Globally, robotics startups have so far raised $18.8 billion in 2026, compared to $15 billion in the full year of 2025. The figure also handily surpasses the $14.1 billion raised in the peak venture funding year of 2021, and we still have more than six months of fundraising left.

The impressive rise in funding reflects a marked shift in perception among venture investors about the robotics sector, which was traditionally considered an expensive, asset-heavy hardware gamble. In particular, investors appear to be drawn to startups working on embodied AI, or artificial intelligence with a physical body that interacts with the real world in real time.

Noteworthy recent rounds

The surge in funding is driven by a number of robotics-focused startups raising considerable capital from investors this year. Also, interestingly, two of the five largest raises in 2026 to date have been by Austin-based companies.

Topping the list of largest deals in 2026 so far is Austin-based , a defense tech startup focused on autonomous sea vessels. In March, the 4-year-old company 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.

Earlier this month, Germany鈥檚 , a developer of AI infrastructure for robots to learn, collaborate and operate across real-world environments, said it secured up to $1.4 billion in Series C funding. led that raise.

In January, , a robotics company building an 鈥渙mni-bodied鈥� brain to operate any robot for any task, announced that it had raised $1.4 billion, tripling its valuation to over $14 billion. That financing came just over seven months after Skild raised at a $4.5 billion valuation. led the startup鈥檚 latest round, which included participation from , 鈥檚 venture capital arm.

On June 15, Beijing-based , which creates water robots and intelligent unmanned equipment, raised $1 billion in a massive Series A round led by .

And in February, AI-powered robotics company raised $520 million in an extension of its $415 million Series A raise in February 2025, bringing the total round to over $935 million. Existing backers , , and joined new investors, including and manufacturing giant in participating in the extension.

Interestingly, spinout has already raised two rounds in 2026. In March, the Palo Alto, California-based startup closed on a $500 million Series A round, co-led by and . Then in May, it raised another $400 million in a financing led by . The company is developing an AI-enabled industrial robotics platform focused on automating industrial and manufacturing tasks at scale.

Exits

While mergers and acquisitions have been relatively robust with several strategic buyouts, the robotics IPO landscape is a bit quieter, particularly in the U.S.

In China, however, a number of robotics companies have recently gone public. The of , targeting a $3 billion to $7 billion valuation, was considered a milestone for the industry. In March, the company filed for an to list on the , and its IPO was widely expected to spur other startups in the space to pursue their own public-market debuts.

, a startup based in China鈥檚 Shandong province that makes lightweight industrial robots, in May listed on the , raising about $86 million. And it did not disappoint. Robotphoenix closed its first full day of trading at HK$53.75 ($6.86 U.S.), up nearly 80%, though shares have dipped to the HK$37 range more recently.

On the M&A front, a number of Big Tech and automotive giants have been aggressively acquiring embodied AI and humanoid talent to anchor their physical automation strategies.

In February, AI-powered supply chain provider acquired , an Austin-based maker of autonomous forklifts and lift trucks.

Skild AI in April that it had picked up the robotics arm of in an effort to deploy its technology to warehouses.

And in May, tech giant entered the humanoid robotics field directly by acquiring San Diego-based . The team was absorbed into Meta’s Superintelligence Labs unit to accelerate training of its foundational physical AI model.

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I sold my AI research company while I was qualifying as a lawyer in the U.K. I built with researchers from , , and who believed in the mission enough to trust a 21-year-old law student to lead the ship.

, when acquired us, it was the first time in its 170-year history it bought a company pre-revenue. Thomson Reuters acquired us for the science.

Getting there was painful, though. Our published papers put the model among the best in the world at legal reasoning, and we trained it for a fraction of what the large labs were spending. We had been a quieter version of 鈥渢he story,鈥� developing very capable models using novel algorithms with huge capital efficiency.

None of that counted for much in the rooms I walked into. Investors always asked about the product and the traction. U.K. investors passed, and I ended up raising most of our funding in the United States.

I back founders now, and the things I weigh have stayed consistent. As a founder, I was told again and again that science meant little until it was bolted onto a product. That test was wrong then and I believe it is fatal now.

Backing founders in the foundational layer

In the first quarter of 2026, foundational AI startups raised around $178 billion. The market is realizing that foundational AI is where the long-term value sits, and this is the year we may see the exits and IPOs that prove the bet right.

However, the capital and the conviction have also pooled around a few names that were already incumbent. , and took roughly 97% of it, and every other foundational AI company in the world shared what was left.

For a deep-tech founder starting out now, that might push them toward a tempting but dangerous read of the market: that the race is over, and that the sensible move would be to build on top of one of these giants.

I鈥檓 looking for founders who move the other way.

Most application-layer companies, built on a model they do not own, adapt to the pricing and access decided for them by the firms upstream, and compete in categories that the same firm can absorb whenever it chooses.

The more durable place to build is the layer underneath. The cost, speed, reliability, interpretability and safety of AI systems remain unsolved and genuine scientific challenges, and they decide what everything that sits above them can do.

A real advance in training efficiency, model architecture and inference cost is the work that will still matter in five years, long after most of today鈥檚 wrappers have been priced out or absorbed.

Asking the right questions

So the questions I ask AI founders are:

• Is your technical team, scientist-for-scientist, equal to or better than the team at DeepMind?
• Does the problem sit at the level of the model and the system, or is it one more thing stacked on someone else鈥檚?
• Will the 鈥減roduct鈥� get harder to live without over the next five years, or is it looking to reach for early revenue like every other startup?

Some of the companies that ended up mattering most in the AI era are those that survived this line of thought. DeepMind and OpenAI began as research efforts with no obvious product, and both would have looked uncomfortable to a conventional early-stage software investor. Their importance is obvious in hindsight, but the foundational problem-solvers tend to look unfundable right up until it looks inevitable.

Do not build to look fundable this quarter. Build something that the whole stack will depend on in the future. Hire the best team you can find to do it, and solve the hard, foundational problem while it is still unfashionable.

The deep-tech capital market is slow, and it will keep chasing familiar names for a while yet. The work still comes first, and the founders who dare to do it early are the ones the market eventually has to come and find.

The future lies in deep tech, not in the surface wrappers that pass for most products nowadays.

was the founder and CEO of , which was acquired by in 2024. He is an angel investor and senior director at Thomson Reuters Labs.

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The acquisition represents an enormous return on investment for Cursor鈥檚 backers. Since its founding just four years ago, parent company raised $3.4 billion from investors including , repeat backer , and and was most recently valued at roughly $30 billion in November, per 91精品.

The acquisition gives SpaceX, which raised $75 billion in its IPO last week, a foothold into the enterprise software development market, where AI-assisted coding has taken off and led large companies to significantly pare back their reliance on human engineers. Cursor said in November last year that it had crossed $1 billion in annualized revenue.

Hawthorne, California-based SpaceX has in recent years expanded beyond space exploration to become something of an umbrella company for CEO 鈥檚 numerous other interests and ambitions, as the company acquired the social media platform (formerly Twitter) and the AI company . SpaceX shares jumped around 16% on Tuesday following the Cursor announcement.

This year has proven robust for M&A activity involving venture-backed startups, 91精品 data shows. Through June 16, at least 1,177 such deals altogether valued at $182.7 billion have been announced. That compares with 1,132 deals valued at $106.7 billion in the same period last year.

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Meanwhile, filed on June 1 at a $965 billion valuation, and followed on June 8, . After four years of a venture liquidity drought, the read across the industry is simple: the IPO window is finally open again.

I would be careful with that read.

Look at where the money is coming from. SpaceX’s raise alone is slated to be more than the .

that with brokerage cash balances low, retail investors may have to sell existing holdings to fund their SpaceX orders, with and Bitcoin the most likely sources, and SpaceX is reserving as much as 30% of the deal, roughly $22.5 billion, for that same risk-on crowd. Crypto’s own this year as capital rotated toward AI. These three companies could very well be the entire 2026 IPO class.

Put together, this points to a concentration event rather than a broad reopening. A small number of funds and pre-IPO sellers get liquidity, three tickers absorb the available capital and attention, and the rest of the queue waits. If you run an early-stage company, the window reopening for SpaceX does very little for you directly.

The acquisition outlook

What these listings do change is more durable, and it runs through M&A.

A public SpaceX, OpenAI and Anthropic become some of the best-capitalized acquirers on the planet, with liquid stock to spend. OpenAI has already closed roughly half a dozen acquisitions this year, nearly matching its full 2025 total, and AI dealmaking across the market in the first quarter. The vast majority of venture exits have always been acquisitions; these offerings deepen the pool of buyers far more than they shorten the IPO queue.

For founders, that reframes the goal. Don’t build for an IPO window that was only ever open to a handful of companies. Build to be the company a newly public AI giant needs to own: real ownership of a workflow, proprietary data that compounds, the testing and evaluation infrastructure these labs increasingly run on, or a wedge into a market one of these platforms wants to enter. At the seed stage, the exit math has always pointed toward a single meaningful acquisition, and this wave widens the set of acquirers who can write that check.

For investors, the discipline is to not mistake a concentration event for a market that has reopened. The liquidity 鈥斅燼nd the distributions LPs have spent four years waiting on 鈥斅爓ill land with a narrow set of names. Most portfolios still get liquid the way they always have, through M&A, and the health of that market matters more to the median fund than whether SpaceX trades up on day one.

The test comes this fall. If the retail bid holds and the next tier of the queue prices well, Friday really will be the start of a broad reopening. Watch those follow-on listings, and watch what three newly public companies do with their stock over the next year. That second part is what reaches the rest of the market.

As the co-founder and managing partner of , is committed to establishing MGV as the premier venture firm for world-class tech entrepreneurs to accelerate their visions. Under Schr枚der鈥檚 stewardship, MGV has swiftly ascended to a top-quartile firm, surpassing the performance of 95% of venture funds. The performance of MGV is driven by Schr枚der鈥檚 unique approach to venture investing 鈥� that providing intensive sales training, devising robust fundraising strategies and securing follow-on investments is the best way to support founders and drive the deepest return for investors. has recognized him as one of the Top 100 global seed investors, and his perspectives are published regularly in 91精品 News and other leading publications.

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AI’s share of venture funding climbed to 80% this quarter, up from 55% a year ago. The deployment is real. The liquidity question behind it is the one founders should be paying attention to.

In 2025, 91精品 roughly 2,300 venture-backed acquisitions against just 65 IPOs. In aggregate, the LPs sitting behind every venture fund have been in since 2022. Record deployment in Q1 doesn’t change the math at the LP level, and that pressure is reshaping every term sheet, follow-on decision and board conversation in venture right now.

Know what’s actually driving the firm across the table

When a partner walks you through their thesis, they’re telling you a story about your market; rarely are they telling you a story about their fund. That second story determines whether they can write your bridge in 18 months, whether they’ll fight for pro rata in your Series B, and whether their behavior in the next downturn looks like patience or anxiety.

LPs are demanding cash back. Paper markups aren鈥檛 enough. Some firms are responding well, consolidating into their best companies and being deliberate about new commitments while others are pretending it’s still 2021. Founders should know which type they’re sitting across from before signing anything.

Ask the questions founders rarely ask

Three reference calls with portfolio CEOs used to be enough due diligence on a VC. Not anymore.

Ask what vintage the partner’s current fund is and how much dry powder is left. Ask how many of their 2018 through 2020 companies have produced realized returns rather than paper markups.

Ask whether their LPs have been pushing for GP-led secondaries. If the answer is yes, the firm is operating under a cash-flow constraint that will show up in your boardroom. These aren’t rude questions. They’re the same ones serious LPs are asking that partner this quarter, and high-quality firms welcome the conversation.

Build your buyer relationships now

If you’re raising in 2026, you’re statistically far more likely to get acquired than to ring the bell at the . Q1 2026 alone produced, the third-busiest quarter since 2022. Of the 21 venture-backed exits over $1 billion globally last quarter, only four happened in the U.S. The exit window for American founders is narrower than the headline funding numbers suggest.

Smart founders design for that reality from Series A. They know which platform companies have an active corporate development team. They build product surface area that maps cleanly into someone else’s stack. They cultivate executive relationships at the most likely acquirers years before any sale conversation, so when one starts naturally the introduction is already there.

Capital is plentiful. Discipline is what separates outcomes.

Every dollar concentrated into the four AI mega-rounds is a dollar that hasn’t returned anything to LPs yet. Founders who understand the LP-to-GP-to-startup chain end up with better partners, smarter terms and companies built for more than one path to a great outcome.

As the co-founder and managing partner of , is committed to establishing MGV as the premier venture firm for world-class tech entrepreneurs to accelerate their visions. Under Schr枚der鈥檚 stewardship, MGV has swiftly ascended to a top-quartile firm, surpassing the performance of 95% of venture funds. The performance of MGV is driven by Schr枚der鈥檚 unique approach to venture investing 鈥� that providing intensive sales training, devising robust fundraising strategies and securing follow-on investments is the best way to support founders and drive the deepest return for investors. has recognized him as one of the Top 100 global seed investors, and his perspectives are published regularly in 91精品 News and other leading publications.

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Just through mid-May, China-based robotics companies this year have raised $5.6 billion across 176 deals, 91精品 data shows. That sum matches total investment to the nation鈥檚 robotics companies in all of 2021, the peak of the funding cycle. Investment in the sector has also already eclipsed the $4.3 billion raised by China-based robotics companies in all of 2025.

Startup funding in Asia overall surged to $27.4 billion in Q1, its highest level in over three years, with China capturing $16.5 billion 鈥� 60% 鈥� of that total, according to recent 91精品 data. Robotics contributed meaningfully to that $16.5 billion total, with startups in the sector raising $3.3 billion across 126 deals.

Embodied AI boom

A review of 91精品 data shows that investors now are no longer funding mostly pre-programmed hardware, but increasingly backing China-based startups working on embodied AI 鈥斅爋r artificial intelligence with a physical body that interacts with the real world in real time.

That shift toward artificial intelligence-driven robotics mirrors a global surge in investment into robotics and other physical AI startups. It鈥檚 also thanks to the rise of advanced, open-source reasoning models that have fundamentally changed how robots operate. Startups are moving away from coding robots line-by-line toward Vision-Language-Action models that allow physical machines to observe, reason and execute physical tasks end-to-end.

In China, robotics startups at the intersection of the software and hardware integration are drawing the largest checks in the space and often back-to-back funding rounds. They include:

• , a 1-year-old humanoid robotics company that integrates embodied intelligence that last month raised a massive $513 million seed round led by and . The Shanghai-based company was valued at $1.9 billion.
• , which develops robotic systems and automation solutions for industrial and service applications, closed a $140 million Series A extension round in January from investors including . Then just three months later, it raised $293 million in a massive Series B round co-led by and
• In February, Beijing-based , which says it鈥檚 building a 鈥渦niversal brain鈥� for robots, raised a $290 million Series A led by and . The 2-year-old company was valued at $1.5 billion. Then in April, it announced a $145 million Series A extension financing, bringing the total round to $435 million.
• Humanoid robotics company in February raised a $145 million Series B led by . The 2-year-old China-based company was valued at $1.4 billion. In April, it announced a $290 million extension to that round, bringing its total to $435 million
• Shenzhen-based , a builder of humanoid and quadruped robots, raised a $200 million Series B last month led by and . The 2-year-old company鈥檚 robots will be deployed for traffic, security and retail. It was valued at $1.5 billion.

Top investors

91精品 data shows the most active investors in the space are largely Asia-based. The busiest this year has been Hong Kong-based , taking part in six deals, including a $200 million round last month for humanoid robotics and embodied intelligence developer .

Among lead or co-lead investors, three China-based firms 鈥� , and 鈥� have each taken part this year in deals totaling $290 million or more.

Exits gain steam

Venture investors are likely feeling confident as the sector notches notable liquidity events, including IPOs and acquisitions.

The of , targeting a $3 billion to $7 billion valuation, is a milestone for the industry. The company in March filed for an to list on the , and its IPO would likely spur other startups in the space to pursue their own public-market debuts.

The sector has already seen some notable exits.

They include Hong Kong-based ,聽 a Shanghai-based startup that makes lightweight industrial robots. The company on May 18 listed on the , raising about $86 million. And it did not disappoint. Robotphoenix closed its first full day of trading at HK$53.75 ($6.86 U.S.), up nearly 80%. (Interestingly, Chinese robotics firms as their primary liquidity hub.)

On the M&A front, in what is widely considered a historic first for China鈥檚 embodied artificial intelligence sector, AI robotics unicorn in July 2025 engineered a two-stage consortium takeover to in legacy manufacturer for about $290 million. AgiBot鈥檚 co-founder formally stepped in to chair Swancor, effectively turning the publicly traded shell into a direct extension of AgiBot.

Ultimately, it seems that 2026 is the year China鈥檚 robotics companies are pivoting from raising early venture rounds to mass production, as a domestic market that currently accounts for more than 43% of global robotics venture investment, per 91精品.

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I can definitely understand their logic in wanting a valuation that builds on top of the previous valuation. I also understand that they have strong underlying tech, a good team and the belief that the right buyer would see the potential upside.

And to be fair, there are cases that support this line of thought.

But in the current AI cycle, we鈥檝e seen transactions that look disconnected from fundamentals.

structured a roughly $650 million licensing and talent deal with , effectively bringing in most of the team and its technology. has done similar deals around AI startups, combining technology access with hiring key teams. and others have been active in this space as well.

In rare situations, they can be replicated. When they are, they can lead to exceptional outcomes and everyone involved would welcome that. But they cannot be the working assumption.

The main reason I decide to walk away from a deal is simply because expectations are not aligned with how M&A actually works. If we are not aligned on that from the beginning, I am setting myself up for failure.

Here are the patterns I see most often:

1. Narrative without enough proof

Founders tend to focus on what the company can become. Buyers focus on what has already been demonstrated. Technology and vision matter, but they need to be supported by real signals: Revenue quality, growth, retention and how easily the product fits into a buyer鈥檚 ecosystem all carry weight.

When expectations are built mainly on potential, the gap becomes hard to close.

2. Using exceptional outcomes as reference points

The market always has headline deals that shape perception, especially in AI. While these examples are real, we cannot use them as a baseline.

Most transactions are still priced on traction, growth and strategic fit. When a process is anchored on rare outliers, it is likely doomed to fail.

3. Capital raised vs. commercial reality

When a company raises capital at a certain valuation, it sets a reference point. Founders and investors expect the next outcome to build on that. Buyers look at something else entirely. Current performance and future synergies. If the business has not grown into the expectations created by earlier funding rounds, a gap forms, and it is a gap we need to address.

is a strategic adviser to tech companies and investors, specializing in strategy, growth and M&A, a guest contributor to 91精品 News, and a seasoned lecturer. Learn more about his advisory services, lectures and courses at . for further insights and discussions.

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Look closer, and the story changes completely. Early-stage funding was up 41% year over year. AI/ML deal count , up from roughly 5,600 the year before. More companies are getting funded at the early stage, not fewer.聽 The concentration at the top? That’s an infrastructure play. The application layer looks entirely different.

Build vertical, not horizontal

The real signal is in the shift from horizontal to vertical. shows horizontal SaaS down 35% over the past 12 months while vertical SaaS is essentially flat (up 3%). That divergence matters for founders deciding what to build.

Horizontal software (project management, general productivity, collaboration) is commoditizing fast as AI agents handle coordination natively. But vertical software? That鈥檚 where proprietary data shines and industry-specific compliance workflows matter. AI makes the first category less valuable and the second category more valuable.

If you’re starting a company right now, the data says: Pick an industry, not a feature. Claims processing in insurance, scheduling in healthcare, compliance in financial services, job costing in construction. These are workflows where software penetration has been shallow for decades because the problems were too specific for horizontal tools. AI changes that math.

Build for the $6T, not the $500B

The addressable market for software is expanding, not contracting. In Redpoint’s CIO survey, 58% cite AI as the top driver of increased software spend. As agents move from copilot features into autonomous workflow execution, the addressable market grows from roughly $0.5 trillion in current U.S. enterprise software spend toward $6 trillion or more, because AI starts capturing portions of the knowledge-worker payroll that software never could.

This is classic : When a resource gets dramatically cheaper to produce, consumption goes up. AI makes software dramatically cheaper to build, deploy and maintain. Suddenly, job costing for midsize contractors pencils out. Inventory optimization for independent pharmacies becomes economically viable. The cottage industries that enterprise software ignored for decades? They’re all in play now.

Build for acquirability, not just IPO optionality

But let’s talk about exits, because that’s where the rubber meets the road. The IPO market remains largely closed. In 2025, roughly 2,300 VC-backed startups were acquired compared to just 65 IPOs, per 91精品 data.

LPs have seen nearly $200 billion in cumulative negative net cash flows since 2022. The pressure to return capital through M&A is real and growing.

Smart founders are building for this reality from day one. They鈥檙e building products that integrate into existing enterprise stacks, accumulating proprietary data that makes them expensive to replicate and cheap to integrate. Strategic acquirers in insurance, healthcare, logistics and financial services are actively buying vertical software companies. Why? Because these buyers can’t build this stuff internally 鈥� they lack the talent, the focus, and frankly, the DNA.

Start with the workflow, not the technology

So while everyone’s mesmerized by the infrastructure megarounds, the real opportunity is staring us in the face. Pick a specific industry workflow that’s still manual or stitched together with Excel. Build the AI-native solution that actually works for that vertical. Get to revenue before the market catches up.

The record quarter and the shrinking fund base are telling the same story from different angles. Infrastructure capital is concentrating at the top while the application layer is wide open for those willing to roll up their sleeves and solve real problems for real industries. That’s where I’m putting capital, and that’s where smart founders should focus their energy.

As the co-founder and managing partner of , is committed to establishing MGV as the premier venture firm for world-class tech entrepreneurs to accelerate their visions. Under Schr枚der鈥檚 stewardship, MGV has swiftly ascended to a top-quartile firm, surpassing the performance of 95% of venture funds. The performance of MGV is driven by Schr枚der鈥檚 unique approach to venture investing 鈥� that providing intensive sales training, devising robust fundraising strategies and securing follow-on investments is the best way to support founders and drive the deepest return for investors. has recognized him as one of the Top 100 global seed investors, and his perspectives are published regularly in 91精品 News and other leading publications.

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Per 91精品 data, the high end of the purchase price represents the largest acquisition of a venture-backed biotech company in years. It鈥檚 a testament to the perceived potential of Kelonia鈥檚 pipeline of genetic medicines, including a treatment targeting multiple myeloma that has produced promising clinical trial results.

It鈥檚 also a quick progression by biotech standards. Boston-based Kelonia from stealth mode just four years ago, with $50 million in Series A funding led by , and . Two years later, it entered a research and licensing partnership with , a subsidiary of Japan鈥檚 , that included funding to develop immuno-oncology therapeutics using its in vivo gene placement system.

Per Lilly, Kelonia鈥檚 platform promises to not just improve outcomes for patients, but to do so in a rapid, simpler 鈥渙ff-the-shelf format鈥� compared to currently available CAR T-cell therapies. Its approach has been described as enabling the reprogramming of patients鈥� T-cells inside the body so those cells can attack cancer.

Kelonia鈥檚 vision is ambitious enough, and early results encouraging enough, to warrant what ranks as the largest acquisition of a venture-backed, private biotech company in the past 10 years, per 91精品 data. To put that in context, below we ranked the next-largest deals valued at up to $2 billion or more.

The list does not include venture-backed biotechs that went public, which would broaden the ranks considerably. This includes companies that sold to acquirers shortly after IPO, such as , a developer of therapeutics for obesity and metabolic disease that went public in February 2025 and sold to later in the year in a deal valued at around $10 billion.

In vivo acquisitions on the rise

Acquirers of late have been paying particularly handsomely for startups developing in vivo therapeutics. Just two months ago, Lilly purchased another high-profile venture-backed company in the space, , dedicated to engineering immune cells in vivo, in a deal valued at up to $2.4 billion. Cambridge, Massachusetts-based Orna had previously raised over $320 million in venture funding, per 91精品 data.

Last June, meanwhile, pharma giant snapped up , a biotech advancing in vivo engineering of cells through RNA delivery, for $2.1 billion. San Diego-based Capstan had previously secured $340 million in venture funding.

Another big deal, announced in October, was 鈥檚 acquisition of , a Cambridge, Massachusetts-based developer of RNA medicines that reprogram the immune system in vivo, for $1.5 billion.

Of course, Kelonia鈥檚 purchase price dwarfs all its predecessors, and by a hefty sum. Under the terms of the agreement, Lilly will acquire Kelonia for $3.25 billion up front, plus up to $3.75 billion in subsequent payments tied to meeting clinical, regulatory and commercial milestones.

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This past quarter, funding to security- and privacy-focused startups dipped slightly on a sequential basis, but remained well above year-ago levels. Overall, investors put $4.9 billion into global companies in the space in Q1, per 91精品 , a comparatively solid performance relative to recent quarters, as charted below.

Round counts also held steady at just under 200 1, per 91精品 data. Of those, 13 were financings of $100 million or more.

Biggest funding recipients

The largest funding recipient in Q1 was , a consumer-focused privacy startup that closed on $375 million in Series B funding.

Two other companies raised $250 million Series B financings: , a provider of AI-enabled cybersecurity services, and , a cloud security provider.

For a broader view of large funding recipients, below we put together a list of 10 of the largest Q1 cybersecurity rounds.

AI is dominant trend

Not surprisingly, a majority of cybersecurity-related funding went to companies that are also in 91精品 AI-related categories. This coincided with a record quarter for AI-related funding overall, with the category capturing 80% of all global funding in Q1.

Acquirers were also attuned to AI. This included the quarter鈥檚 largest acquisition, 鈥檚 purchase of identity access management startup for a reported $740 million. Another big AI-related deal was 鈥� acquisition of agentic endpoint security provider for a reported $400 million.

IPO activity, meanwhile, was quiet, with no major cybersecurity-related offerings in Q1, per 91精品 data.

Looking ahead

We expect to see AI-driven investment continue to be a dominant theme for cybersecurity. And while Q2 has not yet brought us a cybersecurity megaround, the default assumption is this is only a matter of time.

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