and each launched multibillion-dollar deployment ventures staffed with forward-deployed engineers, while a long list of startups building AI infrastructure, autonomous software and robotics also reached unicorn status. Together, the new entrants point to where investors increasingly see value creation: turning AI advances into real-world applications and pairing software intelligence with physical automation.

Beyond AI, new unicorns were minted across many sectors including healthcare, quantum, aerospace, financial services, manufacturing, e-commerce and energy.听

China dominated in the robotics sector, while Canada did so in quantum. The single new legaltech unicorn last month was from Brazil. also joined the board this past month, as the adult creator content company raised its first external financing.听

Of the new unicorns, 17 are U.S-based, while four each are based in China and the UK. Two new unicorns joined the board from Canada, as one each from India and Brazil.听

Unicorn IPOs

The board鈥檚 total value is undergoing rapid fluctuations amid lofty new valuations for some of the largest new unicorns, as well as high-profile exits to the public markets.

The Unicorn Board reached $9.9 trillion in value in May, as Anthropic moved ahead of OpenAI to become the second most valued private company after . On the heels of the funding, Anthropic privately filed for an IPO, followed shortly thereafter by OpenAI’s .听

SpaceX is expected to list this Friday, in what would be the largest-ever IPO. Its listing will erase more than one-tenth of value from the board as the the -led company exits the private markets.听

Chip company went public in May in a blockbuster IPO that valued the company at $56.4 billion,听well above its last private valuation of $23 billion just three months earlier in February.听

New unicorns in May

Here are May鈥檚 new unicorn companies, including 10 companies that are less than 3-years old:听

AI deployment

• San Francisco-based raised a $4 billion private equity round led by with co-leads , and . The new company is majority owned by with partnerships with 19 investment firms and consultancies. OpenAI acquired , with its 150 forward-deployed engineers to support enterprises in this effort. The less than 1-year-old-based company was valued at $14 billion in the new funding, which it said will be used to scale operations and acquire companies.听
• raised a $1.5 billion private equity funding to build an AI services company to work with companies to bring Claude into their operations. Each of the co-leads 鈥� , private equity investor and legal firm 鈥斕齣nvested $300 million into the round. and also invested in the joint venture. The less than 1-year-old-based, San Francisco-based company鈥檚 valuation was not disclosed.
• , a company building search for AI agents, raised a $250 million Series C led by . The 5-year-old San Francisco-based company was valued at $2.2 billion and is used by coding agents, go-to-market agents and chat agents.听
• Boston-based autonomous AI software developer raised a $200 million Series A led by . Blitzy鈥檚 platform reverse engineers existing code bases to build a knowledge graph and thereby enable autonomous development of software projects over days or weeks that can re-engineer and test complicated systems and deal with technical debt. The 2-year-old company was valued at $1.4 billion and is said to be used by dozens of global 2,000 companies.听
• , a routing technology for applications to select from 400-plus models, raised a $113 million Series B led by Alphabet鈥檚 . Investors in the round included a host of corporate venture firms including , , , and . The 3-year-old New York-based company was valued at $1.3 billion.

搁辞产辞迟颈肠蝉听

• raised a $700 million Series A led by . The company plans to build personalized robotics developing its own models, training and hardware. The 1-year-old San Jose, California-based company was valued at $6 billion. It was founded by CEO , founder of humanoid robotics unicorn .
• Guangdong, China-based , a dual arm robotics developer, raised a $147 million Series B led by and . It said its new funding will be used for R&D, production and a global sales network. The 10-year-old company was valued at $1.5 billion.听

• Shanghai-based has raised four funding rounds since it was spun out of in January, and reached a valuation of $1 billion. Agilink is focused on dexterous hand technology. The funding will be used for model development, data and hardware with the spinout able to license to the broader robotics market.听
• , a robot leasing and rental platform, raised a Series A funding. The less than 1-year-old Pudong, China-based company was valued at $1 billion. It is looking to expand from event rentals to warehousing, logistics and park operations.听

贬别补濒迟丑肠补谤别听

• , a treatment provider for cardiovascular and orthopedic disease, raised a $1.5 billion corporate round led by . Boston Scientific has an option to acquire its heart valve technology. The 10-year-old Georgia, U.S.-based company was valued at $4.4 billion.听
• , a longevity biotech company, seeking to extend human life by a decade, with therapeutics targeting age related disease raised the initial close of funding round led by . The 5-year-old Redwood City, California-based company was valued at a pre-money valuation of $1.8 billion.听
• , launched a suite of AI agents for healthcare built from its clinical data, raised $146 million in equity and secondary funding led by . The 15-year-old New York-based company was valued at $1.6 billion.

Quantum computing

• Vancouver-based , a quantum computing company that combines silicon-based qubits with native photonic interconnects, raised a $70 million extension funding led by Luxembourg-based . Photonic raised $130 million in January. The 9-year-old company was valued at $2 billion.
• Quebec-based , which says it addresses quantum error correction in each qubit, raised a $30 million funding. The company has raised a mix of government grants and venture capital. The 6-year-old company was valued at $1.4 billion.

础别谤辞蝉辫补肠别听

• , a builder of rockets to deploy data centers in space, raised a $305 million Series B led by . The 2-year-old San Carlos, California-based company, formerly called Aetherflux, was valued at $2 billion. The company plans to launch its first satellite later this year. Its technology entails using the upper stage of the rocket as a low-earth orbit satellite that uses solar energy to create 1-megawatt data centers in space.听
• Hyderabad, India-based , a rocket company that delivers satellites into space, raised a $60 million funding led by Singapore-based and Menlo Park, California-based . Skyroot is planning the maiden voyage of Vikram-1 in June. The 7-year-old company was valued at $1.2 billion.

Financial services听

• , an AI insurance provider for startups, raised a $160 million Series B led by . The 2-year-old San Francisco-based company was valued at $1.3 billion and plans to go after the trucking industry next.听
• Intelligent wealth management platform raised a $150 million Series D led by . With in recruited assets, it is built to create an all in one system for advisors. The 7-year-old San Francisco-based company was valued at $1 billion.

惭补苍耻蹿补肠迟耻谤颈苍驳听

• , a manufacturer of aerospace and defense components, raised a $300 million Series B led by . The 1-year-old El Segundo, California-based company, which aims to strengthen America鈥檚 industrial base, operates six factories across the U.S. and was valued at $1 billion.
• , likewise says it is building out American manufacturing with a rapid custom manufacturing software to production platform. It raised its first institutional funding of $110 million led by , and founders and . The 7-year-old Reno, Nevada-based company supports small-scale inventors to large-scale enterprises and has shipped 30 million parts to 300,000 customers. The company was valued at $1 billion.

E-commerce

• , a real-time inventory management platform, raised a $170 million Series B led by and . Its sensor technology tracks items and its precise location and movement in the store. Retail customers include and . The 13-year-old New York-based company was valued at $1 billion.

• London-based , a booking service for hair salons, beauty experts and wellness salons raised a $80 million Series C led by . The 11-year-old London-based company was valued at $1 billion.

贰苍别谤驳测听

• , a nuclear fusion startup spun out of Tsinghua University, raised a $74 million Series A funding. The 4-year-old China-based company was valued at $1 billion.
• , a provider of fast charging batteries, raised a $60 million Series C led by strategic investor . The batteries are used in data centers, robotics, electric vehicles and grid infrastructure. The 7-year-old Cambridge, UK-based company was valued at $1 billion.

Social media听

• Creator platform raised its first external funding, a $535 million private equity round led by , which now owns around 16% of the company. The 10-year-old London-based adult content platform was valued at $3.2 billion. Its CEO noted the company has paid out since 2016.

Data center听

• Modular data center builder raised a $230 million Series B led by , and. In partnership with the company plans to build capacity for secure data centers useful for military and remote manufacturing environments. The 3-year-old San Francisco-based company was valued at $2.2 billion. Customer booking for fiscal year 2026 was up 540% from 2025.听

尝别驳补濒迟别肠丑听

• S茫o Paulo-based , a Brazilian AI legal platform to manage company litigation, raised a $100 million Series B led by that valued the 2-year-old company at $1.2 billion. Enter counts , and among its customers, who use its technology along with law firms to handle litigation paperwork and settlements. Around have been managed through the platform. led the Series A.

颁谤测辫迟辞肠耻谤谤别苍肠测听

• , a digital asset trader, raised a $150 million funding led by , UK bank Standard Charter鈥檚 fintech arm. The deal brings digital assets into banking and represents GSRs first strategic external investor. The 12-year-old London-based company was valued at $1 billion.听

厂别肠耻谤颈迟测听

• , a security platform built for an open-source automated coding environment, raised a $60 million Series C led by . The platform is adopted by companies including Anthropic, , , , and and supports 27,000 organizations. Its socket firewall product is free to block malicious packages. The 6-year-old Stanford, California-based company was valued at $1 billion.

Related 小蓝视频色情网页版 unicorn lists:听

• (1,785)
• (619)
• (160)
• (189)
• (118)
• (102)
• (921)
• (525)
• (241)
• (39)
• (486)

Related reading:

• Anthropic Files Confidentially For IPO听
• Active Startup Investors Didn鈥檛 Hold Back In May
• Anthropic Funding Pushed Startup Investment To Near-Record Levels In May As Exit Market Reopened听听

Methodology

The 小蓝视频色情网页版 Unicorn Board is a curated list that includes private unicorn companies with post-money valuations of $1 billion or more and is based on 小蓝视频色情网页版 data. New companies are as they reach the $1 billion valuation mark as part of a funding round.听

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.听

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

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

Please note that all funding values are given in U.S. dollars unless otherwise noted. 小蓝视频色情网页版 converts foreign currencies to U.S. dollars at the prevailing spot rate from the date funding rounds, acquisitions, IPOs and other financial events are reported. Even if those events were added to 小蓝视频色情网页版 long after the event was announced, foreign currency transactions are converted at the historic spot price.

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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 in a spendy mood this week, backing more than a dozen rounds in the multiple hundreds of millions. Of those, the biggest one went to spend-management platform , which closed on $750 million, followed by three $500 million rounds for companies in the AI and space tech sectors.

1.听, $750M, finance software: Spend-management software provider Ramp secured $750 million in a financing led by , , and . The round set a $44 billion valuation for the seven-year-old, New York-based company.

2 (tied).听, $500M, space tech: Redondo Beach, California-based Impulse Space, a developer of spacecraft and propulsion systems for transport, moving and orbital repositioning in space, raised $500 million in Series D funding. and led the financing which brings total investment to date to more than $1 billion.听

2 (tied).听, $500M, AI developer tools: Supabase, provider of an open source platform for developers and AI app builders, closed on $500 million in fresh funding. led the financing, which set a $10.5 billion valuation for the six-year-old, San Francisco-based company.

2 (tied).听, $500M, foundational AI: New York-based Flourish, a startup working on artificial intelligence models inspired by the human brain, raised $500 million in initial funding. Backers include , , and .

4.听, $465M, fusion energy: Helion, a startup with a mission to build the world鈥檚 first fusion power plant, picked up $465 million in Series G funding led by at a $15.5 billion post-money valuation. The round brings total reported funding for the Everett, Washington-based company to at least $1.5 billion, per 小蓝视频色情网页版 data.听

5.听, $435M, longevity medicines: NewLimit, a developer of medicines designed to restore youthful function in old cells through epigenetic reprogramming, closed on $435 million in Series C funding. led the financing for the South San Francisco, California-based company, which was co-founded by CEO .

6 (tied). , $400M, AI for music: Suno, a provider of AI tools for making music, raised $400 million in Series D funding led by . The round set a $5.4 billion valuation for the company, which is currently facing lawsuits from multiple music labels for training its AI on copyrighted materials.

6 (tied). , $400M, robotics: Generalist AI, a startup focused on using AI to enable robots to do complex tasks, picked up $400 million in new funding led by . The financing reportedly set a $2 billion valuation for the two-year-old, San Mateo, California-based company.

9. , $350M, AI enterprise software: AlphaSense, an AI-enabled market intelligence and workflow orchestration platform, closed on $350 million in a new funding round led by , , and , , and . The round set a $7.5 billion valuation for the New York-based company.

10. , $300M, defense tech: Defense tech startup Mach Industries raised $300 million in Series C funding at a $1.8 billion valuation. and led the financing for the three-year-old, Huntington Beach, California-based company.

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Legal tech funding is booming, but the money isn鈥檛 spreading evenly across the market.

Last year, 小蓝视频色情网页版 News reported that legal tech startup investment was riding high as investor enthusiasm for AI reshaped legal software funding, citing a report estimating that 44% of legal work could eventually be automated. That concentration has helped create one of the clearer success stories in legal AI 鈥� and may also be obscuring an adjacent market that remains far less developed.

Using disclosed funding totals for a selected group of plaintiff-side legal AI companies, the imbalance is hard to miss.

EvenUp has raised $370 million, $164 million, $85 million, and Darrow $63 million, for a combined total of roughly $682 million. Plaintiff-focused companies account for about 71% of disclosed capital for legal AI, suggesting investors have found a part of the sector where adoption, workflow clarity and venture-scale narratives already line up.

That investor interest is not difficult to understand. Plaintiff firms tend to share more standardized workflows around client intake, case evaluation, medical review and demand generation 鈥� all areas where AI can automate repetitive work and improve throughput. As those firms have adopted software, the category has become easier to understand, distribute and fund.

The underserved side: legal defense

The defense side, by contrast, remains underdeveloped and may present the next big opportunity.

Corporate legal departments and the law firms managing high-volume defense work still rely heavily on fragmented systems, spreadsheets, email-based coordination and outside counsel processes that were not designed to produce portfolio-wide visibility. For companies facing hundreds or thousands of active matters, litigation is often still run more as a services function than a software-enabled one.

That creates a sizable but harder-to-package opportunity. Retailers, insurers, healthcare systems and financial services companies can each manage large litigation portfolios, yet many still lack a unified view of case risk, settlement patterns, legal spend and outside counsel performance. The need is not new. What has been less clear is whether a venture-backable software category could be built around it.

Part of the reason defense-side legal AI has lagged is structural. Workflows vary widely by industry, matter type and regulatory context, making the market less standardized than plaintiff-side practices. Buying decisions also tend to run through general counsels, legal operations teams and outside counsel relationships, which can lengthen sales cycles and make the category look less immediately viable to investors.

But a shift is underway. Last fall, 小蓝视频色情网页版 News reported that legal tech funding reached record highs in 2025, reinforcing how quickly investor attention has shifted toward AI-enabled legal workflows. As plaintiff-side firms get faster at sourcing, valuing and prosecuting claims with software, the operational pressure on defense teams mounts. At the same time, AI is making it more feasible to turn messy litigation workflows into systems that can surface comparable matters, flag risk earlier and benchmark outcomes across portfolios.

From an investor perspective, that makes defense-side litigation AI look less like a niche and more like an underbuilt segment of a broader legal software market. If plaintiff-side investment reflects where legal AI has already become easy to fund, defense-side infrastructure may represent where the next category still has room to form.

Investors, take notice

For venture capitalists, this is the kind of asymmetry worth watching: a large enterprise market with measurable pain points, improving technical feasibility, and no entrenched category leader yet. What investors should watch is whether startups in the category can pair proprietary outcome data with repeatable enterprise adoption 鈥� the combination most likely to produce a durable category leader.

One emerging approach on the defense side is exposure and settlement benchmarking: using historical resolution data to estimate settlement ranges, legal spend and case risk across similar matters. In practice, that can mean comparing claims by jurisdiction, plaintiff firm, claim type or other operating variables to help in-house teams make faster and more consistent decisions.

If the category scales, one potential moat may come from proprietary outcome data. Defense-side settlement details, matter economics and resolution patterns are often difficult to reconstruct from public records alone.

A platform that aggregates and normalizes those signals across customers could build a data asset that becomes more useful with scale 鈥� a familiar dynamic in vertical software, and a potential early signal for investors of durable advantage in defense-side legal AI.

There is still no clear, scaled, venture-backed winner built specifically around defense-side litigation intelligence. For startup and growth investors, that makes the segment less a settled market than an open question: whether one of legal AI鈥檚 next durable companies will emerge not from the workflows that have already attracted the most capital, but from a large enterprise category whose software stack is still taking shape.

听 is CEO and co-founder of , which builds AI-powered litigation intelligence for corporate defense teams and law firms.

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Related reading:

• Legal Tech Startup Investment Is Riding High, Thanks To AI Boost
• EvenUp, AI Software For Personal Injury Law, Doubles Valuation To $2B As Legal Tech Funding Hits Record High
• Highest Count Of New Unicorns Join 小蓝视频色情网页版 Board In Over 3 Years As Exits Also Gain Steam
• Wheels Of Justice Slow To Accept Legal Tech As Funding Falls

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A grab bag of funded startups caught our attention this past month, from a previously bootstrapped custom metal manufacturer that got its first outside funding from big-name Silicon Valley backers, to a startup that aims to provide geothermal energy from underwater volcanoes to small island nations. Let鈥檚 take a look.

$110M for on-demand custom manufacturing

First, let鈥檚 start with a refreshingly non-AI round, and a sizable one at that.

Reno, Nevada-based said last month that it has raised $110 million in funding led by brothers and founders and , along with and , at a $1 billion valuation.

The company operates an on-demand manufacturing platform specializing in custom-cut metal and fabrication. The round is its first venture investment, and apparently came only after Sequoia’s flew to Reno to woo SendCutSend CEO into accepting Silicon Valley backing. Previously, Belosic had bootstrapped the company, founded in 2018, with personal savings, bank loans and credit cards, he told .

He held little interest in taking cash from startup investors until SendCutSend started to be flooded earlier this year with orders from AI-driven industries including robotics and data centers, and Belosic said he realized the business needed outside investment to grow.

Investor of Paradigm told WSJ that underlying SendCutSend鈥檚 booming business is intense demand for rapid, on-demand sheet metal and custom parts. 鈥淚f you think about the entire frontier of robots, defense companies, rocket companies, electric-car companies, they all need very fast turn prototyping,鈥� he said.

The investment is Paradigm鈥檚 first into the manufacturing sector, he noted.

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$100M for insurance-covered metabolic health counseling

GLP-1 weight-loss drugs may be booming, but a well-funded startup is betting that medication alone isn鈥檛 enough to solve the chronic disease crisis.

, a New York-based metabolic health startup that combines dietitians, AI tools and GLP-1 medication management, last month said that it raised a $100 million Series C round led by . , , and a long list of other investors also backed the round, which brings the company鈥檚 total funding to date to just over $213 million, .

Founded in 2021, Nourish operates what it describes as the country鈥檚 largest dietitian-led metabolic health clinic, pairing more than 10,000 registered dietitians with AI coaching, lab testing and virtual care. The company has increasingly expanded into GLP-1 prescribing and medication management as demand for drugs such as Ozempic and Wegovy continues to surge.

Nourish said it has partnered with hundreds of health insurers in the U.S. and that its service is covered by most plans.

Its pitch is that the next phase of the GLP-1 boom will require more than prescriptions. While the drugs have transformed obesity treatment, many patients struggle to stay on them long term or maintain results after stopping, according to the company. Nourish is positioning itself as a broader metabolic health platform focused on nutrition, behavior change and ongoing clinical support alongside medication.

鈥淐hronic disease is the central failure of U.S. healthcare 鈥� nearly 200 million Americans affected, trillions spent, and outcomes that still don’t move,鈥� Menlo Ventures partner said in a statement. 鈥淲hat Nourish has built in four years is remarkable: a care model that actually bends the cost curve, with 10,000 dietitians, deep payer relationships, and clinical outcomes patients stick with.鈥�

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$58M for Gen Z group travel adventures

Group travel startups are having a moment as younger travelers increasingly look for ways to meet people while exploring new destinations.

, a Milan-based startup that organizes group travel experiences for millennials and Gen Z travelers, raised a 鈧�50 million (roughly $58 million) Series C funding round as it looks to expand further across Europe and enter the U.S. market. The round was led by .

Founded in 2017, WeRoad operates a platform that connects solo travelers and small groups through curated multiday trips led by coordinators. The company says it has served more than 300,000 travelers across over 1,000 itineraries, with offerings ranging from adventure travel and cultural experiences to outdoor excursions. Participants are typically grouped with strangers in similar age ranges, turning the trips into a hybrid of travel booking and social networking.

鈥淲e live in a time when artificial intelligence and social media are reshaping the way we connect with each other. And amid all this digital connection, real human connection has become increasingly rare. Around 30% of young adults say they feel lonely every day. In the United States, this phenomenon is especially significant,鈥� the company said in a statement. 鈥淲e believe we have an answer. Not the only one, not a perfect one, but a real one: putting people in a room together (or on a quad bike in Morocco, in a canoe in Vietnam, or in front of a sunset in Patagonia) and letting whatever is meant to happen, happen.鈥�

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$26M to keep AI data centers cooler

AI may be driving the data center boom, but keeping those facilities cool is becoming a business opportunity in its own right.

, a U.K.-based startup developing precision liquid cooling systems for AI infrastructure, said last month that it raised a $26 million Series B as demand surges for technologies that can manage the growing heat and power requirements of next-generation AI data centers. The round was led by and and brings Iceotope鈥檚 total funding to date to just under $100 million, .

Founded in 2005, Iceotope has developed a chassis-based liquid cooling approach designed to replace traditional air cooling and cool entire systems rather than individual chips. The company says it now holds 219 granted and pending patents. It said it will use the new funding to expand product and engineering development, grow its patent portfolio and accelerate partnerships that bring its cooling technology to market.

The raise comes as AI workloads create mounting challenges for conventional cooling systems. Iceotope argues its technology can reduce energy consumption and water use while supporting high-density AI and high-performance computing deployments in both data centers and edge environments.

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$25M for geothermal energy from subsea volcanoes

As AI companies scramble for more electricity, investors are increasingly willing to fund some unconventional ideas for generating it. One of those is , a Seattle-based startup developing subsea geothermal power systems designed to tap into heat generated by subsea volcanic activity.

The company recently raised between $25 million and $30 million in a seed round led by , sources familiar with the matter .

Founded just last year, Endurance Energy is targeting island nations 鈥� where it says electricity can cost almost 7x as much as in the U.S. 鈥� industrial sites and eventually hyperscale data centers that need large amounts of reliable power.

Unlike solar and wind, geothermal energy carries the promise of round-the-clock, renewable baseload electricity, a feature that has become increasingly attractive as AI infrastructure drives soaring power demand.

Endurance says its seafloor geothermal generators could deliver gigawatts of power from hydrothermal systems along tectonic plate boundaries and volcanic regions. It is , where about 80% of electricity generation still relies on imported diesel fuel.

Earlier this year, the company signed an agreement with the Tongan government and launched a pilot project aimed at harnessing geothermal heat generated by subsea volcanic activity around the island nation.

鈥淐lean geothermal power will enable us to substitute most of our diesel base load power and further insulate ourselves from future external shocks caused by geopolitical conflicts and global economic impacts,鈥� Tongan Prime Minister Lord Fakaf膩nua said in a statement.

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That trend is reflected in the May tallies for most active investors. 小蓝视频色情网页版 data showed top dealmakers weren鈥檛 setting any records for deal count. However, they wrote some enormous checks for those they did back.

Familiar names dominated the most active investor ranks, including regulars on our list like , and . The highest spending investors, meanwhile, included lead backers in 鈥檚 massive Series H last week.

For a more granular view, we broke out ranks below by category, including active lead backers, highest spending investors, and most prolific venture dealmakers.

Busiest lead investors

General Catalyst and Andreessen Horowitz were the most active lead investors in May, leading or co-leading six rounds each. This included some exceptionally large deals, such as 鈥檚 $5 billion Series H, co-led by Andreessen, and Cognition鈥檚 $1 billion Series D, co-led by .

was the next-busiest lead investor, with five deals, followed by and , with four rounds each. For a broader perspective, below we chart out the 10 most active lead investors by deal count:

Highest spending lead investors

Of course, the most prolific dealmakers aren鈥檛 always those leading the largest rounds. For May, investors who led deals with the highest aggregate value were all co-lead backers in Anthropic鈥檚 massive $50 billion Series H. This included , , , and , along with , , , , and which co-led the investment.听

Next on the list were and Andreessen Horowitz, which co-led Anduril鈥檚 $5 billion fundraise. To complete the picture, below we rank the 17 investors who led or co-led May rounds with the highest aggregate value.

Most active venture dealmakers

When we stop focusing exclusively on lead investors, the list of most active dealmakers changes up some, but not dramatically.

The most active investors in rounds of $5 million or more for May include , Andreessen Horowitz, and General Catalyst. Y Combinator typically ranks high on this list, as it commonly co-invests as a non-lead investor in follow-on rounds for startups it incubated.

For a broader picture of most active venture backers, below we ranked the top 10 for May.

Same dealmakers, bigger rounds

Overall, May鈥檚 active investor tallies painted a picture of a startup funding scene still dominated by familiar names.听

Given the huge funds raised in recent years by big-name venture and growth investors, it鈥檚 no surprise to see them putting capital to work. Increasingly, they鈥檙e doing that in the form of larger rounds, with capital flowing in particular flowing to consensus picks in AI.

Related reading:

• Anthropic Funding Pushed Startup Investment To Near-Record Levels In May As Exit Market Reopened听听

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Operating as an 鈥渁ll-in-one鈥� software ecosystem, Scotch provides liquor retailers with point-of-sale hardware, custom software, payment processing and a back-office suite to manage state-by-state regulatory complexities. Customers range from boutique single-register shops to enterprise stores running over a dozen lanes.

led Scotch鈥檚 Series A raise, which included participation from , and . The injection of capital comes on the heels of a growth spurt, with the Denver-based startup reporting greater than 500% year-over-year growth and surpassing $1 billion in processed payment volume.

While the company declined to reveal its valuation, co-founder and CEO said the funding marks 鈥渁 significant step-up鈥� from its $10 million seed round, raised in September 2024 and led by First Round Capital.

Old-school market

Formally incorporated in January 2024, Scotch was born out of a unique industry challenge encountered by Bolling and CRO during their previous venture, . A convenience-store software company that supported 15,000 stores across the U.S., Skupos attracted attention from major consumer packaged goods giants such as , and Budweiser owner .

鈥淏udweiser, in some way, shape, or form, tried to get us not only to continue to grow our C-store business, but to also expand into the liquor store industry,” Bolling told 小蓝视频色情网页版 News in an interview.

Market research conducted in 2022 revealed a striking contrast between the two sectors. While the $650 billion convenience store market is highly fragmented, its point-of-sale technology is heavily consolidated around four major players.

Conversely, the liquor-store industry proved to be an entirely different beast: highly fragmented, intensely regulated and flooded with more than 200 regional, legacy POS systems.

Recognizing that the Skupos business model didn’t align with that level of fragmentation, the founders held off. Following the acquisition of Skupos by in August 2023, the team revisited the concept.

Drawing inspiration from the business model of restaurant tech giant 鈥� with whom the founders frequently shared strategy notes in the mid-2010s 鈥� they recognized the potential to replicate that success in a highly specialized, nuanced retail market.

, former chief architect of (acquired by for more than $1 billion), serves as Scotch鈥檚 CTO.

鈥楤usiness in a box鈥� strategy

The platform鈥檚 business model scales directly with the merchant, driving revenue through a hybrid mix of SaaS fees, charged on a per-device, per-month basis; fintech monetization, or collecting standard interchange fees on its payment volume and hardware sales, providing the modern storefront terminals necessary to run the infrastructure.

While general retail giants like Lightspeed and exist, Scotch markets itself as the only player capable of handling the severe operational and compliance hurdles distinct to alcohol retail.

Customers include The Liquor Store of Jackson Hole, Big Bear Wine & Liquor, Corkdorks and Everest Spirits Superstore.

Eradicating the 鈥榯oil鈥� via AI

With inventory sizes ranging from 2,000 to 12,000 distinct products per store, manual inventory and vendor management can lead to miscalculated ordering and tied-up working capital, noted Bolling.

Scotch says it differentiates itself by building artificial intelligence directly into these back-office workflows. The platform uses AI to eliminate administrative friction, with the company claiming its offering can save business owners over a full day of work per week. It also saves them money by giving them, for example, a more accurate picture of their inventory, according to Bolling.

鈥淲e’ve really focused our AI workflows on the ‘toily’ aspects of running one of these businesses,鈥� Bolling said. “Some of our customers are sommeliers who opened a store because they are passionate about serving their community with the right wine curation. That鈥檚 their creative outlet. We try to take up the parts of the day that suck for these business owners.鈥�

By optimizing supply chains and automating store management, Bolling believes that Scotch鈥檚 AI native architecture is driving 鈥渕easurable鈥� gross margin expansion for its merchants.

Grassroots growth and word of mouth

Because it is targeting an industry historically dominated by 鈥渙ld-school,鈥� family-owned, mom-and-pop operations, Scotch has employed an unconventional go-to-market approach. The company relies on a dual strategy of targeted geographic inside and outside sales reps as well as localized trade association partnerships. The reasoning behind that approach, according to Bolling, is because liquor store owners rarely search for new POS hardware on a whim.

However, the startup’s fastest growth vector over the last six months has been organic word of mouth. Because many state laws cap the number of liquor licenses an individual can own, competitive hostility is low, creating tight-knit networks of friendly competitors.

“They go to the same industry events, they talk to each other, they are in study groups together,” Bolling noted. “When one of them adopts a system like Scotch, they refer a lot of other customers our way.”

Scotch currently has about 45 employees working out of its Denver headquarters. It plans to use its new capital in part to scale its engineering and sales operations across the United States in addition to accelerating product development.

Going after 鈥榯he hard part of the market first鈥�

, general partner at VMG Partners, believes that Scotch is modernizing 鈥渙ne of the last major categories of retail.鈥�

鈥淭he beverage alcohol market is nearly $250 billion and, despite that, is still operating on systems built in the 1970s with on-prem servers,鈥� he wrote via email. 鈥淚t isn鈥檛 an exaggeration to say Scotch is the only player that has solved enterprise-level complexity.鈥�

Most industry startups never moved beyond basic solutions for small businesses, believes Stenmark.

鈥淪cotch went after the hard part of the market first, solving for some of the largest and most complex retailers in the country,鈥� he wrote via email. 鈥淭his approach allowed them to harden their product early, and has translated to them having the only product that can actually solve every business operations and payments problem a retailer might have, whether they be a national brand or a beloved regional storefront.鈥�

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All told, global venture funding reached $92 billion in May, marking the second-largest monthly total on record, just behind February, 小蓝视频色情网页版 data shows. Of that, Anthropic raised $50 billion听1 , or 54% of the month鈥檚 total funding.

Startup funding was up 284% year over year from $24 billion, per 小蓝视频色情网页版 data.

The month also had a successful IPO for a venture-backed company as chip company Cerebras, which has benefited from growing demand for AI inference, went public at the upper end of its range at $185 per share and opened at $350. The stock is currently trading around $225 as of June 2, which values the company at just over $49 billion.

On the valuation front, Anthropic rocketed ahead of on The 小蓝视频色情网页版 Unicorn Board as it became the second-most highly valued private company at $965 billion, just behind at $1.25 trillion. Just months earlier in February, Anthropic was valued at $380 billion. The board has shot up in value in recent months and has 1,780 companies altogether valued at $9.9 trillion as of the end of May.

Billions more

Last month, a further $17 billion was raised by 10 companies in rounds of $500 million and above. They include defense tech unicorn , which raised $5 billion, and China-based AI labs and , which each raised more than $2 billion having raised rounds earlier this year. Automated coding lab raised $1 billion, and , which develops AI for customer service, raised $950 million in a single round.

Funding to the AI sector totaled $72 billion, or 79% of funding, last month.

The boom funds itself

The Cerebras IPO sets the stage for further public listings, including potentially record-setting ones.

SpaceX publicly filed its prospectus in May, stating its intention to raise $80 billion via its IPO. The space tech giant has raised $9.4 billion in equity funding to date, per 小蓝视频色情网页版.

Anthropic, which is set to beat OpenAI to the public markets after filing its confidential IPO paperwork on June 1, has raised $125 billion in equity funding thus far, compared with its rival鈥檚 roughly $180 billion in private funding.

The private markets in 2026 have raised capital at a greater pace than ever before, thanks to听 larger rounds, faster follow-on fundings and record-breaking valuations. At the same time, if SpaceX, Anthropic and OpenAI all list this year, as they鈥檝e said they intend to, the resulting liquidity could be the largest in market history, pouring hundreds of billions back into the hands of startup investors who will redeploy it into the next wave of private companies.

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Methodology

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

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

Please note that all funding values are given in U.S. dollars unless otherwise noted. 小蓝视频色情网页版 converts foreign currencies to U.S. dollars at the prevailing spot rate from the date funding rounds, acquisitions, IPOs and other financial events are reported. Even if those events were added to 小蓝视频色情网页版 long after the event was announced, foreign currency transactions are converted at the historic spot price.

Glossary of funding terms

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

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

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

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

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How times have changed. Already this year, more than $14.6 billion in venture investment has gone into companies in 小蓝视频色情网页版鈥檚 military, national security and law enforcement categories, blowing past the sector’s previous annual record of $9.6 billion raised in all of 2025.

Investors have poured billions into startups developing AI-powered military systems, autonomous vehicles, defense software and space technologies, and they’re writing increasingly large checks to do it, 小蓝视频色情网页版 data shows.

Funding growth accelerates

The defense tech sector’s rise has been years in the making

Global defense tech funding totaled $1.6 billion in 2020 before climbing to $3.9 billion in 2021, 小蓝视频色情网页版 data shows. Funding then remained relatively steady between roughly $2.8 billion and $3.8 billion from 2022 through 2024.

That changed dramatically last year, when funding jumped to a record $9.6 billion. Now, five months into 2026, startups in the sector have already eclipsed the full-year record set in 2025.

Deal flow has stayed steadier, mirroring a broader trend of venture capital concentration. So far this year, defense tech startups have announced 107 venture rounds, 小蓝视频色情网页版 data shows, putting 2026鈥檚 pace slightly ahead of the 206 deals done in 2025.

Megarounds lead the way

The biggest contributor to this year’s funding surge, by far, is .

The Costa Mesa, California-based company announced a $5 billion Series H last month, a deal that valued it at $30.5 billion and further cemented its status as the most valuable venture-backed defense startup in the world.

Still, it鈥檚 not the only defense- or military-related startup drawing large sums of funding. Many of this year’s biggest rounds involve companies building AI-enabled defense systems, autonomous aircraft and maritime vehicles, military software platforms and space infrastructure.

Case in point: a $300 million Series C round announced today for , an autonomous drones systems manufacturer. The round was led by and and values the Huntington Beach, California-based startup at $1.8 billion.

Autonomous aviation startup raised a $2 billion Series G round in March led by and, while , which makes unmanned surface vessels for naval and defense use, secured a $1.75 billion Series D led by later that month.

Space-related startups with defense applications have also been especially prominent among defense-tech bets this year. , and , rank among the largest defense-related funding recipients of 2026, highlighting continued investor interest in technologies with both commercial and national security applications.

Attention turns to exits

As funding totals climb, investors may begin looking toward exits. Already this year, one smaller defense-tech startup, AI drone company , went public, with shares soaring more than 500% in their first day of trading. They remain near the high end of their price range as of early June.

Anduril is now widely viewed as one of the most likely defense tech candidates to pursue an IPO in the coming years. A public offering by a company of its size would mark a significant milestone for the sector and provide a closely watched test of public-market appetite for next-generation defense contractors.

Other well-capitalized companies across defense, autonomy and space are also reaching a scale where public listings or major acquisitions become more plausible, with 小蓝视频色情网页版鈥檚 predictive intelligence tools forecasting that nearly four-dozen . Along with Anduril, they include True Anomaly, Shield AI, Sierra Space and .

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The market believes software businesses can鈥檛 charge premiums anymore and it predicts slowing growth indefinitely.

There are two reasons. First, AI powers a 10x decrease in software production costs. Second, these AI capabilities enable a huge wave of new competitors, both VC-funded startups and in-house solutions.

Reduced software production costs and rising competition, they say, will eliminate software鈥檚 pricing power. Public software stocks traded down 20% this year through mid-May, and for the first time in history, software trades at a discount to the average S&P500 multiple on earnings. SaaS is dead.

It is true that AI has brought falling costs and rising competition. But it does not follow that SaaS is dead. Lowering the cost to produce software does not mean that software revenue will shrink. In fact, history suggests the opposite.

In certain cases, efficiency begets consumption. This is the lesson of the . It worked for coal engines, it worked for data centers, and it will also work for AI-powered software.

The Jevons Paradox

Let鈥檚 start with coal. In 1860s Britain, many worried about burning through the country鈥檚 coal resources too quickly. Conventional wisdom said that developing more-efficient coal-burning engines would make the coal last longer.

But economist William Stanley Jevons recognized that more coal-efficient engines would cause an increase in demand for coal energy with the result that Britons would burn through their coal more quickly, not less.

Jevons was right. When greater efficiency produced lower costs, it also unlocked enormous new demand. This consumed coal reserves faster, not slower.

Twenty-five years ago, I joined a buyout firm during the 2001 dot-com crash. My first investment was in a troubled datacenter company. Exodus Communication, which reached a peak market cap of $32 billion, then went through bankruptcy twice as datacenter demand continued to fall.

In 2004, I recommended that our firm acquire that datacenter business out of the second bankruptcy for $200 million and merge it into a competitor named Savvis.

At the time, the market considered datacenters a shrinking industry. Dot-com companies were pulling racks of servers out of the sites, and datacenter floors were emptying out. Industry analysts forecast that given Moore鈥檚 law about the exponential growth of chip capacity and increasing server power density, a single rack in 10 years would deliver what it took 100 racks to deliver in 2005, and that in 20 years, a rack would deliver what 10,000 racks delivered in 2005. Conventional wisdom said that more-efficient chips would require less datacenter floorspace over time.

Our thesis that demand for datacenter floorspace would grow was not a popular opinion at the time. If 10,000 racks in 2005 would be replaced by just one rack in 2025, didn鈥檛 the U.S. have plenty of datacenter floorspace already?

was running advertisements showing a room full of servers replaced by one mainframe. One skeptical investment committee member told me that this business had been through bankruptcy twice in two years, and that if it went through a third time, I would go with it.

Today, one rack can indeed deliver 20,000x the compute power of racks from 2005, and as everyone knows, far from having too much floorspace, we can鈥檛 build new datacenter capacity fast enough. Truly enormous latent demand for computing power was unlocked as rack efficiency increased. The Savvis story ended well too, sold six years later for $3.2 billion.

The Jevons Paradox was true for coal, and it was true for data centers. It will also be true for AI-supported knowledge work.

Knowledge work and market expansion

Twenty-five years ago, only the wealthy had access to personalized investment advice. In 1996, Nobel Laureate Bill Sharpe co-founded to bring personalized investment advice to anyone with a 401(k).

My firm was an investor, and I had the privilege of working closely with the company. At first it tried to sell advice about how to invest 401(k) funds, but only about 20% of employees were interested in taking advice and then managing their 401(k) positions themselves.

Financial Engines鈥� breakthrough innovation was to manage the 401(k) positions directly, not just advise. Employees could check a box: 鈥渄o it for me鈥�. The demand from people who previously had no access to this advice was beyond all expectation and did enormous good. I recall that an early customer was , whose tens of thousands of employees with an average age of 27 years had approximately 40% of their 401(k) monies in cash, 40% in stock of JCPenney (which would eventually file for bankruptcy in 2020), and 20% in everything else. Just moving them into sensible low-cost mutual funds appropriate to their age and other financial goals generated huge benefits.

Financial Engines went from zero to $169 billion in assets under management when it was acquired in 2018 for $3 billion.

The company delivered a service that is very similar to what we today would call agentic AI. The customer (an employee with retirement savings) was delegating a decision (invest my money) to a computer system, and the employee paid in a way tied to the outcome (~50 basis points on AUM).

Of course, the technology to deliver this was quite different, and this was a very narrow application. The lesson remains: Software enabled a massive efficiency in delivering knowledge work (in this case individual investment advice) and a huge latent market appeared to buy the service.

The end of the rationing of knowledge work

The increased cost efficiency of AI, like the increased cost efficiency of Financial Engines鈥� algorithms, allows demand to increase because it relaxes a supply constraint on knowledge work.

Across human history, even to today, knowledge work has always been rationed because it is supply constrained.

Knowledge workers take years of education and training, tend to want to live in high-cost places, over time want to work on only certain kinds of problems they find interesting, and require a lot of management to get along. That is why we pay them such high wages and do everything we can to make them more productive.

Business software is a tool to make knowledge workers more productive. The total business software market in the U.S. is on the order of $0.5 trillion per year, according to Gartner. The U.S. market for knowledge work, that is the amount paid to the 100 million knowledge workers in this country, is roughly $10 trillion, per numbers. Currently, we spend about 5% of the cost of knowledge workers on software tools to help them.

AI enables software companies to not just sell tools to knowledge workers, but to begin to sell the knowledge work outcomes themselves, as I have written about in prior 小蓝视频色情网页版 articles.

Put those together: 90% cost compression in software development plus the ability to sell knowledge work. We know there is a huge latent demand for knowledge work, if only it were not so expensive and hard to access.

For the first time, millions of people and businesses who have never had access to a strategist, an analyst, a lawyer or a financial adviser are about to get one.

Software is far from dead. The increase in efficiency offered by AI will allow it to do much more for less, and just like a more efficient coal engine or data center, this will unlock huge latent demand for knowledge work.

Ultimately, this will increase revenue and the strength of software businesses that use AI to further improve knowledge workers鈥� productivity or deliver knowledge work outcomes directly. Software鈥檚 job today is to solve the problem of delivering this safely and reliably.

It was no small task for industry to learn how to manage knowledge workers who are human, and it will be just as big a task to learn how to manage those who are machine knowledge workers. That is the challenge.

But remember that today the market for knowledge work is 20x the size of the market for software. The scale of the prize for software companies is unlocking the latent demand for knowledge work that, if history is any guide, will dwarf today鈥檚 software market.

The market today fears that the efficiency delivered by AI will shrink the software industry. Exactly the opposite is true. AI will unlock massive latent demand for knowledge work, and the software market will explode. Long live software.

co-founded in 2014 and is managing partner. He has served on numerous private and public technology company boards, and currently is a director of , , , , and . Previously, he was a partner and member of the investment committee at . He also worked at and . Morse serves on the board of directors of and as member of the advisory board for the HMTF Center for Private Equity Finance at . He attended , graduating summa cum laude with a BSE, and , where he earned his MBA and was an Arjay Miller Scholar. Morse lives in Austin.

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The statement was light on details and did not specify the planned offering size or where it will list. For its most recent funding round, a $65 billion Series H funding announced last week, the San Francisco company more than doubled its post-money valuation to a staggering $965 billion.

With that round, Anthropic also surpassed its closest rival, , in terms of last reported valuation. In February, OpenAI announced it had closed a $110 billion round at an $840 billion post-money valuation.

Anthropic has now raised roughly $125 billion from investors, per 小蓝视频色情网页版 data.

The path to the public markets

The IPO filing marks an escalation in the race among generative AI behemoths to make it first to the public market. That said, it could still be while.

Before making its market debut, Anthropic must still receive a sign-off from securities regulators on its confidential filing. After that, it will need to submit its public filing, carry out its pre-IPO roadshow, and put the remaining pieces in place for an offering of this presumed magnitude.

How long could it take? It鈥檚 unclear, of course, but if we use as a proxy, things could proceed briskly. SpaceX, which is reportedly seeking a valuation of $1.8 trillion or more, submitted its confidential filing on April 1. The company is expected to begin trading this month, with multiple reports citing June 12 as the target date.

If Anthropic follows a similar timeline, we could potentially see a market debut in August. Before that, however, will be the public filing of its IPO prospectus, which will offer a long-awaited peek under the hood at Anthropic鈥檚 famously fast revenue growth and the scope of the capital expenditures it has taken to get there.

As someone who has used the word boring in IPO market headlines many times in the past, one thing that can assuredly be said is that word no longer applies.

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