But that鈥檚 often not the case, an analysis of 小蓝视频色情网页版 data shows. This year, a number of larger acquisitions of private companies involved startups that haven鈥檛 disclosed a new investment for more than four years.

Several of these acquisitions are quite recent 鈥� and in some cases, quite large. The standout is 鈥檚 purchase earlier this month of , a platform for catering and workplace meals, for $2.3 billion in cash. The deal comes nearly five years after Boston-based ezCater raised its last reported venture funding round.

That鈥檚 not the only one. A number of companies whose names might feature on a playlist of 2021 boom-era unicorns have sold to acquirers in recent months, including one-time highfliers like , and . In many cases, companies are selling at valuations which, while not puny, are still far below their former peaks.

Who鈥檚 getting acquired

To illustrate the extent to which these aging startups are finding acquirers, we used 小蓝视频色情网页版 data to put together a list of 15 deals involving well-funded companies that haven鈥檛 raised equity funding for four or more years.

Post-peak runway

One big issue for older and middle-aged startups is that valuations hit a cyclical peak in 2021 and early 2022. Many companies that raised during that time had difficulty attracting fresh capital or were reluctant to close new rounds at reduced valuations. Even with the more recent AI boom, little went to this cohort.

Moreover, since the 2021 boom-era rounds were quite large, funded startups commonly had the option to cut operating costs and extend their runways with existing capital. As a result, quite a few companies that haven鈥檛 raised rounds in years are still chugging along, managing to survive and even grow without more venture funding.

EzCater is a case in point. In the year prior to its acquisition, the business generated more than $2.5 billion in gross bookings. It had an annual growth rate in the high teens, with average order sizes over $400.

That said, even that revenue and growth rate didn鈥檛 secure ezCater much of an acquisition premium from its last funding round. At $2.3 billion, Uber鈥檚 purchase price is 53% above the $1.5 billion pre-money valuation the catering startup secured in its last funding round in late 2021.

Acquisitions below peak venture valuation

In many cases, even good-sized acquisitions of well-funded startups are occurring at valuations far below former peaks.

Take Miro, a provider of online collaboration tools that agreed to sell to last month in a deal valued around $1.36 billion. That鈥檚 a huge step down from early 2022, when San Francisco-based Miro closed its last round at a $17.5 billion post-money valuation.

Or consider Bending Spoons鈥� prior purchase of data and workflow platform , for $1.28 billion in August. That鈥檚 barely over one-tenth the $11 billion valuation Airtable secured in its December 2021 Series F.

Fashion startup is another that lost its shimmer after securing a 2020 valuation in the hundreds of millions. It sold to fast-fashion leader this spring for $100 million.

In the health and wellness sector, meanwhile, Headspace also saw its valuation plunge. The meditation and mental health app sold to in a deal reportedly valued around $300 million. That鈥檚 well below its peak post-money valuation of around $2.6 billion.

A good thing?

While startup investors aren鈥檛 celebrating acquisitions made far under peak private valuations, they鈥檙e not the worst outcome. And for startups themselves, they鈥檙e also far from a catastrophic scenario.

Of course, every unicorn investor hopes for high-multiple returns. But for startups that go years without funding, the market seems to be telling us that鈥檚 not likely in the cards.

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Acquisitions are reshaping the technology industry. Venture-backed AI companies acquired 195 AI startups this year through late September, already exceeding the total for all of 2025, 小蓝视频色情网页版 data shows.

For investors and founders, such acquisitions can represent major financial milestones. For employees holding equity compensation, a transaction can also change personal financial plans they had expected to follow for years.

A client whose employer was acquired in an all-cash transaction described to me the atmosphere inside the company during the weeks that followed: Employees repeatedly discussed the deal in office corridors, trying to understand what it meant for their equity awards, their jobs and their future. She compared the confusion to the atmosphere surrounding a major reorganization or a round of layoffs.

The transaction offered the prospect of substantial financial gains. Yet employees were struggling to establish what those gains would mean for them individually.

One acquisition, different outcomes

Employees at the same company can emerge from an acquisition with remarkably different financial outcomes.

Some own vested shares. Others hold restricted stock units, stock options or performance-based awards. Their rights depend on grant agreements, vesting conditions and transaction terms. Even two employees holding RSUs may face different payment schedules or employment requirements.

Depending on the agreements, outstanding awards may be settled in cash, accelerated, converted into replacement awards, or remain subject to future conditions. One employee might receive a substantial payment when the transaction closes. Another may have much of the expected value tied to continued employment.

The announced acquisition price provides a reference point. It rarely tells an individual employee everything they need to know about the money they will receive.

This helps explain the conversations my client described. Colleagues may compare the value of their equity without realizing that their contractual rights differ.

Wealth and employment uncertainty

Technology employees with substantial equity compensation often depend on their employer in several ways.

Their salaries, bonuses, career opportunities and investment portfolios may all be linked to the same company.

An all-cash acquisition can reduce their exposure to its share price once vested shares are converted into cash. Other forms of dependence may continue.

The acquiring company may reorganize teams, change responsibilities or introduce retention arrangements. Employees whose unvested awards remain conditional on employment may face difficult choices about staying.

Someone expecting a large payment can therefore feel financially stronger while becoming less certain about their career.

Before making plans

A major acquisition announcement can change personal ambitions long before the proceeds arrive.

Employees may begin considering early retirement, a new business, a career break or a major family purchase.

Those possibilities are worth exploring. But an announced acquisition may still require regulatory approvals and other closing conditions. The headline value of an equity award may differ substantially from the cash ultimately available to its holder.

Taxes, exercise costs where applicable, outstanding liabilities and payment schedules can all affect the outcome. So can the employee’s financial position outside the company.

A substantial payment might make a career change affordable without providing enough capital to fund permanent retirement. Existing pension savings, household spending and future earning capacity remain important.

In my work with technology executives, I have seen expectations about new wealth reshape personal plans before the underlying numbers have been established.

Employees facing a cash acquisition can begin with three questions: What rights do my specific awards provide? When will the proceeds actually become available? And what choices will the resulting after-tax capital support?

The answers may differ considerably among colleagues.

An exit without an exit decision

Founders who sell their companies often participate directly in negotiating the transaction. Employees holding equity compensation generally have much less influence over its timing.

They may have intended to retain their shares for years, sell gradually or remain employed until additional awards vested. A corporate acquisition can replace those plans with a timetable established by the transaction.

For some employees, the result will be substantial financial flexibility. For others, a significant part of their expected compensation may remain connected to future employment.

The period between announcement and closing can be especially difficult because the financial opportunity is visible while important details remain unresolved.

My client’s description of the office corridors captured that experience. The company had made a decision about its future. Its employees were left to work out what that decision meant for theirs.

The acquisition determines the terms of a corporate transaction. Each employee still has to establish how much financial freedom it creates.

is co-CEO and managing partner of , which works with technology executives, founders and families on integrated wealth planning, equity compensation and major liquidity events. His background includes more than two decades in the technology industry.

Disclosure: The views expressed are the author’s own. This article is for general informational purposes and does not constitute financial, investment, legal or tax advice. Details of the client experience have been presented without identifying information.

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The partner began his career as a high school math teacher with after studying astrophysics at . He later worked in college access and Yale admissions, and earned graduate degrees in business and education from before joining Reach. As a teacher, he was an early user of , an experience he describes as 鈥済ame-changing.鈥�

His investment firm, Reach Capital, has also evolved. Founded in 2015 after spinning out of , the San Francisco-based firm initially focused on technology for K-12 schools and districts. Its mandate has since expanded to learning, health and work, with investments in companies including ClassDojo, , and .

In August, Reach announced its fifth fund, a $265 million vehicle that brought its assets under management to nearly $1 billion. The firm, which has backed more than 180 companies, plans to invest in approximately 50 additional teams through the new fund, targeting pre-seed, seed and Series A rounds.

小蓝视频色情网页版 News spoke with Kim about how Reach鈥檚 education roots inform its broader strategy, what it saw in AI detection company , and why some of its best investments initially divided its own team. We also discussed how ownership stakes and secondary transactions have shaped the firm鈥檚 approach to returning capital.

This interview has been edited for length and clarity.

小蓝视频色情网页版 News: You started your career as a high school math teacher. How did that shape your view of education technology?

Kim: I taught ninth through 12th grade, mostly Algebra I and geometry. I was very early to ClassDojo. Back then, it was a very simple classroom management tool, and it was game-changing for me. It has since evolved into a sprawling suite, but I already knew technology could move the needle.

Reach began as an education investor. How did the firm鈥檚 focus evolve into learning, health and work?

Kim: Reach started in 2015, and our original focus was exclusively on learning and education technology 鈥� more specifically, technology sold into schools and districts.

Our founding partners were seeing the growth of devices in schools, one-to-one device ratios and broadband penetration. The belief was that you would start to see a proliferation of technology serving students, teachers and administrators and moving the needle on learning outcomes. That is what ended up playing out. Some of our early bets are now household names in edtech, such as , and ClassDojo.

Reach spun out of NewSchools Venture Fund, where three of our four founding partners had started doing for-profit seed investing before 2015. Over time, we branched out from K-12 into higher education, and then into consumer learning.

We also started getting pulled toward healthcare and work. Health and wellbeing affect a learner鈥檚 readiness for the classroom, so we were being pulled toward mental health, behavioral health and developmental health. On the work side, formal learning typically ends in college, but you still need the bridge to a job. Once you鈥檙e on the job, you need to continue learning, especially in the current environment.

A few years ago, we officially put a stake in the ground and said we invest across learning, health and work. The common thread is that these are the most important systems underlying human development and flourishing.

So far, the breakdown has been roughly 50% learning, 25% health and 25% work.

These sectors have different buyers, regulations and business models. What did investing in education teach you that translates to healthcare and work?

Kim: Education is highly regulated, and institutional buying is complex. Many stakeholders must provide input, and decisions often require board-level approval. We were familiar with and comfortable with regulated products and complex go-to-market motions.

Selling to a university or a K-12 district, in terms of the complexity and the need to intersect with regulation and policy, is quite comparable to selling to a health system, hospital or insurance carrier.

Cartwheel is a good example of where our experience gave us an advantage. It provides mental health teletherapy, but the customer is the school district and the care setting is in schools.

While we were relatively new to behavioral health when we made that investment, we were very familiar with selling to school districts and implementing an intervention within a school setting. That gave us an advantage both in winning the investment opportunity and supporting the company afterward.

Reach talks about 鈥渆levating human potential.鈥� What makes an investment fit that mandate?

Kim: We look for products and services that increase access to quality education, quality care or quality earnings, or some combination of those. We really have to see the mechanism for that happening.

It鈥檚 not good enough to be pitched a SaaS or AI product and have the founders say, 鈥淭his will make people more productive at work, and therefore maybe they will earn more or enjoy their jobs more.鈥� That鈥檚 plausible, but it isn鈥檛 a good enough theory of how the product actually increases access to quality earnings.

Several teammates, including myself, are former educators. We care about meaningful, needle-moving impact.

We address access from both the demand side and the supply side. On the demand side, we build products that create delightful, impactful experiences for consumers: , Stepful鈥檚 allied healthcare training, and Replit for what its founder calls 鈥渃itizen developers.鈥�

On the supply side, it鈥檚 helping schools, health systems and companies function more efficiently and effectively. , for example, helps logistics and hospitality companies hire hourly workers better and treat them better. We think about the problem from both sides of the market.

Reach backed GPTZero, which agreed to join . Was that an investment in solving a problem created by AI?

Kim: That wasn鈥檛 actually our investment thesis. In my opinion, they have the best AI detector on the market. But their thesis was that AI use in education should not be banned. It shouldn鈥檛 be punitive or become a cat-and-mouse game between the educator and the learner.

Since all of us as professionals use AI in our jobs, students should learn how to use it responsibly and thoughtfully. It was the first AI detector company I had seen with that positioning, as opposed to helping schools, districts and universities clamp down on AI usage.

That鈥檚 why I liked it. I don鈥檛 see it as a problem for students to use AI for certain purposes, such as brainstorming, organizing thoughts and editing. GPTZero helps educators work with students and teach them how to use AI responsibly.

Do you see other opportunities to build companies around the problems AI creates?

Kim: Yes, most notably in AI governance and evaluations.

Going back to regulated categories, you need to make sure AI is not irresponsibly using personally identifiable information in education or healthcare. Those categories have very strict regulations, and infrastructure companies are emerging to help ensure AI products interact with that data responsibly.

I do think there are opportunities for large, successful, profitable companies to be created in response to the problems AI creates.

What does GPTZero鈥檚 sale tell you about which AI products can become durable standalone companies and which belong within larger platforms?

Kim: I don鈥檛 know whether GPTZero is an example of either. They had been fielding acquisition offers from pretty early on. This particular opportunity arose earlier this year, and there was a compelling synergy story with Superhuman, formerly .

The founders and the board agreed that it made sense to combine the companies. But they could just as easily have remained standalone. There is another AI detection company called that鈥檚 quite good and is still a standalone, venture-backed company.

It鈥檚 not clear to me that this category can鈥檛 exist on its own. We have to be very case-by-case. We don鈥檛 know until we see the trajectory, financial sustainability and evolution of the market, whether it makes sense to explore a strategic acquisition or grow independently and perhaps one day become a publicly traded company.

Reach has backed more than 180 companies. What patterns have you noticed among those that exceeded expectations?

Kim: The reality of venture is that a very small share of investments yields the overwhelming majority of returns. Given the outlier nature of those successes, it鈥檚 hard to identify unifying principles that always predict a successful exit. If we could, we would only make those investments.

But there are a few things we think are somewhat common across our wins. One is a very smart, gritty, genuinely mission-driven founder or founding team, often with a strong personal connection to the problem.

Second is some sort of nonconsensus insight about the market. That often comes from experiencing the problem themselves, sometimes as practitioners in the industry 鈥� a former educator, for example.

Third is a defensible and scalable business model.

The nonconsensus insight is funny because it鈥檚 what makes these companies look weird and maybe uninvestable in the beginning. Even within our team, they鈥檙e often the most polarizing opportunities. You look at the votes, and a bunch of people vote no, but it gets just enough yeses to pass. Then, 10 years later, it鈥檚 one of our best investments.

People lose sight of this in the current environment, but the best opportunities are often the most nonconsensus. Those can be the most creative and interesting founders, and you can get in at reasonable valuations early and help them become consensus bets.

Reach says its first two funds have returned investors鈥� capital. What produced those returns?

Kim: We鈥檙e no exception to the power-law distribution in venture. Our first fund has been returned 2.2x by literally two investments. Our second fund has been returned 1.2x by one investment. These are cash distributions, by the way.

Especially in the second fund, there鈥檚 still remaining value, so we鈥檒l see how high that number gets. One fund-returning exit would be great; two or three would be amazing. That鈥檚 what we鈥檙e striving for.

How has that experience changed your approach to ownership and follow-on investing?

Kim: We鈥檝e had some great exits where, given how prominent the company is, you might be surprised that our share of the returns wasn鈥檛 that large. That鈥檚 purely an ownership calculation.

From our first fund to today, we鈥檝e meaningfully increased our initial ownership target. We now try to get as close to 15% ownership upfront as possible.

That means writing slightly bigger checks and reserving relatively less for follow-on investments and more for the initial check. It鈥檚 important for the exit math and distribution math.

What role do secondary transactions play in getting liquidity?

We鈥檝e become very proactive and conscientious about liquidity opportunities. Much of our distributions to investors come from secondary sales 鈥� selling our shares in a subsequent round, before an actual exit.

Whenever there鈥檚 an opportunity, we evaluate it. We consider how long we鈥檝e been in the company, how much we can get out, and how much upside we think remains.

As companies stay private longer, early-stage investors are achieving liquidity much more often through secondary transactions. I like to think we were early to that trend, but it鈥檚 certainly mainstream now.

Sometimes, when we see enough upside, we鈥檒l buy secondary shares. GPTZero was an example: After our Series A investment, we bought secondary shares, and I鈥檓 really glad we did because it worked out well. For us, we sell more often, but occasionally we buy.

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A better model could arrive tomorrow, but replacing the first assistant would require changing how the company operates. That is where I believe an important AI moat is developing: inside customer workflows.

Recent acquisitions and partnerships illustrate three implications for founders, investors and boards.

Workflow access creates strategic value

鈥檚 agreement to acquire for approximately $22.6 billion in equity value gives it software used to design, manufacture and service physical products, placing it inside customer decisions throughout a product鈥檚 lifecycle.

Meanwhile, the – partnership illustrates a similar logic: Combining frontier AI with established chip-design tools and expertise, supported by licensing and revenue sharing.

My reading is that these transactions highlight the strategic value of owning the environment in which AI performs useful work. Companies already embedded in complex industries bring customer relationships, domain expertise and trusted processes that AI developers need to commercialize their technology.

For founders, that suggests building a position inside a specific customer workflow. For established businesses, it creates an opportunity to turn existing workflow access into bargaining power.

Completing recurring work builds defensibility

reported that its agents handle more than 15 million conversations weekly, including refunds, insurance renewals and healthcare bookings, alongside announcing an employee tender at a $22 billion valuation. The operational adoption is particularly relevant to the moat discussion. Once a product connects to internal systems, follows permissions, handles exceptions and reliably completes tasks, replacing it involves migration, testing, retraining and operational risk.

This can strengthen retention and create opportunities to serve additional workflows. Integration alone offers limited protection, however. Customers need to depend on the product and measure the value it delivers. Investors should therefore examine how much recurring work flows through the platform, which processes rely on it, and what switching would actually require.

Companies can acquire their way into workflows

鈥檚 of combines an AI assistant and enterprise search technology with established workflow automation. At completion, Moveworks had 5.5 million employee users, with approximately 250 customers already using both companies鈥� technologies.

The strategic opportunity is to connect employee requests directly to the systems and processes that resolve them across IT, HR and other functions. This creates a clear corp dev agenda: identify the customer workflows the company wants to enter, understand the barriers, and assess whether an acquisition or partnership can accelerate entry.

An attractive target may bring technology, customer relationships, integrations and an established role in daily operations.

Diligence should test how deeply customers depend on the product, whether those relationships will survive the transaction and whether the combined offering can deliver measurable improvements. As AI capabilities improve, acquiring the right position inside customer operations could become a powerful route to durable growth.

is a strategic adviser to tech companies, investors, CEOs and boards, specializing in strategy, growth and M&A. He is a guest contributor to 小蓝视频色情网页版 News and a university lecturer on strategy, finance and entrepreneurship. Learn more at and connect with him on .

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European startup funding reached $25 billion last quarter, well above the $14 billion invested in Q3 2025 and up slightly from the $24 billion invested in Q2. Quarterly funding was up 77% year over year, per 小蓝视频色情网页版 data.

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

Table of contents

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

Billion-dollar fundings

Four European companies raised billion-dollar-plus fundings, representing close to 40% of the region鈥檚 startup capital raised last quarter.

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

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

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

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

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

Venture expands beyond the UK

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

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

Late-stage rise

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

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

Early stage

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

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

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

Seed

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

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

Looking forward

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

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

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

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Methodology

The data contained in this report comes directly from 小蓝视频色情网页版, and is based on reported data. Data is as of Oct. 5, 2026.

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

Please note that all funding values are given in U.S. dollars unless otherwise noted. 小蓝视频色情网页版 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 小蓝视频色情网页版 long after the event was announced, foreign currency transactions are converted at the historic spot price.

Glossary of funding terms

Seed and angel consists of seed, pre-seed and angel rounds. 小蓝视频色情网页版 also includes venture rounds of unknown series, equity crowdfunding and convertible notes at $3 million (USD or as-converted USD equivalent) or less.

Early-stage consists of Series A and Series B rounds, as well as other round types. 小蓝视频色情网页版 includes venture rounds of unknown series, corporate venture and other rounds above $3 million, and those less than or equal to $15 million.

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

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

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In total, investors poured $92 billion into seed- through growth-stage rounds for U.S. and Canadian startups in the third quarter, per 小蓝视频色情网页版 data. That鈥檚 a 35% decline from the prior quarter but up 50% from year-ago levels.

Deal volume held fairly steady, with late-stage and early-stage round counts remaining close to prior quarter levels.

Artificial intelligence remained the prevailing theme for startup investors. Per 小蓝视频色情网页版 data, roughly two-thirds of total funding this past quarter went to AI-focused companies. Of that, a big chunk went to large rounds for , and .

Overall, however, investment fell across most stages. Early-stage dealmaking posted a particularly sharp decline from a multiyear peak the prior quarter, while later-stage funding was also down.

As for exits, quarter-over-quarter IPO comps were always going to be challenging, given that Q2 featured 鈥檚 record-setting market entry. Even compared to a typical quarter, however, the IPO market was fairly sluggish in Q3, with a few biotech, energy and consumer-facing offerings, but no blockbuster tech debuts. M&A activity was more exciting, topped by 鈥檚 September acquisition of .

Below, we look over the quarterly numbers in more detail, breaking out investment by stage, charting AI funding, and analyzing exit activity.

Table of contents

• Late-stage and technology growth funding
• Early stage
• Seed
• AI
• Exits
• M&A
• IPOs
• Slower, but not a slowdown
• Methodology
• Glossary of funding terms

Late-stage and technology growth funding

We鈥檒l start with late stage, since that鈥檚 where most startup funding went.

For Q3, investors poured $66.45 billion into late- and growth-stage deals, per 小蓝视频色情网页版 data. That鈥檚 up about a third from year-ago levels, but down sharply from Q1 and Q2 of this year, when OpenAI and Anthropic pulled in financings of $110 billion and $65 billion, respectively.

For the just-ended quarter, the largest late-stage and growth rounds went to Databricks ($5 billion), AI infrastructure unicorn Crusoe ($3.9 billion), ($3 billion), and AI coding startup ($2 billion). Overall, more than a dozen startups attracted late-stage or growth rounds of $1 billion or more, per 小蓝视频色情网页版 data.

Early stage

Early-stage investment also held up at historically high levels in Q3, albeit down from prior highs.

Overall, investors put $20.6 billion into early-stage rounds in the just-ended quarter, per 小蓝视频色情网页版 data. That was down sequentially from the prior quarter but still well above prior year levels.

A few exceptionally big rounds pushed up the latest quarterly tally. The largest funding recipients included open source AI company 鈥檚 $1.1 billion Series A, nuclear startup 鈥� $660 million Series B, and chip hardware and software developer 鈥檚 $500 million Series A.

Seed

Seed-stage dealmaking was also quite busy in Q3.

At least $5 billion went to seed, angel and pre-seed rounds in the just-ended quarter, per preliminary 小蓝视频色情网页版 data. That鈥檚 a bit below both the prior quarter and year-ago comps. However, we expect the Q3 tally to rise a bit over time as seed deals commonly get added to the dataset a few weeks or months after they close.

The AI space delivered some particularly large seed rounds. Of these, standouts were physical AI startups , which picked up $300 million, and . which secured $90 million.

AI

The percentage of funding going to AI-focused startups also held up at high levels in Q3, per 小蓝视频色情网页版 data.

A total of $61 billion went to AI-focused rounds, per 小蓝视频色情网页版 data. While that鈥檚 down sharply from the prior two quarters, it鈥檚 still one of the highest tallies on record.

Exits

As for exits, Q3 featured a number of large M&A deals, particularly in the AI space. The IPO market was a bit quieter, with much of the market鈥檚 attention looking forward to enormous offerings from foundational AI pioneers in coming months.

M&A

Acquisition activity was fairly robust in Q3, boosted by a handful of large AI-related purchases. Of these, the biggest was Nvidia鈥檚 acquisition of open model development platform Hugging Face for $12.93 billion.

The next-biggest M&A deal was 鈥檚 purchase last week of , an AI model and research lab led by AI pioneer , in a stock deal valued around $8.2 billion. Not far behind, in third place, was 鈥檚 acquisition of , a startup that routes prompts through different AI models, in an August transaction reportedly valued around $7.5 billion.

In total, there were 11 North American startup acquisitions at reported prices of $1 billion or more in Q3, per 小蓝视频色情网页版 data. We list them below.

IPOs

Overall, it was a light quarter for IPO activity. Per 小蓝视频色情网页版 data, 17 venture-backed North American companies went public on major U.S. and Canadian exchanges in Q3, per 小蓝视频色情网页版 data, collectively raising just under $4 billion.

Three biotech companies raised the largest sums in their IPOs: , focused on mRNA; , a developer of cardiovascular therapies; and , which is working on antibody therapeutics.

Other venture-backed companies that carried out good-sized debuts included , a developer of advanced nuclear fuel, and , the scooter and e-bike rental platform.

Notably, however, it was the IPOs that didn鈥檛 happen this quarter that attracted the most attention. By this, we are referring of course to Anthropic, which is reportedly eyeing a聽 public list as early as November, and OpenAI, which filed confidentially for an IPO in June and is expected to make its debut in 2027.

Slower, but not a slowdown

Overall, Q3 seems to exemplify the notion that funding activity can decline from peak levels without a clear indication that the investment climate has turned bearish.

Yes, giant funding rounds contracted. However, the maturation of the two most valuable startups, OpenAI and Anthropic, into even more valuable pre-IPO companies, is the kind of thing venture investors want to see.

Moreover, big rounds are still closing at a brisk clip. The AI space is still regularly minting fresh unicorns. And acquirers are snapping up leading names at historically high valuations.

Could things go south from here? Sure. But for now, the AI-driven momentum continues.

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Related reading:

• North American Startup Funding Shattered Records In First Half Of 2026, Driven By AI

Methodology

The data contained in this report comes directly from 小蓝视频色情网页版, and is based on reported data. Data is as of Oct. 2, 2026.

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

Please note that all funding values are given in U.S. dollars unless otherwise noted. 小蓝视频色情网页版 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 小蓝视频色情网页版 long after the event was announced, foreign currency transactions are converted at the historic spot price.

Glossary of funding terms

Seed and angel consists of seed, pre-seed and angel rounds. 小蓝视频色情网页版 also includes venture rounds of unknown series, equity crowdfunding and convertible notes at $3 million (USD or as-converted USD equivalent) or less.

Early-stage consists of Series A and Series B rounds, as well as other round types. 小蓝视频色情网页版 includes venture rounds of unknown series, corporate venture and other rounds above $3 million, and those less than or equal to $15 million.

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

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

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The buying spree has pushed acquisitions of AI startups by other venture-backed AI companies to 195 through Sept. 29, according to 小蓝视频色情网页版 data 鈥� 14% more than in all of 2025. Yet the number of buyers grew just 2%, indicating that increasingly active acquirers are driving much of the increase.

Those deals point to a new phase of competition in the AI sector: Well-funded startups are using M&A to broaden their products and reach new customers faster than they could by building everything themselves. In legal tech, for example, acquisitions are bringing research, regulatory monitoring and litigation tools into broader platforms.

CFO described that calculus in a earlier this year explaining the company鈥檚 back-to-back purchases of multiple startups: 鈥淢&A is explicitly part of how we accelerate what we’re building. The question we always ask is: does this deal get us somewhere faster than we’d get there ourselves?鈥�

Repeat buyers step up dealmaking

Some of the AI acquirers have returned to the dealmaking table more than once in recent years, 小蓝视频色情网页版 data shows. Across the three-year period, 67 repeat buyers accounted for about 42% of all transactions tracked. OpenAI was by far the most active, with 20 AI-related acquisitions, including 10 this year.

This year鈥檚 other repeat buyers include and legal AI startup Legora, which have each announced five acquisitions, followed by legal AI startup with four. Customer-service AI provider and coding company have each made three acquisitions this year, while announced two. Many of the buyers are vertical AI startups acquiring companies in their respective areas.

Several of this year鈥檚 transactions are sizable.鈥檚 reported $1.65 billion acquisition of was the largest with a recorded price, followed by鈥檚 $1 billion acquisition of identity security startup.

Anthropic鈥檚 acquisition of, which develops AI for pharmaceutical research, was valued at $400 million. 翱辫别苍础滨鈥檚 $300 million acquisition of, a Los Altos, California, startup that uses customized AI in camera hardware for computational photography, and鈥檚 acquisition of, valued at up to $285 million, rounded out the five largest deals recorded in the dataset through Sept. 29.

Overall, prices were disclosed for only 12 of the 195 deals, making it difficult to gauge how much AI startups are spending on acquisitions overall.

Dealmaking has clearly picked up as more AI companies turn to acquisitions 鈥� and, in some cases, make them a recurring part of their growth strategy. 1

鈥淚t鈥檚 all about speed in the AI world,” according to , partner at , which has backed numerous AI startups including Anthropic and Legora. “It鈥檚 faster to acquire a team or product than build it yourself. If you鈥檙e not growing 10x, you鈥檙e not interesting to growth investors, which leaves a gap in the funding market for AI startups that need a home. High valuations have also given AI startups cheap currency to use their stock to get these deals done with minimal dilution.”

What AI startups are buying 鈥� and why

The specific companies being acquired offer insight into what AI startups hope to gain from their stepped-up M&A activity.

翱辫别苍础滨鈥檚 purchases have ranged widely, from healthcare data and scientific-writing software to developer infrastructure, security tools and specialized talent. The San Francisco-based company announced three acquisitions in January alone, setting the tone for a busy M&A year.

In January, it acquired:

• , which built AI software to help executive coaches automate leadership assessment reports.
• , an AI-powered health app that aims to unify scattered medical records from hospitals, labs, wearables and consumers.
• , which provides LaTeX editing, error detection and team collaboration.

In February, OpenAI participated in an deal involving open-source AI agent and its creator, . Then in March, it announced plans to , a creator of open-source tools for software developers. It also snapped up , an open-source tool for testing AI applications.

In June, OpenAI agreed to buy , formerly known as Gitpod, which provides secure cloud environments where developers 鈥� and, increasingly, AI agents 鈥� can continue working after a user鈥檚 laptop is closed. In August, it also picked up , an AI presentation company that converts prompts, notes and documents into editable presentations.

Vertical AI roll-ups

Well-funded vertical AI startups, particularly in legal tech, have also been busy this year buying smaller companies, an analysis of 小蓝视频色情网页版 data shows.

San Francisco-based Harvey鈥檚 AI-related purchases have focused on filling gaps around its core platform. developed tools for creating product demos, videos and guides, while built software that helps companies connect customer data and applications with AI systems.

New York-based developed software that helps asset managers capture insights from previous investments and apply them to new deals. That acquisition helped expand Harvey鈥檚 presence in the asset management space. Its fourth known acquisition this year, announced Sept. 9, was , which builds open-source tools for testing, monitoring and managing AI agents.

, COO of Harvey, told 小蓝视频色情网页版 News that the company鈥檚 M&A strategy is rooted in finding 鈥渢echnical talent with high ownership and deep experience in legal tech or an adjacent space to legal.鈥�

She pointed to Benchmark as an example. The co-founders, she said, 鈥渒now the asset management space cold, and their name was dropped so many times in customer conversations that it was a natural fit for them to join our team.鈥�

Burke further described the startup鈥檚 M&A strategy as 鈥渟elective but aggressive.鈥�

鈥淲e hold an incredibly high bar for talent and when we identify an additive company, we move quickly and will continue to do so this year and beyond,鈥� she added.

Legora has pursued an even broader legal-tech rollup. The Stockholm-based company鈥檚 five announced acquisitions this year include:

• , a nine-person Canadian startup whose agents work inside Word and Outlook;
• , a Stockholm company building AI-native legal research tools;
• , an Australian regulatory-intelligence platform that monitors more than 100 areas of law for changes;
• , whose AI agents analyze documents and data for commercial real estate companies; and
• London-based , which helps litigation teams extract facts from large collections of documents, identify inconsistencies and build case timelines.

Sierra鈥檚 acquisitions reflect an effort to expand both geographically and beyond conventional customer-service automation. In March, it acquired Tokyo-based enterprise AI startup as part of its expansion in Japan, followed by Paris-based , which helps businesses automate operational work with AI. In July, Sierra bought , a 14-month-old startup developing 鈥渓ong-horizon鈥� agents.

For acquisition targets, joining a larger platform can offer a shortcut to scale even when their own businesses are growing rapidly. TakeOff founder wrote in a July that his company was posting a 鈥渘ear 8-figure run rate鈥� with a team of just three people. 鈥淭he advice for an AI startup growing at our pace is to hire out a sales team, raise again, and keep going,鈥� he wrote. 鈥淲e had capital, customers, and great traction,鈥� but the Sierra acquisition offered an opportunity to 鈥渁ccelerate our shared vision and simultaneously build it at a grander scale.鈥�

The surge in M&A activity is driven by both a wider pool of buyers and increasingly active serial acquirers. At this pace, we should expect even more in the months and years ahead.

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• Data: OpenAI Has Already Done Nearly As Many M&A Deals In 2026 As It Did All of Last Year
• Startups Are Still Acquiring Startups, Led By Ultra-High-Valuation Unicorns
• Your AI Strategy May Be Destroying Your Exit Value

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Funding to private companies has skyrocketed this year, totaling $679 billion in venture funding globally in Q1 through Q3 2026, per 小蓝视频色情网页版 data. That is the highest amount in the first three quarters of any given year.

While global venture funding in Q3 was down 25% quarter over quarter from the $212 billion raised in Q2, it was up 53% year over year from the $104 billion raised in Q3 2025.

聽Table of Contents

• Billion-dollar fundings
• US and sectors
• Late-stage funding
• Early-stage funding
• Seed
• Exits: IPOs and M&A
• Robust market
• Methodology
• Glossary of funding terms

Billion-dollar fundings

A notable shift in 2026 has been the number of startups that have raised billion-dollar-plus rounds. An all-time record of 27 companies raised such sizable rounds in Q3 2026, an increase from the previous record, set in Q2, of 16 companies and Q1鈥檚 total of 14 companies.

Around a third of all global venture capital raised in Q3 went to those 27 companies. In the two prior quarters, billion-dollar raises pushed total funding to well above historical norms.

No single company raised funding in the tens of billions last quarter. However, eight companies raised funding rounds of $3 billion or more, with frontier labs and data centers leading by company counts for the biggest raises. Of these eight companies, five were founded within the past four years.

The largest funding deals went to and , which each raised $5 billion. Close behind, , , , , and each raised more than $3 billion.

US and sectors

U.S.-based companies continued to raise the dominant share of venture capital with $91 billion invested in American startups, or around 57% of the global total in Q3. The San Francisco Bay Area alone accounted for 24% of global venture investment in the quarter.

AI-driven startups across the stack raised $102 billion, or 64% of global venture capital, down from the two previous quarters, but still 14 percentage points above Q3 2025 global funding.

The realm of physical AI has attracted significant capital in 2026. That continued in Q3 with the aerospace, robotics, data centers, semiconductor and energy sectors each raising $10 billion or more in the quarter.

Late-stage funding

Late-stage venture funding totaled $105 billion in Q3, down 23% from Q2 but up 73% from Q3 2025, 小蓝视频色情网页版 data shows. Funding rounds of $100 million and above accounted for close to 90% of late-stage financings.

Early-stage funding

Early-stage funding totaled $40.6 billion in Q3, up by 25% from a year earlier. The number of companies raising jumbo sized rounds at $100 million and over, represented 50% of early-stage financings.

Seed

Global seed funding totaled $13 billion in Q3, 小蓝视频色情网页版 data shows. Of that, $2.6 billion went to seed rounds of $100 million and over, around 20% of seed financings.

Exits: IPOs and M&A

Q3 was a fairly strong quarter for exits. China dominated on the IPO front for the largest exits聽 with semiconductor and robotics listings surging on their first day of trading.

• China-based , developer of DRAM chips, was the largest IPO in Q3, raising聽 $8.6 billion at an $85.5 billion value. Its stock surged more than 500%聽 on its debut to become the most valuable listed company in the local market.
• The second-largest was Singapore-based fast fashion company listing at a $26.3 billion valuation, well below its 2022 valuation peak of $100 billion. Shein was the one exception that closed its first day around its opening price, after falling by about 10%;
• Shanghai-based AI chipmaker , a competitor to , went public in September, raising $912 million at a valuation of $25.5 billion.
• Milan-based , acquirer of and , raised $1.6 billion on its debut at a value of $18.4 billion.
• Hangzhou-based humanoid robotics company went public raising $905 million debuting at a valuation of $9 billion.

U.S.-based companies, meanwhile, dominated the largest M&A deals.

Semiconductor companies were the largest acquirers in Q3. bid to acquire New York-based open-source AI platform for $12.9 billion. Semiconductor giant announced its intent to acquire 鈥檚 , a San Francisco-based builder of models for physical intelligence, for $8.2 billion. The third-largest acquisition was payments provider 鈥檚 acquisition of New York-based AI model router for $7.5 billion.

Robust market

Over the past few quarters, larger checks across funding stages have pushed venture investment higher as young AI companies gained traction rapidly. Half of startup capital invested in Q3 went to companies founded since 2022.

Venture funding has also expanded beyond software into physical infrastructure and robotics, reindustrializing economies. And a dynamic seed funding climate for AI-native startups signals continued appetite for the next wave of companies.

Methodology

The data contained in this report comes directly from 小蓝视频色情网页版, and is based on reported data. Data is as of Oct. 2, 2026.

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

Please note that all funding values are given in U.S. dollars unless otherwise noted. 小蓝视频色情网页版 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 小蓝视频色情网页版 long after the event was announced, foreign currency transactions are converted at the historic spot price.

Glossary of funding terms

Seed and angel consists of seed, pre-seed and angel rounds. 小蓝视频色情网页版 also includes venture rounds of unknown series, equity crowdfunding and convertible notes at $3 million (USD or as-converted USD equivalent) or less.

Early-stage consists of Series A and Series B rounds, as well as other round types. 小蓝视频色情网页版 includes venture rounds of unknown series, corporate venture and other rounds above $3 million, and those less than or equal to $15 million.

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

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

Related reading:

• VCs Pour Billions Into Physical AI As The Next Wave Of AI Investing Takes Shape
• Jumbo-Sized Series A Rounds Are On The Rise

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That creates enormous productivity potential, but it also creates a new security problem: Companies now need to protect not only users, devices and applications, but software actors that can take actions on their behalf.

AI agents are becoming a new class of enterprise identity

An agent may access corporate files, query databases, send emails or execute code. Once it has that level of access, it needs permissions, monitoring and governance. Companies will need to know which agent accessed what information, which systems it connected to, and whether the actions it took were authorized.

As enterprises move from experimenting with a few agents to deploying hundreds of them, agent identity will become another important layer of cybersecurity. The challenge is that these identities are not passive. Agents can move between systems, invoke tools and make decisions, which makes controlling them more complex than managing traditional users or service accounts.

The value will sit in specific control points

This market will probably not develop as one broad category called 鈥淎I security.鈥� The real opportunity will be around specific control points.

One company may protect agent identity, another may control the data an agent can access, while others may focus on prompts, MCP servers, plug-ins, traffic or auditability.

We are already seeing activity around these areas. recently acquired Israeli startup which focuses on real-time data classification and policy enforcement. Israeli cybersecurity startup , meanwhile, raised a $27 million Series A led by and focuses on understanding and securing increasingly complex internet traffic, including traffic generated by autonomous systems.

These companies are solving different problems, but together they show how the market may begin to separate into distinct security layers.

These control points are creating a new M&A map

Identity providers may extend identity governance to autonomous agents. Data-security vendors may need to control what information agents can access. Cybersecurity platforms, cloud companies and enterprise software vendors may eventually need agent-security capabilities embedded directly into their products.

For entrepreneurs, this means that 鈥淎I security鈥� may already be too broad a positioning. The more important question is what exactly the company controls.

is a strategic adviser to tech companies, investors, CEOs and boards, specializing in strategy, growth and M&A. He is a guest contributor to 小蓝视频色情网页版 News and a university lecturer on strategy, finance and entrepreneurship. Learn more at and connect with him on .

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One of the strangest things about the current AI cycle is just how fast the math changes for the people building it. You can be a 20-something founder who feels like you are still in the warm-up phase of your career, yet on paper your equity is already life changing. Or a mid-level engineer who went from holding startup options to staring at a substantial personal balance sheet practically overnight.

The gap between life experience and the sudden reality of managing serious wealth is widening as AI-native companies reach major valuations faster and private company liquidity arrives earlier.

A of more than 3,400 founders and senior leaders across 20 countries found that AI-native startups are reaching billion-dollar valuations in about 3.5 years, roughly half the time it took before generative AI. They are doing it with about half the staff.

We have seen an even more compressed version firsthand. We recently advised founders who went from launching their company to a major liquidity event in less than a year.

When the money outpaces the mindset

For decades, tech wealth followed a more predictable script. Significant personal wealth often accumulated alongside a long career. Equity vested over years, responsibilities grew and additional grants often followed. If everything went right, an acquisition or IPO marked a visible transition into a very different financial reality.

Today, that boundary is much less clear. AI capabilities allow companies to grow at a much faster pace.

A young founder can suddenly face questions that used to come much later in life. What are their long-term personal goals? What should the new capital be used for? What does financial independence mean for someone who may still be figuring out what they want their life to look like?

These are not always questions that can be answered overnight.

Compounding this is the fact that one doesn鈥檛 have to wait for an IPO to de-risk. Tender offers and secondary transactions allow founders and employees to turn part of their equity into cash while the company remains private.

Take as an example. While still only 3 years old, the company authorized a $100 million secondary sale for staff at a $6.6 billion valuation. By February 2026, it had at an $11 billion valuation.

For someone inside a company moving at that speed, the sequence can look very different from the traditional startup script. It is a dizzying loop of grants, valuations and a sudden liquidity window. All of this can happen long before an IPO.

Flexibility is the name of the game

A sudden liquidity event can make financial independence a realistic goal. It may make buying a home possible, even while someone is still single or has no idea where they want to live long term. It may allow them to take care of parents or fund another entrepreneurial chapter.

The pace of these cycles can also be contagious. Opportunities seem to be everywhere. At the same time, a founder may still be taking substantial risks with the current venture and have very little idea what life will look like in five years.

When we advise technology executives and founders in this position, we try to leave room for several possible paths while the broader picture is still developing. Some capital may eventually support long-term family security. Some may need to remain available for opportunities or life changes that do not exist today.

A future business endeavour, a career change, a relocation to another country, or other less conventional ideas can change the picture again. Some of these moves can be made today, but others need time to develop.

A company may compress 10 years of growth into three, but people cannot compress 10 years of life into three. Ignoring that gap is where real risk can build.

Valuations and liquidity can move incredibly fast. Decisions about family wellbeing, security, career and the future still move at a human pace. Your financial architecture needs to respect the difference.

is co-CEO of , where he works with founders, senior technology executives and families on wealth strategy, liquidity events and long-term financial planning. Before moving into wealth planning, he spent many years in the technology industry and writes about the intersection of technology, equity and personal wealth.

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