has been operating in that market since 2013. The New York-based company operates a marketplace for shares of privately held companies, giving employees and other shareholders a way to sell stock before a company goes public or is acquired.

announced plans to acquire EquityZen in October 2025 and completed the deal in January 2026, bringing the company under the investment bank鈥檚 umbrella.

, who co-founded EquityZen and serves as its chief strategy officer, has had a front-row seat to the secondary market’s evolution. SA国际传媒 News spoke with Haslett about what secondary-market pricing says about today鈥檚 most sought-after startups, why AI companies are commanding premiums while many older startups trade at discounts, what the IPO market looks like beyond its biggest names, and why investors are taking a closer look at hard tech.

The following conversation has been edited for length and clarity.

SA国际传媒 News: The second quarter was one of the strongest venture-backed IPO quarters since 2021, but drove much of that activity. If you remove SpaceX, how open is the IPO market for the typical late-stage startup?

Phil Haslett: Generally, I鈥檇 say it鈥檚 better than it was three or six months ago. If you were a private late-stage technology company, you probably were going to wait until after SpaceX anyway, so that hurdle is gone.

Tech markets are also doing well. The stock market is at an all-time high, and there鈥檚 been a strong recovery in tech stocks overall. I assume that we鈥檙e gearing up for a busier summer than usual.

Another thing to consider is IPO performance beyond SpaceX. Some have had initial enthusiasm followed by a slowdown. has come down a bit. So companies may see it as a good time to go public, while post-IPO performance has been, in a word, 鈥渕eh.鈥�

But within AI, I think we鈥檝e seen that there鈥檚 opportunity up and down the production curve 鈥� from energy for data centers, to the technology inside them, to orchestration of compute, to efficient spending on training and inference. There are a lot of interesting companies along that spectrum, and I think that bodes well for companies in the space that want to go public.

A few companies entered your Top 20, including , , and . Does that reflect a durable shift away from traditional software, or are investors chasing a small group of scarce, high-profile hard-tech companies?

Haslett: I think it reflects a thematic shift. The companies entering that list generally fall into AI infrastructure, space tech and robotics.

If those are industries we think will have generational growth opportunities, the logical conclusion is that each sector will have winners. SpaceX gets people thinking about opportunities in space and space tech, and by extension defense tech.

The same applies to AI infrastructure. If the market is that big, and we鈥檝e seen companies go public over the last year or so, it stands to reason investors will be interested in other companies in that space. I think that鈥檚 more important than simply chasing scarce supply.

These businesses tend to be more capital intensive and may take longer to reach predictable revenue than a traditional SaaS company. How are secondary investors underwriting them?

Haslett: If a company needs more capital, investors have to decide whether the overall opportunity is big enough to justify waiting longer and having the company raise more.

If you have to build a factory or get regulatory approval, that can delay the company鈥檚 ability to increase its valuation or reach an exit. Investors discount that into what they鈥檙e willing to pay.

Secondary investors are making the same calculus as primary venture and growth investors, so you鈥檇 imagine much of that is already baked into headline valuations from primary raises.

What鈥檚 changed is that capital-intensive companies now have more financing options. Five or six years ago, a battery company or new chip manufacturer might have had little choice but to raise equity. In 2026, more credit and asset-based financing options are available.

That matters because if one of these companies underperforms or has a distressed asset sale, creditors and lenders get paid first. Secondary investors have to factor that in, too.

EquityZen says the average transaction occurred at a 38% discount to the last funding round, while many AI transactions traded at premiums. What does that say about how bifurcated the private market has become?

Haslett: I don鈥檛 know if it鈥檚 a mispricing. There are essentially two vintages of private companies right now.

Some companies weren鈥檛 built AI-first and have had to adapt. Many raised during the go-go years of 2021, at very high valuations, and may not have raised since. They鈥檝e had to rethink their strategies, which can slow growth and execution. That gets reflected in the discount.

Then there鈥檚 a new wave of companies, from 2023 and beyond, that were built with an AI-first mentality. They started from a clean slate, may operate more efficiently, and have a cleaner story for the market.

Some of those companies are raising rounds in quick succession at higher valuations. Secondary investors may pay a premium because they believe the company鈥檚 trajectory is clear and the next valuation increase could happen quickly.

is an example from the 2021 cohort. It raised at roughly a $10 billion-plus valuation and just sold for substantially less. It鈥檚 still a good business, but when investors compare 20% growth with newer companies going from zero to hundreds of millions in revenue in just a few years, you can understand why their appetite changes.

We may see more companies from that era sell for less than where they raised in 2021.

Over the past few years, many private companies have conducted secondaries because they weren鈥檛 ready to go public. When should founders consider establishing a company-approved secondary program?

Haslett: Historically, companies started thinking about liquidity programs after they鈥檇 been around five, six, or seven years, largely to reward employees for their patience and provide liquidity to early investors.

Now we鈥檙e seeing younger companies engage in controlled liquidity and tender offers.

One reason is talent retention. There are only so many engineers and data scientists, and companies need to compete for them. Secondary liquidity has become more normalized.

More solutions are available than before. Morgan Stanley, for example, has significantly grown its tender-offer activity as investor interest and available tools have expanded.

There鈥檚 also more investor appetite. Investors are increasingly willing to gain ownership through tender offers or secondary transactions. Five years ago, that was far less common.

Right now, it鈥檚 a very founder- and employee-friendly environment, and investors are willing to support secondary liquidity because they want access. If markets turn, that pendulum could shift back.

For investors considering private-company shares, what does a secondary-market price tell them compared with the valuation at the company鈥檚 last fundraise?

Haslett: I think it gives them the true price.

A primary valuation is a point-in-time measure of what investors were willing to pay, and those investors generally received preferred stock with additional rights and liquidation preferences.

The secondary market is more telling of what you could actually get in your pocket now. For companies that embrace secondary liquidity, those prices help employees, former employees and early investors understand what their shares are actually worth.

How does EquityZen calculate popularity and distinguish durable investor demand from curiosity or hype?

Haslett: Our platform allows investors, typically retail accredited investors, to tell us what they鈥檙e interested in. They can browse companies, review our analysis, and indicate which companies they would invest in, if shares became available, and at what size.

That gives us a real-time metric of what our user base wants to invest in and how much. It helps guide where we spend our time bringing opportunities to clients.

The last thing we want is to work with a shareholder when we can鈥檛 find a buyer, or with a buyer when we can鈥檛 find shares for sale.

What does the recent consolidation in the secondary market tell you about how the market is evolving?

Haslett: There was a lot of attention toward the end of 2025 around consolidation in the secondary-market space. went to , and EquityZen went to Morgan Stanley.

To me, that reflects market growth, increasing adoption of secondary liquidity, and the fact that the biggest financial institutions are paying attention. I don鈥檛 expect that to change.

Your data showed that some software companies began trading at premiums again in the second quarter. What separates those gaining investor confidence from those still trading at deep discounts?

Haslett: Execution. Leadership and execution.

It鈥檚 about a company鈥檚 ability to take a legacy SaaS business and turn it into something AI-enabled across the business. Are you using AI tools to improve internal tasks? Are you building AI into your product for clients?

Companies that can combine the stickiness and customer loyalty they鈥檝e already built with their domain expertise and AI are going to do just fine. The ones that are slower to adopt are going to get pummeled.

Six months ago, there was concern that when a company like announced a cybersecurity or legal tool, companies in those sectors would immediately lose value. I think some of that was a knee-jerk reaction.

Customers already using your software have some patience, but they also expect you to keep improving the product and give them a reason not to switch. The companies that are slow to react, or too proud to react, are the ones I think will get hit hardest.

, and 1聽are examples of software that is deeply ingrained in large enterprises. If companies can keep their products working well and keep adapting them, they still have a shot at being successful standalone businesses. It comes down to management execution.

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In Silicon Valley, if a founder wants to build the next unicorn, there’s a formula: find a bold idea, surround yourself with well-heeled advisers and investors, and raise a war chest. With cash and fundraising buzz, go after a large market in search of product-market fit. That journey sometimes leads to winning pilots, more rounds and real customers. More often, the company pivots into a different niche or quietly dissolves. A whiff of failure sends employees to the exits and funding evaporates. That’s the VC-backed model. It fuels the dreams of college dropouts and frustrated engineers, rewarding luck and timing when they meet in the hottest niches.

But not all companies can or should be built that way. Only a handful of winners make fairy tale successes. The more common path is bootstrapped or self-funded: Start with an existing customer problem and get paid more than it costs to solve it. Find more customers with the same problem, build systems to improve the solution, repeat.

For entrepreneurs without the luxury of risk capital, product-market fit can鈥檛 be an odyssey. It has to be a starting point. Much of the global economy has been built this way. The path may take longer than the VC “go big or go home” approach, but many small companies scale into middle market businesses, and a few of the best find their way to market leadership, even in tech. Consider and . For every VC-backed startup, there are hundreds of bootstrapped founders building profitable businesses without any outside investment.

Customer-focused and experienced founders

Ask VC-backed founders how they built their company, and you’ll hear about the team and investors first. Bootstrapped founders tell it in reverse: the customer comes first, and the team is built around them.

Some of the most successful VC-backed founders are younger, benefiting from inexperience by seeing opportunity as a blank sheet of paper rather than a wall of entrenched obstacles. A 25-year-old with no mortgage, no reputation to protect, and no comfortable job to leave can withstand a failure and start again. These risk-taking enterprises spare no expense to attract the best hired guns money can buy and build fancy offices, all with a focus on hitting milestones for the next round of financing. When it works, the outcomes are spectacular: think of the Collison brothers at taking on payments, or ‘s young team taking on development tools.

But these are exceptions, not the rule. Industry experience, domain knowledge and customer relationships are essential to building a company. Bootstrapped founders typically know their customer before they build. There’s no search for product-market fit, because the product is built for problems the founder already knows intimately. Growth comes from deepening existing relationships, a surer path to revenue than risk capital is meant to fund. The team is hired out of profits to serve paying customers, not to test if demand exists.

Bootstrapped founders have a different profile. Typically mid-career, they have more at risk: a mortgage, a reputation, a family depending on their income. They lack the appetite for a long-shot bet. Instead, they gravitate toward businesses with a real chance of working, aiming for profitability quickly, often starting small rather than earth-shattering, with lower barriers to entry. The result is a business run for profitability, not growth. Leadership has often worked together before or shares common backgrounds. Growth is often linear and slow for years, until the company reaches a scale where it can pursue more strategic opportunities.

The AI advantage for bootstrapped companies

In an AI era where code-generation and product design tools bring down the cost of building and deploying new products, most companies should require less risk capital, not more. In the past, a non-technical founder with an idea needed outside capital to build it. Product development required an engineering team, and an engineering team meant a payroll early revenue couldn’t finance. That was the justification for raising a seed round before lining up a single customer. With AI, capital is no longer the limiting factor for innovation.

The VC-backed market, though, is moving the other way, with larger seed rounds and bigger early-stage funds than ever. Increasingly, risk capital is used for less rational reasons that speak to the speculative bubble we live in: not to fund product development, but to buy time to market, fuel “land grab” velocity in sales and marketing, and subsidize deployments that would otherwise be uneconomic for customers.

A founder today can build a working application with a small team, deploy with real customers, and validate whether further investment is needed. The product/market gap that once required millions of dollars and world-class hires can now be closed by a handful of competent people. , the with $1 billion in revenue, is an extreme example of what is possible. Niche markets once too small for VC-backed startups now can be addressed by bootstrapped companies.

That doesn’t mean every business should be bootstrapped. A founder with a genuinely untested, capital-intensive idea and no existing customer base still has real use for outside risk capital to fund the search for a market. But AI has lowered the cost of entry and should spur an unprecedented number of bootstrapped companies built outside the VC ecosystem, profitable and lean from the start. The best of them will become the.

is the founder, managing partner and chair of the investment committee at . He launched Lateral with a strategy to allocate first institutional growth capital to independent, owner-operated middle-market businesses underserved by typical buyout firms. Previously, he served as a managing director at , a venture capital and growth equity firm that has invested in more than 300 companies including , , , , and . De Silva also previously co-founded , a marketplace for construction equipment that was sold to for nearly $800 million. He received an MBA from , a master of philosophy from the , and an undergraduate degree from .

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

Overall, the pace of dealmaking in 2026 looks relatively flat聽1Reported deal counts are down slightly this year from the comparable period, but are likely to even out more over time as some acquisitions, particularly smaller deals, are added to the dataset weeks or months after they close.2 compared to last year. That鈥檚 not entirely surprising given that overall market conditions haven鈥檛 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 SA国际传媒 data.

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

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

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

No big slowdown in sight

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

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

Concentration of capital is another factor driving M&A deals. While overall startup funding has risen this year, it鈥檚 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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• The Rise And Rise Of Billion-Dollar-Plus Rounds

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

Startup investors were busily closing on big rounds this week, with AI and defense among their favored target sectors. The biggest financing went to , a defense tech startup developing a hypersonic missile. Other sizable rounds went to companies developing AI inference technology, a video-creation platform, data centers and voice-to-text tools.

1. , $800M, defense tech: Castelion, a defense tech startup developing a hypersonic strike missile, raised new Series C funding consisting of $800 million in equity capital along with $250 million in debt financing. , and led the equity financing, which set a $13 billion valuation for the Torrance, California-based company.

2. , $700M, semiconductors: San Jose, California-based Etched, a developer of inference clusters to accelerate AI computing, secured $700 million in a new funding round led by and joined by a long list of prominent investors. The financing set a $21 billion valuation for the 4-year-old company.

3. , $400M, AI video tools: AI video- and image-creation platform Higgsfield closed on $400 million in Series B financing at a $5.4 billion valuation. led the round for the San Francisco-based company, with the financing drawing at least 18 investors.

4. , $350M, data centers: Groq, an operator of 13 data centers across the globe, pulled in $350 million in a new fundraise led by , with planned participation from .The fundraise, which values the San Francisco-based company at $3.5 billion, comes on the heels of a $650 million in June.

5. , $280M, voice-to-text AI: Wispr Flow, a provider of an AI-powered voice-to-text tool called Flow, picked up $280 million in Series B funding at a $2 billion valuation. led the financing, joined by a long list of new and existing investors.

6. , $250M, satellites: Muon Space, a designer, builder and operator of satellite constellations, closed on $250 million in Series C funding led by . The Mountain View, California-based company also recently opened a manufacturing facility in San Jose, California, designed to produce up to 500 satellites annually by 2027.

7. , $150M, micromobility:聽 Also, a spinout that makes electric bikes and small four-wheeled micromobility vehicles, secured $150 million in Series D funding led by . The Palo Alto, California-based startup said the financing will go in part toward accelerating development of its autonomous vehicle platform.

8. , $110M, AI computing: Velaura AI, a developer of AI compute infrastructure focused on ultra-low-power silicon and software technologies, picked up $110 million in Series A funding. led the financing, which set a valuation of over $1 billion for the Silicon Valley-based startup.

9. , $100M, agentic finance: Rillet, a developer of AI-powered enterprise resource planning tools, landed $100 million in Series C funding led by . The round, which sets a $1 billion valuation for the San Francisco company, is Rillet鈥檚 third financing in the past year.

10. , $75M, sleep testing: Happy Health, and Austin-based developer of a ring device for diagnosis and treatment of sleep apnea, raised $75 million from and .

Methodology

We tracked the largest announced rounds in the SA国际传媒 database that were raised by U.S.-based companies for the period of Aug. 15-21. 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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This month鈥檚 installment of this column is all AI, though applications for the technology range widely, from two startups that apply AI to trash or recycling, to another that promises to help people breathe and sleep better, to a company that says its AI can help architects and builders spot commercial projects before they鈥檙e even announced. Let鈥檚 jump in.

$27M to help recycling plants see what鈥檚 in trash

For decades, the recycling industry has relied on sampling and educated guesses to understand what moves through its facilities. But wants every discarded bottle, carton and wrapper to become data.

The London-based startup said last month that it has raised a 拢20.3 million ($27 million) Series B led by technology investor . The company installs AI-powered camera systems above conveyor belts in recycling plants, then uses computer vision to identify materials, products and brands in real time. Greyparrot says that data helps operators recover more valuable materials, improve sorting efficiency and comply with increasingly strict recycling regulations.

Its systems are now deployed in more than 20 countries and have analyzed more than 1 trillion waste objects, per the company. It counts large waste-processing companies such as and among its customers.

The data gathered at plants also feeds Greyparrot鈥檚 Deepnest platform, which it says consumer brands including , and use to understand what happens to their packaging after consumers throw it away, helping to inform redesigns and comply with Extended Producer Responsibility rules in places such as Canada and the EU.

The fresh funding will help expand the company’s footprint across North America and Europe and support its goal of preventing more than 1 million tons of waste by 2030.

The raise reflects growing investor interest in applying AI in the physical world rather than behind computer screens. Companies in the physical AI sector raised nearly $47.3 billion in the first half of 2026, SA国际传媒 data shows, up nearly 80% year over year, as startups increasingly apply artificial intelligence to settings such as factories, recycling plants and other 3D environments.

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$17M to help robots navigate where GPS can’t

For a recently funded robotics company, the next frontier for physical AI is underground: in mines, tunnels and other places where GPS doesn’t work.

Australian startup said last month that it secured $17 million in new funding. That includes a $10 million equity round backed by , , , and as well as a $7 million venture debt facility from the country鈥檚 National Reconstruction Fund Corp. The company plans to scale manufacturing and expand its AI autonomy and cloud mapping platforms.

Emesent is best known for Hovermap, a LiDAR scanning payload that mounts to drones, vehicles or backpacks to create detailed 3D maps of mines, industrial sites and other hazardous environments. But increasingly, the company’s focus is software. Its Cortex AI platform enables robots to navigate autonomously in environments without GPS, while its Aura cloud platform processes and analyzes the resulting spatial data.

The company says its technology is already deployed at more than 200 mine sites worldwide and that it is expanding into the defense, critical infrastructure and construction sectors.

Its raise is another example of increased interest and investment in physical AI. As industries grapple with labor shortages and increasingly dangerous operating environments, startups that combine robotics, computer vision and autonomy are attracting fresh capital to automate work that’s difficult, dirty or unsafe for humans.

Robotics investment funding overall has been on a tear in recent quarters. Startups in the category raised $15 billion globally in 2025 鈥� an annual record that has already been eclipsed partway through 2026 鈥斅燬A国际传媒 data shows.

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$12.25M for AI that treats congestion with sound

We鈥檝e covered AI that can do dirty work like help sort through trash or navigate underground mines. What about AI to help people breathe?

San Francisco-based medtech startup recently raised an oversubscribed $12.25 million Series A led by . The company develops FDA-cleared, noninvasive devices that it says use AI and acoustic resonance therapy to treat congestion and improve sleep without drugs.

The company said its flagship Sonu band personalizes sound waves based on a user’s facial anatomy to open nasal passages, while its newer Spatial Sleep device aims to help users fall asleep faster and stay asleep longer.

The raise comes as investors continue to back AI-powered medical devices that combine software with regulated hardware. Companies that intersect SA国际传媒鈥檚 AI and medical devices industries raised more than $629 million in the first half of this year, our data shows, up about 33% year over year.

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$3.85M to turn unrecyclable trash into fuel

Trash and recycling emerged as an unexpected theme in this month鈥檚 column. While Greyparrot helps companies better understand what鈥檚 in landfills and recycling plants, another recently funded company, , says it鈥檚 working to turn unrecyclable garbage into industrial fuel.

The Nashville, Tennessee-based company last month announced a $3.85 million round co-led by and to commercialize technology that converts hard-to-recycle plastics and other waste into industrial fuel. The startup says its engineered fuel can replace coal in cement, steel and other heavy industries without requiring factories to modify existing equipment. The new funding will help it build its first commercial U.S. biofuel facility outside Las Vegas.

Global venture investment into cleantech-related startups has been steady but not record-breaking in recent years, SA国际传媒 data shows. Around $15 billion went into rounds for companies in SA国际传媒鈥檚 cleantech-, EV- and sustainability-focused categories in the first half of 2026, putting this year鈥檚 funding on track to slightly exceed the 2025 tally, which was the lowest in several years.

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$3.5M to predict construction projects before they’re announced

The biggest construction opportunities often surface months before the first request for proposals. promises to use AI to spot them first.

The New York-based startup last month raised $3.5 million in seed funding from 鈥檚 accelerator, , and others to build an AI platform for architecture, engineering and construction firms. The startup promises to give such companies an edge over their competitors by helping them discover projects earlier and identify the best path to winning them. Instead of searching public bid databases, Cascade says its tech can analyze signals such as bond filings, property transactions, capital budgets and meeting minutes to identify projects while they’re still taking shape.

Overall funding to real estate-related startups has trended higher in recent quarters, and the sector emerged as a bright spot for seed funding in the first half of 2026, an analysis of SA国际传媒 data shows. Other seed-funded real estate startups this year have spanned areas ranging from streamlining planning and building processes to real estate investing to reducing power consumption in buildings.

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

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

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

Seed portfolio

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

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

Series A leaders

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

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

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

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Venture investors appear to increasingly see physical AI as the next leg of the broader AI boom. Notably, according to a recent article in , many firms known for early bets on software, internet services and social media companies are writing more checks to companies building 鈥減hysical technologies and materials tied to the artificial-intelligence boom.鈥�

SA国际传媒 data backs this up.

In the first half of 2026, global venture funding in the space totaled $47.4 billion across 521 deals, per our data. That鈥檚 up dramatically 鈥� almost 4x 鈥� compared to the second half of 2025 when physical AI startups raised $12 billion across 470 deals. It鈥檚 also up significantly 鈥� by nearly 80% 鈥� from the $26.4 billion raised across 436 deals in the first half of 2025.

To give you an idea of just how much more money is going into physical AI companies, here’s a comparison. In the three years spanning 2022 to 2024 combined, venture investors put a total of $41.9 billion into physical AI companies 鈥� still several billion less than we鈥檝e seen raised in just the first half of this year alone.

And before we go any further, I should clarify that by our criteria, physical AI includes industries such as robotics, autonomous vehicles, aerospace, drones, industrial automation and sensors.

Noteworthy deals

Several multibillion-dollar megadeals drove the spike in H1 investment. One very large deal in particular accounted for nearly one-third of all venture dollars: Mountain View, California-based 鈥檚 raised in February. , , and co-led the financing, which was raised at a staggering $126 billion valuation.

Other companies that have brought in large rounds this year include:

• In May, defense tech startup raised another $5 billion in funding at a $61 billion valuation 鈥� double the $30.5 billion valuation it received less than a year earlier.
• San Diego-based in March landed a $2 billion Series G round co-led by and . Its valuation jumped to $12.7 billion.
• In March, Austin-based , a defense tech startup focused on autonomous sea vessels, raised $1.75 billion in Series D funding, bringing its total funding to around $2.6 billion. led the round, which set Saronic鈥檚 valuation at $9.25 billion 鈥� more than double its Series C level in 2025.

Exits

The physical AI space has also produced several notable exits so far in 2026, although activity has been more concentrated in aerospace, defense and drones than in areas like robotics.

has been the clear outlier, raising $75 billion in its June IPO at a $1.77 trillion valuation. Other notable public debuts include Herndon, Virginia-based space intelligence company , which raised $416 million, and Arlington, Virginia-based autonomous drone maker , which raised $320 million. On the M&A side, one of the most notable deals was roughly $900 million acquisition of Tel Aviv鈥檚 humanoid robotics startup , a transaction the company explicitly tied to its push into physical AI.

Investor POV

, general partner at , told SA国际传媒 News via email that while funding in physical AI has historically been concentrated in robotics and humanoids, defense, and foundational models, he sees the opportunity as much broader. Physical AI, in his view, represents the convergence of software, hardware, sensors and IoT, and services across a wide variety of real-world applications. What is changing, according to Ziegler, is AI’s ability to process data from those systems at such a scale and speed to generate useful operational insights, while the underlying hardware becomes cheaper and more accessible.

鈥淓ven our mobile phones now have LIDAR scanners on them,鈥� he noted, 鈥渄emocratizing the ability to map objects and spaces.鈥�

For Edison Partners, the appeal is particularly strong in high-value, traditionally analog industries where physical AI can become mission-critical infrastructure. Ziegler pointed to manufacturing, supply chain, utilities, agriculture, transportation, government, and physical and spatial intelligence as areas of interest. Many of these companies resemble vertical software businesses, he said, with 鈥渁ttractive unit economics, large deal values and multi-year deployments,鈥� while their combination of software, sensors and hardware can generate proprietary datasets that become increasingly valuable over time. Edison is especially interested in applications where the return on investment is measurable through predictive maintenance, risk management, asset integrity, security and autonomous operations.

The economics of building these companies have also improved considerably over the past two years. Ziegler compared the shift to what cloud infrastructure did for SaaS.

鈥淭he costs to build these companies have come down, and AI infrastructure and multi-modal tech to do so is now available,鈥� he said.

Meanwhile, compute and foundation-model capabilities have become more accessible, reusable models and physics-based simulation have improved, training data is more plentiful, and sensor and hardware costs have declined. At the same time, companies are increasingly bundling hardware into recurring or mixed-revenue models and moving toward outcome- or usage-based pricing. That combination, Ziegler said, makes the hardware itself a distribution mechanism for software and data, with 鈥渉ardware [as] the distribution model for creating a data intelligence flywheel.鈥�

, partner and head of growth at , told SA国际传媒 News via email that while physical industries remain capital intensive, AI and other enabling technologies are changing how efficiently companies can build and scale. Historically, the capital required to reach meaningful scale made investors wary, but he argues that 鈥渢ech barriers are plummeting, experienced talent is pouring in, and market demand is rising.鈥�

That convergence is driving more investment into areas including energy, robotics and autonomy, inference, chips and compute, and data center infrastructure. As a result, he said, funding is increasingly shifting away from experimentation and toward companies that can hit production milestones, land customers and scale efficiently.

For Eclipse, physical AI is not a new theme but a core investment thesis dating back to the firm鈥檚 founding in 2015. Fath said the opportunity has become more compelling because 鈥渢he technical and economic conditions are now catching up to that longstanding conviction,鈥� allowing companies to iterate, deploy products and reach customers faster.

Eclipse defines physical AI broadly as 鈥渋ntelligence embedded in systems that perceive, reason, and act in the real world,鈥� while generally avoiding investments in standalone large-language-model providers. Fath described the firm鈥檚 focus as investing on the 鈥渟houlders,鈥� rather than the 鈥渉ead.鈥� This means that Eclipse backs both the infrastructure that enables generative AI, such as chips, compute, energy and data centers, and the companies applying AI to build new businesses in the physical world.

He views the current landscape as the result of technology, talent, capital, demand and policy finally aligning. More powerful compute, foundation models, simulation and developer tools are allowing smaller teams to build faster with less capital and labor, Fath points out. Looking ahead, he expects value to accrue throughout the physical AI stack, but believes the strongest moats will belong to companies that vertically integrate and own multiple layers.

Ultimately, he said, 鈥渃ustomers value operational efficiency, reliability, and revenue, not technical sophistication alone.鈥� The companies that can turn technical capability into dependable systems at commercial scale 鈥� and then use their data and infrastructure to expand into additional products 鈥� are likely to capture the most value.

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In turn, semiconductor giants are investing record sums in startups. So far this year, the sector鈥檚 most valuable companies have participated in rounds collectively valued at over $250 billion, per SA国际传媒 data. That鈥檚 multiples above prior high marks.

Large cap chip companies are also leading and co-leading some of the biggest financings. This includes 鈥檚 record-breaking $122 billion March funding round, in which was one of eight lead investors.

The other big deals

There鈥檚 no getting around that the OpenAI megaround really skewed the 2026 totals. That one deal accounts for over 95% of the value of all semiconductor company-led financings.

Still, there are plenty of other big rounds with semiconductor backing this year that, by any other comparative benchmark, would also be considered enormous. Take July鈥檚 $5 billion corporate financing from Nvidia for foundational AI startup .

So far this year, corporate semiconductor giants have invested in more than 60 startup financings of $100 million or more. Of those, 16 rounds were valued at $1 billion or more, which we list below.

Most active and highest spending semiconductor investors

It should surprise no one that Nvidia is the most active and highest spending corporate investor in the semiconductor space. The AI chip architect has participated in a record 59 known funding rounds so far this year, per SA国际传媒 data, up from 53 in all of 2025.

With a market cap around $5.4 trillion and a continued reign as the world鈥檚 most valuable public company, Nvidia certainly has the financial resources to invest heavily in startups. The company is also active as a lead investor, having led or co-led at least 11 private company financings this year, per SA国际传媒 data.

, with 19 private company financings this year, is also upping its startup investment activity in tandem with what鈥檚 been a strong year for its own shares. This year鈥檚 tally includes at least four rounds valued at $1 billion or more.

Another standout is , with at least 17 known startup investments so far this year. The South Korean megacap has a lengthy history of active participation in seed and venture deals.

The corporate investment tallies also don鈥檛 represent the full extent of semiconductor companies鈥� involvement in the venture funding ecosystem. Additionally, some invest through backing outside venture funds.

Is this peak?

With semiconductor companies raking in profits from the AI boom, and shares soaring alongside, it鈥檚 worth considering whether we may be close to a peak for semiconductor startup investment. On the other hand, if industry leaders鈥� shares keep rising, the sums spent on startup dealmaking look comparatively small relative to semiconductor giants鈥� swelling valuations.

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

is back raising another $5 billion, after it raised that amount eight months ago. The largest fundings also went to an AI neolab, data center and electricity storage, defense, coding and biotech. Let鈥檚 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 SA国际传媒 data.

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

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

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

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

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

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

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

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

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

Large non-US deals:

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

, $400M, automated applications: Lovable raised a $400 million Series C funding led by and , valuing the company at $13.3 billion. The Stockholm-based company claims 900 million visits each month and 60 million projects created. Lovable鈥檚 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 SA国际传媒 database that were raised by U.S.-based companies for the period of Aug. 8-14. Although most announced rounds are in the database, there may be a small time lag, as some rounds are reported late in the week.

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

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

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

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

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

New unicorns in July

Here are July’s new unicorn companies:

Financial services

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

Robotics

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

AI

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

Multimodal AI

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

Energy

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

Semiconductor

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

Cryptocurrency

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

Defense

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

Marketplace

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

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

Data center

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

Insurance

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

Quantum

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

AI coding

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

Legal

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

Security

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

Wearables

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

Related SA国际传媒 unicorn lists:

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

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

Methodology

The SA国际传媒 Unicorn Board is a curated list that includes private unicorn companies with post-money valuations of $1 billion or more and is based on SA国际传媒 data. New companies are as they reach the $1 billion valuation mark as part of a funding round.

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

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

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

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

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