Floyd investment surge.

While 2026 has shown encouraging signs, with Black-founded startups raising approximately $643 million by late May, the strongest quarter since mid-2022, the improvement was driven largely by a handful of unusually large financings, including a $350 million AI round. Across the broader ecosystem, Black founders remain significantly underrepresented in venture funding.

The issue isn’t simply that too little capital is available. It’s that many Black founders raise partial seed rounds that leave them without enough operating flexibility to achieve the milestones required for institutional Series A financing.

The real gap is between seed and Series A

Historically, venture capital rewarded bold ideas and rapid expansion. Today’s market rewards disciplined execution. Investors expect startups to demonstrate product-market fit, meaningful revenue growth, and efficient operations before committing Series A capital. That has made the journey between seed and Series A longer and more demanding.

Black founders who raise only enough money to survive often find themselves trapped in a cycle of continuous fundraising. Instead of focusing on customers, product development and hiring, they spend valuable months chasing additional capital just to extend their runway.

In an AI-driven market where product cycles move faster than ever, that lost time can determine whether a startup becomes a category leader or gets left behind.

Oversubscribed seed rounds are a competitive advantage

This is why oversubscribed seed rounds are taking on new importance for Black founders. Traditionally, oversubscription was viewed primarily as a signal of investor demand. Today, it is becoming a strategic advantage.

Additional capital gives Black founders flexibility to weather slower fundraising markets, invest aggressively when opportunities emerge, and continue executing without returning to investors every few months. It also allows founders to pursue growth intentionally rather than reactively.

Capital efficiency remains important, but efficiency is most valuable when paired with enough capital to execute.

The AI economy requires longer vision

The venture industry often celebrates AI for making entrepreneurship more accessible. In many ways, that’s true. The barriers to launching a company have never been lower. But lowering the cost of starting a company does not eliminate the capital required to build an enduring one.

Closing the Series A funding gap is therefore not simply about increasing investment in Black founders. It’s about ensuring founders have enough money to reach the milestones that unlock future institutional capital. Thatā€™s how you create more Black unicorns.

For Black founders, the conversation should no longer focus solely on access to capital. It should focus on whether they have enough capital to compete. In the AI economy, the Black-led companies that endure won’t simply be those that build the fastest, they will be the ones with the resources to keep building long enough to win.

and are the co-founders of (Black Ops VC), an early-stage venture capital firm. Norman is a managing partner at Black Ops VC. He is also the CEO of , an AI-powered market research platform used by industry giants such as and thatā€™s designed for the media and entertainment spaces to gather audience feedback on video content, and a partner at , an accelerator that provides intense programming, resources and capital to overlooked founders.

Along with serving as general partner at Black Ops VC, Green is the founder and CEO of , an AI-powered CRM and inventory management platform specifically designed for art galleries, dealers, auction houses and collectors.Ģż

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• Share Of Startup Funding For Black Founders Hits Multiyear Low
• 6 Startup Investors On What It Will Take To Fund More Black Founders
• ā€˜This System Wasnā€™t Built For Meā€™: Black Founders Became Investors To Change Venture Capital

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