Among the top 50 private companies globally, the US and China account for 86% of the list, while AI startups represent 40%. These companies are reshaping industries and, in some cases, surpassing their public market competitors in valuation. 

OpenAI is reportedly poised to hit a roughly $500B valuation — putting it closer to the ranks of big tech than any other startup. At the same time, the current top 50 companies’ combined valuation represents under half of Nvidia’s current market cap of $4.3T, underscoring the relative scale of public tech giants.

Using CB Insights data, we analyzed the top 50 most valuable private companies globally to identify where value creation is happening in private markets. Below are the key patterns emerging from the group.

Track all 1,200+ unicorns

Key takeaways

• The United States and China dominate the global unicorn landscape, representing 86% of the top 50 companies. The US leads with 35 companies (70%), while China contributes 8 companies (16%), showing how concentrated tech innovation and capital formation remains within these two tech regions. The remaining 6 countries — Australia, France, Germany, Singapore, Sweden and the UK — each have only 1-2 representing companies.
• AI companies represent 40% of the top 50, signaling the market’s confidence in AI as a primary driver of economic value. These companies range from the big names building foundation models like OpenAI and Anthropic to specialized players tackling applications like defense systems (Helsing, Anduril).
• Abundant private funding enables companies to delay going public while continuing to scale. Today, startups are going public an average of 16 years after being founded, 4 years later than just a decade ago. Databricks recently surpassed its public competitor Snowflake in valuation ($100B) at its recent $1B Series K round. Meanwhile, ByteDance ($300B valuation), generated more revenue than Meta in Q1’25 while staying private. With plenty of private capital available and employees able to sell shares on secondary markets, companies can grow much larger without going public.
• Secondary transactions are increasingly driving valuations, with 7 consecutive quarters of YoY growth in transaction activity among VC-backed companies. Recent secondary sales at companies like Canva (valued at $42B, up from $32B in 2024), Revolut (valued at $75B, up from $45B), and OpenAI’s upcoming $10.3B secondary sale at a rumored $500B valuation demonstrate this trend. As startups stay private for longer, secondary sales are providing both liquidity and fresh valuations. 

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The individual tools for agentic commerce, including AI models, data, selling platforms, and payment rails, remain fragmented. But partnerships will be necessary to stitch them into seamless customer journeys. Tech leaders, with their distribution power and financial infrastructure, are best positioned to control this shift.

Our analysis of CB Insights partnerships data across the major big tech and AI leaders found that 4 companies — OpenAI, Perplexity, Google, and Shopify — have emerged as gravitational centers. The 4 companies have struck 30+ partnerships in AI and agentic commerce over the last 2 years, compared with just a handful across the other tech leaders (Amazon, Anthropic, Apple, Meta, Microsoft, and NVIDIA). 

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To create the 2025 list, we analyzed 10 years of CB Insights’ Business Graph data, evaluating 12,000+ venture firms on portfolio outcomes (unicorns and exits), share of rounds led, portfolio quality via Mosaic Score, capital efficiency, and entry discipline. Smart Money VC portfolios offer a front-row view of where the sharpest investors are placing their bets. Use the list as an early indicator to spot emerging markets and promising founders.

Which VC firms are on the Smart Money list?

Firms are presented in alphabetical order.

1. Accel
2. Andreessen Horowitz
3. Bain Capital Ventures
4. Battery Ventures
5. Bessemer Venture Partners
6. Felicis
7. First Round Capital
8. Founders Fund
9. General Catalyst
10. Google Ventures
11. Greylock Partners
12. Index Ventures
13. Institutional Venture Partners
14. Kleiner Perkins
15. Lightspeed Venture Partners
16. Meritech Capital Partners
17. New Enterprise Associates
18. Norwest Venture Partners
19. Notable Capital
20. Redpoint Ventures
21. Salesforce Ventures
22. Sapphire Ventures
23. Sequoia Capital
24. Spark Capital
25. Thrive Capital

CBI customers: See Smart Money’s latest bets

How Smart Money VCs are outperforming the market

Our 2025 edition of Smart Money VCs:

• 6.5x more likely than the average VC to back a future unicorn
• 2.2x more exits per firm, either through M&A or IPO
• 2.3x higher share of rounds led, shaping pricing and syndicates

Smart Money syndicates amplify signal. The top pairs share dozens of portfolio companies — Sequoia & Andreessen Horowitz (43), General Catalyst & Andreessen Horowitz (42), and Sequoia & Lightspeed (36). Most widely backed across the cohort: Chainguard, Figma, and Wiz (each with 7 Smart Money backers).

Smart Money firms have also been the dominant backers of the AI wave — they backed 52% of new AI unicorns in 2023, 73% in 2024, and 77% in 2025 YTD — and that exposure is translating into outlier outcomes.

Since 2015, Smart Money VCs have backed 80 companies that exited at $10B+ — roughly 100x the $100M median exit. The largest Smart Money exits include Uber ($75.5B, 2019), Coinbase ($65.3B, 2021), and Coupang ($56.6B, 2021).

Mosaic shows where they’re headed next. Smart Money portfolios skew to higher Mosaic Scores — CB Insights’ 0–1,000 predictive rating of private-company health. The average portfolio Mosaic is 628 — about 2.6x the VC norm.

And the edge is most visible at the very top of the distribution: more than 65% of companies in the top 1% of Mosaic Scores are backed by a Smart Money VC. Top firms by average portfolio Mosaic include Meritech (759), IVP (741), and Thrive Capital (688). Standout companies in 2025 include Zepto, Bilt, Glean, Rippling, and Anthropic.

Where Smart Money is deploying now

Smart Money is still leaning into AI — especially agentic applications.

Over the last 18 months, agent-related categories led by deal count: coding agents and copilots (28 deals), agent development platforms (24), enterprise workflow agents and copilots (20), and legal agents and copilots (17). Infrastructure remained active as well, with 17 deals into LLM developers. Top recent AI deals by Mosaic include Glean (enterprise AI agents), Augment Code (coding AI agents), and ElevenLabs (voice AI).

Our M&A probability model points to cybersecurity as the most likely near‑term exit pool among Smart Money portfolios, with companies like Tenex.ai ranking highest. Activity is accelerating — highlighted by Google’s $32B acquisition of Smart Money–backed Wiz in March 2025. For acquirers, targeting Smart Money portfolio or syndicate companies can streamline diligence and post‑deal integration.

Outside the US, cybersecurity is also drawing Smart Money. Since Jan’24, Accel (84 deals), General Catalyst (64), and Lightspeed (55) are the most active by ex‑US deal count; their portfolios include companies like Tines, Cato Networks, and Torq.

Methodology

What is the CB Insights Smart Money list?

The Smart Money list is an unranked collection of the top 25 venture capital firms worldwide. We analyzed 12,000+ venture investors with 10+ unique portfolio companies using 10 years of CB Insights’ Business Graph data (2015–2025) to surface the highest performers via our Smart Money Index.

What makes a VC “smart”?

​​Comparable lists in other asset classes rank firms based on investment performance, but returns data is hard to come by in the VC world, and rates of return can be easily manipulated.

Our methodology factors:

• Portfolio outcomes — unicorn count/share and exit count/share
• Deal leadership — share of rounds led
• Portfolio quality — average CB Insights Mosaic Score
• Capital efficiency — portfolio value created per dollar raised
• Entry discipline — median stage at first check

Inputs were normalized and combined into the Smart Money Index. The top 25 became the 2025 Smart Money cohort.

What can I do with this collection?

Explore the Smart Money Expert Collection on the CB Insights platform to filter deals, build screens, and make faster decisions.

If you are a venture investor and want to submit data on your portfolio companies to allow us to better score you in the future, please reach out to researchanalyst@cbinsights.com.

RELATED RESOURCES FROM CB INSIGHTS:

• All 100 AI unicorns since ChatGPT launched
• State of Tech Exits H1’25
• The top angel investors in AI
• Are AI unicorns starting to move beyond hype?
• Book of Scouting Reports: Enterprise AI Agents

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Equity funding to drone developers has reached a record $5.5B already this year. More broadly, the drone market is projected to grow from $73.1B in 2024 to $163.6B by 2030, driven by defense spending, more permissive regulations, and AI advances that enable autonomous navigation, real-time object detection, and mission planning without human intervention.

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M&A volume stayed flat in the first half of the year, and the IPO market remained muted, though there are early signs of a potential second-half recovery. In the meantime, capital continues to flow into private tech companies at record levels, including a surge in secondary transactions. This is giving private tech companies more runway (and more reason) to delay public listings.

New exit models are also gaining traction. From large minority stakes to reverse acqui-hires, big tech companies are finding ways to access talent and technology without triggering regulatory review. These deal structures are starting to reshape how value is created, captured, and distributed across the ecosystem — for founders, investors, and employees alike.

Taken together, these trends point to a broader shift: private markets are becoming the dominant venue for value creation and capture in tech. With that comes the need for better private market investing infrastructure, including real-time data and context, turning private company intelligence into a new competitive advantage. 

Below, we break down the top stories from this first half of the year and our projections for the rest of the year, including:

• AI and $100M+ deals drive tech M&A momentum
• Signs point to tech IPO market rebound in H2’25
• Private tech markets top $2T in equity funding
• Secondaries get bigger and pricier
• New exit models emerge amidst the AI talent war

Download the full report to access comprehensive CB Insights data and charts on the evolving state of tech exits, in partnership with EquityZen.

Top stories in H1’25

1. AI and $100M+ deals drive tech M&A momentum

Tech M&A activity has remained stubbornly flat since Q4’23, stagnating at just over 2,000 transactions per quarter. We project Q3’25 to follow the same trajectory, with 2,040 deals.

Despite flat volume, this year is shaping up to be a record year in terms of M&A deal value, driven by an increase in the number of $100M+ acquisitions. These large transactions represent 4.7% of deal share so far this year, up from 3.8% from all of 2024, and a level not seen since 2021.

AI has also emerged as a bright spot, as corporations race to grab AI tech & talent.

M&A activity in AI reached record levels in Q2’25 at 192 deals, pushing AI’s share of tech M&A to 7.5% so far this year — almost double its share in 2021. Private companies have notably led some of the largest AI acquisitions in the first half of 2025, with OpenAI acquiring Io for $6.5B and Databricks spending $1B to buy Neon. 

The AI race is also pushing big tech companies to rethink their M&A strategy, after years of muted activity. 

Meta scooped up voice AI startups PlayAI and WaveForms this summer — marking its first acquisition since 2022 — in a bid to win the race to build the future of human-machine interactions. The company is betting that voice will become the dominant interface for interacting with AI.

During the company’s Q3’25 earnings call, Apple’s CEO mentioned being open to larger M&A deals to help accelerate its roadmap. This marks a significant move away from Apple’s historical focus on smaller acquisitions.  

Dive into 7 AI-related areas where we expect to see M&A activity this year, as well as high-potential acquisition targets for each, in the free report.

2. Signs point to tech IPO market rebound in H2’25

The global tech IPO market has remained muted during the first half of 2025, with 122 tech companies going public, in line with the numbers from 2024. But recent activity signals things may be picking up.

Figma successfully went public last month, in an IPO often referred to as a test of the public market’s appetite for tech companies. The company was valued at just over $16B at IPO and now boasts a market cap of $39B (as of 8/20/2025).

A few weeks later, crypto exchange platform Bullish followed a similar path, raising $1.1B in at a $5.4B valuation. The company is now trading at a 60%+ premium to its IPO price.

These recent examples have pushed several tech companies (crypto in particular) to announce they had filed to go public, reviving hopes of a tech IPO market rebound. Based on current trends, we project 84 tech IPOs for Q3 ’25 — above the 2-year quarterly average of 72.

Find 40+ blockchain companies with a high probability of going public in the next 2 years

But any rebound is likely to be modest, with private tech companies expected to remain private for longer and the role of IPOs potentially shifting to becoming a clearinghouse rather than a capital-raising mechanism, as predicted by Jared Carmel, Managing Partner, Manhattan Venture Partners:

“We’re witnessing a fundamental shift in how tech companies approach public markets. The average age at IPO has increased dramatically, from under 4 years in 2000 to 12 years in 2015 and nearly 16 years today. I expect this trend to accelerate, with companies staying private for 20+ years becoming the new norm.

The aggressive IPO pops we’ve historically seen are fundamentally unfair to founders and long-term investors who actually built these companies. Over the next several years, you’re going to see VCs, private equity, and sovereign wealth funds step in to extract maximum value before these companies ever go public. When they eventually do an IPO, they’ll go public at fair market value without the pop — essentially using public markets as a clearinghouse rather than a capital-raising mechanism.

This shift is already playing out in the data. We’re seeing record levels of private funding, exceeding $2 trillion in cumulative investment, and explosive growth in secondary transactions. The real value creation and liquidity will increasingly occur in private markets, rather than public ones. With companies staying private for two decades, secondary liquidity becomes absolutely critical — employees, early investors, and founders can’t wait 20 years for an exit.”

3. Private tech markets top $2T in equity funding

Private tech companies are staying private longer and now have more capital than ever to do so. 

Over $2T in cumulative equity funding has poured into private tech markets to date, with 90% raised in just the last decade. That funding has enabled companies to keep scaling before tapping the public markets. Today, startups are going public an average of 16 years after being founded, 4 years later than just a decade ago.

Late-stage rounds have also reached new extremes, with Databricks joining the exclusive “Series K” club in July. Just 16 Series K rounds have ever been raised — half in the last 5 years — signaling the growing normalization of ultra-late-stage private fundraising.

Private market check sizes have also grown dramatically. The past 18 months alone account for the largest Seed, Series A, Series B, Series D, and Series E+ rounds on record. And more dry powder is on the way: a recent executive order in the US is opening the door for 401(k) retirement accounts to invest in private markets, potentially unlocking a new wave of capital for private tech companies.

As regulatory barriers fall and new investment vehicles emerge, private tech company investments will increasingly define institutional — and eventually retail — portfolios. 

But there’s a catch. 

Private companies operate in information shadows, beyond public view. Institutions will increasingly need real-time data and context on companies not subject to quarterly reporting, turning private company intelligence into a new competitive advantage. 

4. Secondaries get bigger and pricier

The last 7 quarters have seen YoY growth in secondary transaction activity among VC-backed companies, with no signs of slowing down. As tech companies stay private longer and valuations continue to climb, secondaries are playing a growing role in providing liquidity.

In August 2025, OpenAI reportedly launched a tender offer at a $500B valuation, a sharp jump from its last reported $300B. The offer gives current and former employees a chance to cash out while attracting new capital from institutional buyers. Canva followed a similar playbook, recently conducting a secondary sale at $42B. That’s $10B higher than its October 2024 valuation, which was also set during a prior secondary transaction.

These moves are helping long-time employees and early investors realize returns, while giving latecomers a shot at high-growth companies.

Investor demand is heating up too. According to EquityZen, average discounts in secondary markets have compressed to just 13% below last-round valuations — the lowest level observed between Q1’23 and Q2’25. That pricing shift reflects growing competition and perceived upside, even in companies potentially years from IPO.

While large players like SpaceX, Ripple, and OpenAI continue to dominate transaction volume, interest is expanding to smaller unicorns and breakout startups. In Q2’25, 7 of EquityZen’s top 10 secondary movers had Mosaic scores over 800 and valuations north of $1B, including names like Axiom Space, Brex, and Skild AI.

Explore 500+ private tech companies with strong secondary potential

As secondary markets mature, they’re reshaping liquidity expectations — and giving investors new ways to get exposure to private tech winners without waiting for the IPO window to reopen.

5. New exit models emerge amidst the AI talent war

The intensifying race for AI talent is driving a new wave of unconventional exits in the tech ecosystem, bypassing traditional M&A while still delivering strategic value to acquirers. 

Tight regulation has pushed big tech companies to shift away from full takeovers and toward deal structures that offer access to technology and, more importantly, talent, without triggering antitrust alarms.

Large minority stakes have emerged as one such mechanism. In Q2’25, Meta invested $14.8B for a 49% stake in Scale, marking the largest private funding round of the quarter. As part of the deal, Meta hired Scale’s CEO and founder, Alexandr Wang. At their current pace, big tech companies are on track to complete 14 corporate minority deals in 2025.

Reverse acqui-hires  — where acquirers buy the team (fully or partially) and license the technology — are also gaining momentum. These hybrid transactions often include lucrative licensing fees that serve as a partial liquidity event for investors.

Notable examples include:

• Google hiring key personnel from Windsurf to join its DeepMind division, including CEO Varun Mohan and co-founder Douglas Chen 
• Amazon hiring key members of Adept
• Microsoft bringing in employees from Inflection AI

These transactions let acquirers cherry-pick talent and assets without facing regulatory hurdles or needing to buy out entire cap tables.

But it’s not just big tech adapting;  major LLM developers are adopting similar tactics. OpenAI and Anthropic have collectively made 3 acqui-hires so far in 2025 — Context.ai, Crossing Minds, and Humanloop.

These nontraditional exits may complicate fundraising and hiring for AI startups, as investors and employees weigh the risk of being bypassed in partial team acquisitions. In response, both groups may begin negotiating protective terms to ensure they aren’t left behind.

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AI companies drove the surge, accounting for half of all mega-rounds. Many are building foundation models tailored to complex real-world use cases like robotics and healthcare.

Using CB Insights’ Business Graph, our monthly Book of Scouting Reports offers an in-depth analysis of every private tech company that has raised a funding round of $100M or more, to spotlight where capital is concentrating, which startups are gaining momentum, and who’s shaping the next wave of market disruption.

Download the book to see all 50 scouting reports.

Key takeaways from July’s mega-rounds include: 

• Clinical AI moves from development to scaling, with both Aidoc (a clinical AI foundation model developer) and Ambience (an AI medical scribe) having raised mega-rounds last month to build upon their early success and scale across more health systems. Last month also saw OpenEvidence and Tala Health raise $100M+ rounds to bring agentic AI solutions to clinicians, with the latter joining the fast-growing AI unicorn list. 
• Investors keep betting big on the next wave of the AI boom, physical AI. Recent commercial breakthroughs in the autonomous vehicle space and heightened interest in the humanoid space are driving capital toward physical AI infrastructure. This includes robotics foundation models (Genesis AI, TARS), and hardware platforms for embodied AI model training (Galaxea AI). China-based Meituan led both the $100M Series A extension in Galaxea AI and the $125M Seed round in TARS, as it doubles down on physical AI investments.
• AI newcomers are openly taking on tech giants. Half of last month’s mega-rounds went to AI companies, which accounted for 7 of the 13 new unicorns minted during that time. Some of these companies are directly targeting incumbents such as Reka AI which positions itself as a lower-cost alternative to OpenAI or Anthropic, and Perplexity which targets Google‘s core search business with its new browser product. 
• Fintech is minting a new class of financial services challengers.  Fintech companies accounted for more mega-round deals than any other vertical in July, including 2 of the top 4 largest rounds. Ramp’s valuation jumped from $16B to $22.5B in mere weeks, while Bilt more than tripled in value, from $3.3B to $10.8B. Beyond fundraising, fintech leaders are pursuing aggressive expansion strategies. iCapital raised $820M last month to accelerate its acquisition strategy focused on seizing the private markets opportunity. 

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Investors, merchants, and brands can seize this opportunity now, targeting the early movers for investment or partnership ahead of agentic shopping’s arrival.

We’ve been tracking these emerging solutions on our agentic commerce Watchlist. Within this list, we’ve identified 3 breakout markets, each accelerating a different piece of the agent-led shopping journey.

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The fastest-growing startups and tech markets signal what’s next: the proliferation of agents and voice AI. 

Below, we break down the top stories from this quarter’s report, including:

• Massive deals continue to drive the AI funding boom
• Consolidation is in full force in the AI market
• AI revenue multiples reflect investor confidence in startups’ growth potential
• Tech market deals signal a shift from infrastructure to applications
• The fastest-growing genAI startups highlight the rise of voice AI

Download the full report to access comprehensive CB Insights data and charts on the evolving state of AI.

Massive deals continue to drive the AI funding boom

Funding to private AI companies across the globe reached $47.3B across 1,403 deals in Q2’25. 

Combined with the record total for Q1’25 (inflated by OpenAI’s $40B raise), funding in 2025 ($116.1B) has already blown past 2024’s full-year total ($105.7B). 

Together, the top 10 rounds accounted for 60% of the quarter’s funding total. 

AI development players continue to lead the surge, with Scale (AI training data provider), xAI (model developer), and Thinking Machines Lab (model developer) raising some of the quarter’s largest rounds. Other notable raises went to defense tech startups Anduril ($2.5B) and Helsing ($693M) as geopolitical tensions drive interest in the sector.

The largest round of the quarter — Meta’s $14.8B investment in Scale for a 49% stake (with CEO Alexandr Wang joining Meta) — highlights big tech’s recent “quasi-acquisition” spree.

This trend sees tech leaders hiring away the teams and licensing the tech of promising startups — this allows big tech to avoid antitrust scrutiny while giving startups a way to return capital to investors. These deals enable them to move more quickly and be more selective with the talent they bring on than traditional M&A allows.

Deals in this pattern include: 

• Inflection AI (March 2024): Microsoft paid $650M in a licensing deal to Inflection AI while poaching its founders and key employees
• Adept (June 2024): Amazon hired away Adept’s founders and many employees, with $330M+ going to licensing its tech
• Character.AI (August 2024): Google poached the company’s founders and 20% of its team in a $3B licensing deal
• Covariant (August 2024): Amazon hired robotics startup Covariant’s founders and a quarter of its staff while licensing the company’s models 
• Windsurf (July 2025): Google hired Windsurf executives and R&D employees in a $2.4B licensing deal

This activity reinforces the premium placed on AI talent in the current landscape. 

Consolidation is in full force in the AI market

Despite broader M&A weakness across the venture market, AI is a bright spot.

M&A activity in AI reached record levels in Q2’25 at 177 deals — almost double the quarterly average of 89 since 2020. 

The US was largely responsible for the jump, with acquisitions of US-based AI startups nearly doubling from 59 in Q1’25 to 104 in Q2’25. Europe followed with 46 M&A deals in the quarter.

Major US enterprise tech companies led activity as they embed AI across their offerings. Among the top 10 most active in the quarter were IBM (3 AI acquisitions), followed by Intuit, Nvidia, Databricks, and Salesforce (tied with 2 AI acquisitions each). 

Earlier this year, we predicted enterprise tech heavyweights would compete for AI infrastructure dominance. AI optimization company CentML, acquired by Nvidia in Q2’25, was on our AI infrastructure acquisition target list.

Dive into 7 AI-related areas where we expect to see M&A activity this year, as well as high-potential acquisition targets for each, in the free report. 

AI revenue multiples reflect investor confidence in startups’ growth potential

Leading AI companies that raised funding in Q2’25 did so at sky-high valuations — even by AI standards. 

Model developer xAI raised $5B at a $75B valuation in June 2025, up from its $50B valuation in November 2024. With a projected $500M in 2025 revenue, that’s a 150x forward-looking multiple. Similarly, customer service AI agent startup Decagon raised $131M at a $1.5B valuation on just $10M in ARR.

AI startups are commanding a median 17.1x revenue multiple (based on FY 2024 revenue), but some far exceed that. Companies in the chart below command a median 50.1x multiple. 

This indicates investor confidence and competition for the hottest startups. The big multiples are also a reflection of these companies’ growth potential: xAI projects $2B in revenue next year, while others on the list, like Glean, hit $100M ARR in 3 years.

Tech market deals signal a shift from infrastructure to applications

Among the 1,500+ tech markets that CB Insights tracks, those in the chart below saw the greatest number of AI deals in Q2’25.

Leading markets focus on specific industry or technical challenges — like industrial humanoid robots and coding AI agents — not general-purpose AI models.

In fact, LLM developers tied for 9th place with 11 other markets at 5 deals during the quarter. 

This suggests investors increasingly expect greater value creation to come from applications than from infrastructure.

See how markets stack up in the CBI Market Index

The fastest-growing genAI startups highlight the rise of voice AI

While funding may be concentrated among the largest players, opportunities in AI aren’t limited to those companies. Nearly 3 in 4 AI deals (72%) in 2025 so far still involved early-stage startups. 

Early-stage genAI companies with the fastest-growing headcounts are concentrated in AI agent applications — and more specifically in voice AI development. 

Advancements in voice AI models in 2024 — including the launch of OpenAI’s Realtime API for speech-to-speech applications — jumpstarted voice applications across use cases.

Companies are now positioning themselves for a future where humans interact with AI via conversation rather than text interfaces. 

Job postings from Vapi — one of the fastest-growing voice startups based on headcount — highlight its positioning around this inflection point, as noted by CB Insights Hiring Insights.

Vapi has also seen the greatest jump in its Mosaic health score among voice development companies, as shown in the chart below.

Watch these startups for partnership, investment, and acquisition opportunities. Signaling the potential for increasing consolidation, Meta acquired voice startup Play AI, which uses AI to generate human-like voices, in July 2025. 

MORE AI RESEARCH FROM CB INSIGHTS

• The AI agent market map
• AI 100: The most promising artificial intelligence startups of 2025
• AI agent startups are becoming revenue machines — here are the top 20 ranked
• What’s next for AI agents? 4 trends to watch in 2025
• Pharma AI readiness: How the 50 largest companies by market cap stack up

The post State of AI Q2’25 Report appeared first on CB Insights Research.

AI continues to dominate, capturing 50% of venture investment. At the same time, investors are doubling down on hard tech — hardware-focused and capital-intensive technology — driven by surging energy demands from AI, advancements in robotics, and growing defense interest.

Below, we break down the top stories from this quarter’s report, including:

• Funding tops $90B for the third straight quarter, while deal count declines
• Hard tech claims 6 of the top 10 largest deals
• AI companies command funding premiums across sectors
• Regulatory shifts push big tech from M&A to minority investments
• CVC deals hit a 7-year low as the tariff threat looms

We also outline the categories shaping venture dealmaking for the rest of 2025 — including stablecoins, defense tech, quantum, and nuclear energy.

Let’s dive in.

Download the full report to access comprehensive data and charts on the evolving state of venture across sectors, geographies, and more.

Top stories in Q2’25

1. Funding tops $90B for the third straight quarter, while deal count declines

Venture funding reached $94.6B in Q2’25, marking the second-highest quarterly figure since Q2’22 and the third straight quarter to surpass $90B.

While funding dipped slightly from Q1’25, the decline reflects normalization after OpenAI’s $40B raise inflated numbers in Q1. In fact, Q2 remained elevated even as foundation model developers accounted for just 3% of total capital, down from 36% in Q1’25 and 29% in Q4’24. This shift signals a broadening of venture activity beyond foundation models into the broader AI ecosystem and adjacent hard tech sectors.

With this continued momentum, annual funding is projected to reach nearly $440B, a 53% increase from 2024, pointing to a sustained recovery in venture investment.

At the same time, deal volume continues to decline, reflecting greater investor selectivity. Q2 saw just 6,028 deals — the lowest quarterly total since Q4’16. This puts 2025 on pace for around 25,000 deals, or nearly half the volume seen in 2022, even as total funding approaches similar levels.

While investors are pulling back on the number of deals, they’re deploying more capital per investment: the median deal size hit a new high of $3.5M in 2025 YTD. Rising check sizes and falling deal count underscore a shift toward fewer, higher-conviction bets.

2. Hard tech claims 6 of the top 10 largest deals

Six of the 10 largest deals in Q2’25 went to hard tech companies, which are firms building capital-intensive physical products.

CBI customers: Track the highest funding startups in Q2’25

This surge is driven by macro forces such as onshoring initiatives, clean energy investment, and the rise of physical AI, which is enabling new capabilities across robotics, autonomy, and industrial systems.

Mega-rounds ($100M+ deals) spanned multiple sectors:

• Montera Infrastructure: $1.5B for hyperscale data center solutions
• Commonwealth Fusion Systems: $800M for commercial nuclear fusion
• Neuralink: $650M for brain-computer interfaces

Geopolitical tensions are also pushing capital toward defense, where startups are securing large rounds:

• World View: $2.6B for high-altitude aerospace platforms
• Anduril: $2.5B for autonomous defense systems and defense connectivity platforms
• Helsing: $693M for AI-powered defense applications

Across the board, defense tech startups are now commanding a median revenue multiple of 17.4x, edging out AI companies at 17.1x and all other major sectors. This signals high investor confidence and competition, driving premium valuations across the defense tech sector.

With investor appetite moving toward physical infrastructure and embodied AI, the rise of hard tech represents a shift likely to define the next chapter of venture investing.

3. AI companies command funding premiums across sectors

The venture market is experiencing a pronounced “AI premium,” with median deal size for AI companies reaching $4.6M in 2025 — over $1M more than the broader market. 

But the premium isn’t just financial. AI companies also score higher on CB Insights’ Mosaic Score (success probability) and Commercial Maturity (ability to compete and partner) across most sectors, signaling stronger fundamentals and market readiness in the eyes of investors.

AI companies in auto tech — with most focused on autonomous driving — are commanding the highest premium. Their median deal size is $20.6M higher than non-AI auto tech peers, and their average Mosaic score is 99 points greater. This quarter, the largest AI auto tech deal went to Applied Intuition, which raised a $600M Series F round at a $15B valuation.

Robotics and cybersecurity follow closely, with AI firms in those sectors securing median deal sizes $10.7M and $6.4M larger than their non-AI peers.

Team pedigree is further amplifying the premium. Thinking Machines Lab — founded by former OpenAI CTO Mira Murati alongside veterans from OpenAI, Google, Meta, and Mistral AI — raised a record-breaking $2B seed round at a $10B valuation, making it the most valuable seed-stage startup ever. 

The deal reflects an increasingly common “go big or go home” investing mentality, as investors make outsized bets on high-credibility AI teams.

4. Regulatory shifts push big tech from M&A to minority investments

Big tech M&A — which includes M&A from Alphabet, Amazon, Apple, Microsoft, Meta, and Nvidia — is entering a sustained downturn. Annual deal activity is projected to hit just 12 transactions in 2025, a steady decline from 66 deals in 2014. 

US regulatory tightening caused M&A activity to collapse from 30+ deals in 2022 to just 8 deals in 2023 — the steepest single-year decline on record.

CBI customers: Track big tech M&A activity

Big tech companies are adapting by taking large minority stakes, allowing them to circumvent federal antitrust review while still gaining strategic influence and access to key technologies. For example, Meta invested $14.8B in Scale — the largest funding round of Q2’25 — for a 49% stake, as did Microsoft with its recent investments in OpenAI. 

In 2025 YTD, big tech is on pace for 14 corporate minority deals, an increase from levels before the regulatory shift.

Big tech’s shift reflects broader M&A weakness across the market. Global activity has fallen 34% from 3,103 deals in Q1’22 to 2,053 deals in Q2’25, driven by high interest rates that have made financing more expensive and economic uncertainty that has made companies more cautious about acquisitions.

However, acquisitions of AI companies is one area where M&A is increasing. Activity reached record levels in Q2’25 at 177 deals — over double the 5-year quarterly average of 84 deals. This surge reflects companies’ need to acquire AI capabilities quickly rather than build them internally, as AI becomes essential for staying competitive.

While falling interest rates will help smaller deals rebound and provide a modest tailwind to overall M&A activity, we do not expect deal volumes to approach peak years. Big tech and other large corporations will remain constrained by regulatory scrutiny.

We are likely entering a new era where strategic partnerships and minority investments replace traditional M&A as a growth mechanism for major corporations.

5. CVC deals hit a 7-year low as the tariff threat looms

Corporate venture capital dealmaking has reached its lowest point in over 7 years, as CVC-backed investment totaled just $17B across 742 deals, down 8% quarter-over-quarter and representing the weakest performance since Q1’18.

CVC activity has fallen dramatically from its Q1’22 peak due to broader market pressures, including high interest rates and economic uncertainty. Tariff concerns are likely adding further burden to an already weakened market.

Despite fewer deals, median CVC-backed deal sizes have reached their highest levels since 2021. This suggests that CVCs are concentrating capital on fewer, higher-conviction investments.

CVCs are also collaborating more frequently. Deals involving 3+ CVCs reached a record high of 32% in Q2’25, reflecting both strategic necessity and market conditions: larger funding rounds in capital-intensive sectors like AI and hard tech may require multiple corporate partners to provide sufficient capital. At the same time, competition for access to the hottest technologies drives CVCs to team up rather than risk being shut out.

Breakout sectors of 2025

Below, we analyze venture funding across tech sectors to identify where investor conviction and market momentum are strongest.

Stablecoin funding is on pace to shatter its previous record

Stablecoin startups are experiencing an explosive year-over-year funding surge as stablecoins achieve mainstream adoption. Funding is projected to reach $10.2B in 2025, representing more than 10x growth from 2024.

Growing regulatory frameworks worldwide — such as the pending passage of stablecoin legislation in the US with bipartisan support — provide needed certainty for institutional investment, setting the foundation for exponential growth.

Multiple startups are taking advantage of the momentum. While the largest funding rounds occurred during the first quarter — with $2B deals for Avalon Labs and Binance — notable rounds also occurred during Q2’25, including:

• Flowdesk: $100M for digital asset trading and liquidity services
• Conduit: $36M for its cross-border business transactions platform
• Niural: $31M for an AI-enabled stablecoin and fiat payroll platform

Major financial services companies are also increasingly involved. Mastercard, Visa, and established banks are now enabling stablecoin transactions and issuing their own digital currencies, bringing institutional credibility to the space. Meanwhile, stablecoin issuers Circle and Ripple applied for banking licenses on June 30 and July 2, respectively, demonstrating their intent to operate like mainstream financial institutions.

Stablecoins are evolving beyond simple stores of value into yield-bearing tools and liquidity products. Solutions like liquidity mining, lending services, and yield-bearing stablecoins are receiving substantial investor attention. Cross-border payments companies powered by stablecoins are also gaining traction as affordable and accessible USD alternatives in emerging markets.

As regulatory frameworks solidify and institutional adoption accelerates, stablecoin companies are positioned to capture significant market share in global payments and financial infrastructure markets.

Defense tech momentum continues

Within the first two quarters of 2025, defense tech funding has already reached a new annual record of $11.1B.

The funding breakout is driven by multiple forces, including geopolitical instability and technology advancements, notably in drones and other unmanned vehicles.

Concurrently, the US Department of Defense is pushing to diversify the defense ecosystem through public-private partnerships and startup support.

The defense investor landscape is also rapidly evolving, with the number of unique investors in the space expected to increase 34% in 2025 to 950 from 710 the year prior. Traditional defense funds like Shield Capital and In-Q-Tel are now joined by generalist VCs, bringing more capital to fund a new generation of startups.

We expect continued investor interest in defense tech, as NATO recently agreed to increase defense spending from 2% to 5% of GDP by 2035, adding over $400B annually in market expansion. The 1.5% earmarked for security infrastructure aligns with venture trends in AI, cybersecurity, robotics, and technologies developed for both military and civilian use cases.

Quantum tech reaches an all-time high, halfway through the year

Quantum tech is attracting significant investor interest, reaching record annual funding levels at $2.2B within the first two quarters of 2025 — an increase of 69% from 2024.

The surge follows major hardware breakthroughs from Google, IBM, and Microsoft, which may drive confidence in leading startups even though the technology still lacks practical applications that outperform classical systems. Industry leaders like Fujitsu and Quantinuum — a subsidiary of Honeywell — expect fault-tolerant quantum computers by 2030 at the earliest.

Massive investments are flowing towards various quantum applications in 2025 so far:

• PsiQuantum: $750M to build million-qubit photonic quantum computers by 2029
• QuEra Computing: $230M to accelerate fault-tolerant neutral-atom quantum systems
• Multiverse Computing: $215M to scale its quantum-inspired AI compression technology

Government support has also increased, with $1.8B in public funding announced globally in 2024. For example, Australia committed $620M to PsiQuantum, while DARPA committed up to $200M in joint funding to assess the feasibility of industrially useful quantum computers.

As quantum technologies move toward commercial viability, the combination of record private investment, substantial government backing, and technical progress positions the industry for significant growth once practical quantum advantage is achieved in commercial applications.

Corporate interest drives a surge in nuclear energy funding

Funding to nuclear energy companies is projected to reach an annual record by the end of 2025 at $5B. Massive energy requirements for AI data centers — with US data center power consumption projected to triple by 2030 — are driving corporate interest in clean baseload power.

Big tech companies are leading the charge, with investments since 2024 across both small modular reactors (SMRs) and fusion technologies:

• Amazon invested in X-energy with plans to develop over 5 GW of SMR projects by 2039; Amazon also backed Realta Fusion
• Google reached agreements with Kairos Power for up to 500 MW of nuclear power by 2030 and has also invested in Commonwealth Fusion Systems and TAE Technologies.
• Microsoft reached a deal with Constellation Energy to reopen the Three Mile Island nuclear plant, while committing to purchasing fusion electricity from Helion Energy by 2028

Corporate interest has also skyrocketed, with earnings call mentions hitting record levels as executives grapple with the major power requirements for AI infrastructure.

Current and previous presidential administrations have reduced regulatory red tape for nuclear development, streamlining approval processes. The bipartisan approach creates stable regulatory support for long-term investments and should accelerate sector growth in the coming years.

As AI adoption continues, nuclear provides the only scalable solution for clean baseload power that intermittent renewables cannot match for always-on AI computing infrastructure. The combination of massive corporate demand and supportive regulatory frameworks positions nuclear for explosive growth in the years ahead.

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RELATED RESOURCES FROM CB INSIGHTS:

• State of Venture Q1’25 Report
• The AI agent market map
• 7 tech M&A predictions for 2025
• State of AI Report: 6 trends shaping the landscape in 2025
• 15 tech trends to watch closely in 2025

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Tech giants have rocketed ahead with a parade of autonomous (and agentic, in the case of OpenAI’s Operator) shopping tools. At the same time, payment behemoths Visa, Mastercard, and PayPal are all developing solutions to enable agentic payments. 

To keep up, retail leaders are building out the foundational layer for autonomous commerce, integrating AI technology into everything from search and personalization to supply chain automation.

Still, none of them have launched an autonomous shopping agent that can make purchases on behalf of a customer. But retailers are actively investing in AI with the aim of maintaining control of the customer experience, first-party customer data, and pace of innovation in the longer term.

We examined the top 20 global retailers by market cap and ranked them based on their current AI capabilities to gauge their preparedness to evolve with the rapidly changing AI landscape. We used CB Insights data on investments, acquisitions, partnerships, patents, and earnings transcripts since January 2023 to determine the companies’ AI activity. 

Our analysis scores the retailers in 2 key areas:

• Execution: The execution score measures a retailer’s current ability to deliver AI-powered products and services to customers and shoppers, as well as to deploy AI internally across business and back-office functions. We based this score on CB Insights data, including business relationships, product launch media mentions, and earnings transcripts.
• Innovation: The innovation score assesses a retailer’s track record of investing in, acquiring, or developing novel AI capabilities to power its future AI adoption. We based this score on CB Insights data, including patents, acquisitions, and deal-making activity.

Below are the 20 biggest global retailers by market cap, ranked by their preparation to transform their businesses and shopping with AI:

Key takeaways

• Top-ranked firms like Amazon and Alibaba are investing heavily in a core AI infrastructure that creates a scalable advantage that the rest of their business will build on. While Amazon and Alibaba have launched AI shopping solutions, both retailers’ real advantages lie deeper. They’ve built AI infrastructure from custom AI chips (Amazon) to proprietary LLMs (both retailers), which power AI development across their businesses. Amazon has positioned itself significantly ahead in future-looking innovation through investments, with a particular focus on foundational AI models and warehouse and supply chain automation.
• Partnerships with AI leaders and big tech companies will be most retailers’ ticket to AI adoption. Below the top 5 AI-ready retailers in the ranking, partnerships with big tech players and others are powering AI adoption. These relationships suggest that external partnerships and infrastructure will be essential for most retailers to effectively integrate AI throughout their operations.
• While agentic commerce remains further on the horizon, retailers are investing in AI to streamline operations, especially in merchandising. Leading retailers are deploying genAI tools for personalization and efficiency across several merchandising functions, both online and in-store, including genAI search, specialized merchant tools, inventory forecasting, and delivery route optimization. But it’s perhaps most notable that none of the retailers on the list have tackled agentic commerce. For now, retailers have placed big tech leaders, such as OpenAI and Google, in the driver’s seat to control agentic commerce infrastructure and offer retailers crucial partnership opportunities as the technology evolves.

Top-ranked firms like Amazon and Alibaba are investing heavily in a core AI infrastructure that creates a scalable advantage that the rest of their business will build on. 

While both Amazon and Alibaba have launched AI shopping assistants and merchandising tools, both retailers’ real advantage is in the potential to build on their foundational AI stack. 

Over the past 2 years, both companies have introduced genAI platforms through their cloud computing divisions. AWS created Amazon Bedrock in 2023, which lets businesses build genAI applications using various AI models, including Amazon’s own Nova model. Amazon also makes its own AI chips. 

Meanwhile, Alibaba Cloud launched its Qwen model family in 2023, its Model Studio in 2024, and in 2025 made its AI models for video generation open source. The company also continues to expand vertical solutions, including an AI-powered weather forecasting model to enhance farm performance, as well as multiple medical diagnosis and virus detection tools. 

In addition to its internal development, Amazon has positioned itself significantly ahead in future innovation. Across all of its subsidiaries, the company has made 53 investments and 2 acquisitions of AI companies since 2023, nearly twice as many as Alibaba (28 investments and 0 acquisitions). The company has invested in a variety of AI models (including 3 investments in Anthropic), agents, and applications, from warehouse automation to AI for crop modification to voice AI gaming.  

CBI customers: Track all of Amazon’s investments since 2023 here

These foundational tools enable downstream business units — from logistics and supply chain to healthcare and agriculture — to accelerate their own AI initiatives without reinventing the wheel.

Amazon’s Bedrock and proprietary chips, for instance, give its retail and logistics operations priority access to high-performance infrastructure, accelerating their deployment of AI in warehousing and delivery.

By owning the full stack — hardware, models, platforms, and end-user applications — these companies ensure their AI gains compound across business units, from consumer interfaces to internal operations.

Notably, the second tier of AI-ready retailers — Walmart, JD.com, and Coupang — is also building AI toolkits through proprietary infrastructure. Walmart has developed its own retail-specific LLMs and has introduced assistants for its merchants, associates, and shoppers, as well as AI tools for virtual fitting and shelf condition tracking. JD.com and Coupang have been similarly active in internally developing merchandising tools, including digital human livestream hosts and generative AI translation. 

Partnerships with AI leaders and big tech companies will be most retailers’ ticket to AI adoption.

Below the top 5 AI-ready retailers in the ranking, partnerships with big tech players and others are powering longer-term AI adoption. 

Lowe’s, for instance, began its partnership with OpenAI by utilizing machine learning tools across internal functions, including pricing and supply chain management. In 2024, the retailer introduced a GPT called “Product Expert” on ChatGPT, which specializes in home improvement questions. Then, in 2025, it launched 2 AI assistants – one for associates and one for shoppers – in collaboration with OpenAI. 

The Home Depot, meanwhile, has similarly relied on its partnership with Google Cloud to power its AI advancements for a decade. The company uses Google AI to improve inventory management and supply chain efficiency and has integrated Google’s AI and machine learning capabilities into its customer search, as well as its employee and consumer apps. The newest generative AI feature on Home Depot’s website, Magic Apron, is an AI agent specializing in home improvement projects; the company used Google Cloud’s vertical agents solution to build it.  

Source: CB Insights – Home Depot business relationships

These relationships suggest that external partnerships and infrastructure will be essential for most retailers to effectively integrate AI throughout their operations. Within these relationships, it will be crucial for retailers to consider how their external partners are utilizing their data to train models that their competitors may also leverage, which could erode any competitive advantages gained from the partnership. 

While agentic commerce remains further on the horizon, retailers are investing in AI to streamline operations, especially in merchandising. 

Big tech and AI leaders are leading the charge for agentic commerce, while traditional retailers are lagging. 

Perplexity, OpenAI, and Google have all introduced agents that can autonomously compare prices, read reviews, and complete purchases on behalf of consumers. 

While Amazon and Alibaba have both released browser agents with the capability to shop and buy for consumers, neither they nor any other retailers on this list have launched or partnered on agentic shopping or payments solutions. However, as autonomous commerce rapidly evolves, major retailers will have to act fast to stay competitive. 

In the meantime, for retail leaders, AI solutions for merchandising are becoming table stakes. More personalized and effective genAI e-commerce search is the most common upgrade, deployed by retailers from Walmart and JD.com at the top of the ranking to Target and CVS at the bottom. GenAI is also powering online content generation across retailers.

Retailers’ merchant teams are also using specialized genAI tools and assistants to quickly translate data and trends to inform product decisions. AI solutions are also fueling demand and inventory forecasting for companies like Amazon, JD.com, and Coupang.

Notably, AI-powered tools are not limited to digital or online use. Several retailers have developed AI solutions to enhance the in-store shopping experience and make it more efficient. 7-Eleven is partnering with Sony Semiconductor Solutions to track customer activity in aisles using vision detection. Home Depot, Target, Walmart, and others have also deployed specialized genAI assistants and agents to provide store associates with quick answers to customer questions. 

CBI customers: See how retail execs are talking AI and shopping

Looking ahead

While access to capital and AI firepower is helping Amazon, OpenAI, and Google lead the way in AI’s retail deployment, retail “natives” may have some advantages in the long run. Walmart, Coupang, and other major competitors have easy access to transaction data, an understanding of the retail value chain, and a built-in supply chain and fulfillment structure. In addition, many of the retailers on this list also have stores, where roughly 82% of all US retail sales still occur, giving them a continued profit source as well as a broader view of how consumers shop.

That said, agents’ entry into shopping has the power to turn the traditional customer journey on its head. We believe that companies already owning critical distribution and financial services infrastructure, in addition to AI innovation, are best positioned to own the customer relationship — putting big tech leaders like Apple, OpenAI, and Google in the driver’s seat. To stay competitive, retailers and other consumer-facing businesses must quickly build partnerships with big tech and other agent leaders or risk consumers excluding them from their buying decisions.

RELATED RESEARCH FROM CB INSIGHTS

• The future of the customer journey: AI agents take control of the buying process
• Voice AI’s sweet spot: Ordering fries with that
• Shopify’s next move: How the e-commerce giant is evolving into a full-stack platform for commerce and media
• The generative AI for e-commerce market map
• The automated warehouse market map

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These significant cash infusions signal where investors are placing the biggest bets at a given time and which startups are being positioned to shape or disrupt markets.

To track trends in mega-rounds, our monthly Book of Scouting Reports offers an in-depth analysis of every private company that has raised a funding round of $100M or more. The scouting reports provide insight into each company’s funding history and latest round; headcount; opportunities & threats; commercial maturity; and business health.

Download the book to see all 46 scouting reports.

Key trends from June’s mega-rounds include:

• AI attracts the largest funding rounds, fueled by tech talent wars: Meta invested a massive $14.8B in Scale, whose CEO is also joining the tech giant. Thinking Machines Lab raised $2B in seed funding without a live product, with several former OpenAI executives having joined the company. These rounds show how quickly AI talent is moving around the industry — and the hefty price tags that this talent can command.
• Industrials command a third of mega-rounds in June, indicating a hardware renaissance: Industrial companies (including defense, aerospace, energy, and robotics) drove many of this month’s $100M+ deals, from Anduril‘s $2.5B round to Helsing‘s nearly $700M deal. While AI is central to many of the companies in this sector, almost all are developing physical hardware and infrastructure. 
• Quantum computing players get a boost from AI and defense applications: Two quantum computing companies raised mega-rounds in June ’25: Infleqtion, which develops quantum sensing for defense, and AI 100 winner Multiverse Computing, which provides quantum-enabled model compression to speed up AI processing. While not a substantial share of deals, these investments point to an increased demand for quantum capabilities across high-growth applications.
• Capital is going toward product and R&D: 37% of mega-round recipients are directing these funds toward product development and core technology advancement, including AI. For example, Observe intends to use the capital to expand its AI observability features, while Impulse Space is planning R&D for new vehicles for NASA and defense customers. 

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So far this year, 53 companies have reached billion-dollar valuations, putting 2025 on pace to exceed the 80 unicorns minted in all of 2024.

Artificial intelligence is the key driver behind this surge, with AI startups accounting for over half of all new unicorns in 2025 so far. These AI-native unicorns are also breaking the mold, reaching $1B+ valuations on faster timelines, hitting the milestone in 6 years versus the typical 7.

Here’s what today’s unicorn landscape signals about the future of tech:

• 1 in 5 new unicorns are AI agents, with AI taking over the unicorn landscape, representing 53% of all new billion-dollar companies in 2025 so far. Among the newest unicorns, 12 are building AI agents, including Hippocratic AI (healthcare), Cyberhaven (data security), and Parloa (customer support). 
• Newer unicorns generate 83% more revenue per employee than older ones, with $814K per employee on average, compared to the $446K average across all unicorns. This reflects automation-first approaches and leaner operations that avoid the operational bloat older unicorns accumulated during their growth phases. For example, among unicorns born in 2025, the company with the highest revenue per employee is soft drink company Olipop ($1.2M/employee), followed by AI sales agent unicorn Clay ($1M/employee).
• Consumer and fintech companies are most primed to exit, boasting the highest M&A probability scores among the top Mosaic-scoring companies. While payments company PPRO tops the list with a 53% probability of getting acquired in the next 2 years, consumer & retail companies dominate the middle tier with ID.me (41%), Cart.com (33%), and Vestiaire Collective (31%), suggesting acquirers see solutions like identity verification, e-commerce infrastructure, and marketplace platforms as prime M&A targets.

CBI customers: Dive into data on every unicorn

Market map of billion-dollar startups

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By combining AI with physical dexterity, humanoids can perform complex tasks once limited to people, without the expensive facility modifications that traditional automation requires.

While manufacturing and warehousing use cases lead in early adoption, humanoids are expanding into healthcare, retail, and hospitality sectors, signaling widespread potential in industries that need human-like movement and flexibility.

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Now, our Book of Scouting Reports offers in-depth analysis on every single one of the private companies featured in the market map.

Combining CB Insights’ proprietary data and AI, scouting reports provide insight into each company’s:

• Funding history
• Headcount
• Key takeaways (including opportunities and threats)
• Commercial Maturity score
• Mosaic score

Download the book to see all 49 scouting reports.

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Now, we’re examining the critical metrics behind these winners, revealing potential acquisition targets, partnership opportunities, and emerging competitors before they reshape the market.

Below, we analyzed the 100 winners to understand how the cohort stacks up, the markets we’re seeing emerge, top investors in AI, and more.

Learn more about the AI 100 here

Some highlights from our analysis: 

• AI infrastructure shows a maturity gap despite massive funding. Despite the already enormous amount of capital raised in this category, AI infrastructure still has overall low Commercial Maturity Scores and sees a lot of early-stage activity with a specific focus on efficiency. These AI 100 winners are betting on next-generation solutions like specialized AI chips, novel computing architectures with reduced energy consumption and optimized inference, and infrastructure designed for multimodal workloads that current systems can’t efficiently handle. 
• Autonomous vehicles are accelerating beyond the hype cycle. The auto & mobility market ranks third by Mosaic score, with companies gaining significant commercial traction following Waymo‘s recent success in scaling its robotaxi operations. This momentum validates years of R&D investment and suggests we’re entering a new phase of AV deployment. Read more in our recent autonomous vehicle analysis.
• Multimodal AI is driving the biggest breakthroughs. Voice AI platform Cartesia leads the largest year-over-year Mosaic score jump (+321), alongside other companies pushing beyond text-only models toward integrated voice, vision, and reasoning capabilities. This shift represents the next evolution of AI, especially for embodied AI systems like humanoids, moving from single-modality tools toward systems that can understand and generate across multiple forms of media simultaneously. 

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Now, our Book of Scouting Reports offers in-depth analysis on every single one of the AI 100 winners, from infrastructure to horizontal to vertical applications.

Combining CB Insights’ proprietary data and AI, scouting reports provide insight into each company’s:

• Funding history
• Headcount
• Key takeaways (including opportunities and threats)
• Commercial Maturity score
• Mosaic score

Plus, the analysts behind this year’s AI 100 provide their perspective on every one of the winners.

Download the book to see all 100 scouting reports.

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After generative AI transformed content creation with large language models and AI agents enabled autonomous decision-making with predictive systems across enterprises and industrial applications, humanoid robots represent the next frontier as the embodiment of physical AI.

The humanoid market secured a record $1.2B in funding in 2024 and is projected to reach $2.3B in 2025, according to CB Insights data.

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While deal volumes remained mostly steady, funding increased 51% to $66.6B, with the majority of this going to infrastructure companies like OpenAI. 

Meanwhile, vertical AI is gaining momentum, with healthcare unicorns dominating Q1’s new unicorn cohort — a sign of investor confidence in AI’s increasing specialization.

Download the full report to access comprehensive data and charts on the evolving state of AI. 

Key takeaways from the report include:

• AI funding grows 51% QoQ to hit $66.6B — a new quarterly record — as industry incumbents secure mega-rounds. This boost was largely driven by a handful of major infrastructure players like OpenAI ($40B round), Anthropic ($3.5B Series E), and Safe Superintelligence ($2B Series B). Even without OpenAI’s massive round, Q1’25 would still represent the second-highest funding quarter ever (following Q4’24). Deal count decreased only slightly, falling 7% QoQ to 1,134. 
• Healthcare dominates the new AI unicorn pool. More than half of the 11 AI companies that reached $1B+ valuations in Q1 are developing healthcare solutions. These healthcare AI unicorns made up 30% of all new unicorns across VC and include Hippocratic AI (healthcare models and agents) and Insilico Medicine (AI drug discovery).
• AI agent companies lead M&A activity amid increasing consolidation. The 3 largest of 85 AI acquisitions in Q1’25 went to companies offering enterprise AI agent technology. The markets these companies occupy — like agent development platforms and multi-agent systems — boast among the highest average Mosaic scores across industries, reflecting strong company health and signaling the potential for more exits. 

We dive into the trends below.

AI funding reaches record $66.6B in Q1’25 as industry incumbents secure mega-rounds

AI funding grew 51% to $66.6B across 1,134 deals in Q1’25. This quarter’s funding total represents nearly two-thirds of all AI investment in 2024 ($101.5B), suggesting full-year 2025 funding will blow previous years’ tallies out of the water. 

The surge was fueled by mega-rounds concentrated among a few infrastructure giants, most notably OpenAI’s massive $40B VC round, along with Anthropic’s $3.5B Series E and Safe Superintelligence’s $2B Series B. Even without OpenAI’s landmark funding round, Q1 would be AI’s second-strongest funding quarter ever.

While total funding surged, the relatively stable deal count suggests larger deal sizes — especially to already established market leaders — rather than simply more companies receiving investment. In fact, in 2025 YTD, the median deal size of $5M represents a 4-year high. 

CBI customers: Track 17K+ AI companies

Healthcare dominates the new AI unicorn pool

While infrastructure companies received the lion’s share of funding, healthcare AI players led in new unicorn creation. 

Healthcare companies claimed the majority of new AI unicorns in Q1’25, with 6 out of 11 total AI companies reaching the $1B+ milestone. Even when looking at the venture landscape beyond AI, healthcare AI players drove nearly 1 in 3 new unicorn births in Q1. 

While healthcare AI unicorns are developing diverse applications across the care continuum, half of these newly minted unicorns apply AI to support provider workflows. These include:

• Hippocratic AI (patient follow-up)
• Abridge (clinical documentation)
• OpenEvidence (healthcare decision-making)

This trend highlights both growing demand for clinician-support tools and strong investor conviction in AI’s ability to deliver returns in the healthcare industry.

See every current AI unicorn

AI agent companies lead M&A activity amid increasing consolidation

Agentic solutions led the top AI exits in Q1’25, securing the 3 largest deals among 85 acquisitions — establishing agents as the primary focus of industry consolidation. 

These acquisitions align with the high Mosaic scores (which measure company health and growth potential on a 0-1,000 scale) across AI agent markets. Top agent categories all score well above the average of 370 across industries: autonomous agents & digital coworkers (721), AI agent development platforms (715), and multi-agent systems & orchestration (705).

The blockbuster exits of companies like Moveworks, Weights & Biases, and OfferFit show that enterprise buyers are increasingly seeking to build comprehensive agent solutions to gain a competitive edge. 

See rising markets in the CBI Market Leaderboard

MORE AI RESEARCH FROM CB INSIGHTS

• The AI agent market map
• AI 100: The most promising artificial intelligence startups of 2025
• Enterprise AI agents & copilots: Our growth projections for the $5B+ market 
• What’s next for AI agents? 4 trends to watch in 2025

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Despite this contraction, median deal size has climbed to $10M this year (up from $8.9M in full-year 2024), revealing that CVCs are making fewer but larger investments as economic uncertainty persists.

The quarter highlighted 2 other dominant forces reshaping the CVC landscape: US startups captured 70% of global CVC-backed funding — the 2nd straight quarter at 70%+ — while AI startups secured 7 of the top 10 CVC deals worldwide. This reflects an intensifying race among CVCs to secure competitive footholds in leading technologies before rivals gain the upper hand.

Download the full report to access comprehensive data and charts on the evolving state of CVC across sectors, geographies, and more.

Key takeaways from the report include:

• Deals continue their downward trend as investors remain selective. Global CVC deal volume fell 13% QoQ to 728 deals in Q1’25, reaching the lowest quarterly total since Q1’18. Mega-rounds ($100M+) accounted for 59% of the $18.7B in total funding, showing that CVCs are still making substantial bets in a more selective environment.
• US companies dominate CVC investment dollars. In Q1’25, US startups captured $13.1B (or 70%) of global funding from deals with CVC participation. Within the US, Silicon Valley maintained its leading position with $7.5B across 97 deals, underscoring its continued importance as a strategic hub for corporate investment.
• AI continues to command CVC attention and dollars. AI startups secured 7 of the 10 largest CVC-backed deals in Q1’25, with these deals representing 31% of all quarterly funding among CVC-backed deals. The biggest deal was Anthropic‘s massive $3.5B Series E round, backed by the venture arms of Cisco and Salesforce.
• Early-stage deal share holds steady at the highest level in over a decade. Early-stage investments made up 65% of all CVC deal activity in Q1’25, matching the high-water mark sustained annually since 2023. With the median early-stage deal size growing to $5.8M this year so far, CVCs are placing larger bets on nascent companies that have long-term growth potential.
• Salesforce Ventures leads with the strongest Q1 portfolio. Among CVCs with 5+ investments in Q1’25, Salesforce Ventures leads the way with the highest average Mosaic score, followed by Qualcomm Ventures. Salesforce Ventures’ Q1’25 investments include 2 of the largest rounds this quarter — Anthropic ($3.5B) and Together AI ($305M) — signaling the importance of AI in its growth strategy.

We dive into the trends below.

Deals continue their downward trend as investors remain selective

Global CVC deals fell 13% QoQ to 728, the lowest quarterly total since Q1’18. CVC-backed funding also declined 22% to $18.7B. 

Despite the pullback, $100M+ mega-rounds accounted for 59% of total funding, indicating that CVCs are still making large, strategic bets but in a more selective environment.

While the number of deals decreased, the median size of CVC-backed deals increased to $10M — up from $8.9M last year — as CVCs write larger checks for companies they believe will deliver long-term strategic value.

The shift toward fewer but larger deals reflects a broader flight to quality across venture capital. Notable mega-rounds in Q1’25 included Anthropic’s massive $3.5B Series E round, which represented nearly 19% of all Q1 CVC-backed funding globally and showcased the concentration of capital in market-leading companies.

US companies dominate CVC investment dollars

US companies captured 70% of global CVC-backed funding in Q1’25, securing $13.1B despite macroeconomic volatility. The US funding share represents the 2nd quarter in a row at 70% or above, up significantly from the historical norm of ~50% before 2023.

Silicon Valley maintained its position as the epicenter of CVC investment, attracting $7.5B across 97 deals — more than half the total US funding.

Several unicorn rounds powered the US’ strong funding quarter, including those from Anthropic, NinjaOne, Lambda, and Apptronik.

The capital concentration is striking given that US companies represented just 37% of global deal volume (269 of 728 deals). The substantial gap between deal share and funding share highlights a key regional difference in investment approach, with US deals ballooning in size. The median US deal reached $17M in Q1’25 — over 50% more than Europe, the next highest region, at $10.9M.

However, as corporate uncertainty grows due to shifting tariff policies, the US’ funding dominance will be a critical trend to monitor in the coming quarters.

Hear from CBI analysts on the global impact of tariffs

AI continues to command CVC attention and dollars

AI dominated the biggest CVC investments in Q1’25 — securing 7 of the top 10 deals — as CVCs place massive bets on startups with the potential to reshape industries.

CVCs are investing in AI companies across diverse areas. These range from general-purpose AI agents & copilots to hardware applications like Apptronik’s AI-powered industrial humanoid robots.

Other leading CVC-backed AI deals in Q1’25 include:

• Isomorphic Laboratories: $600M (backed by Google Ventures, NVentures) in a record-breaking round for AI-powered drug discovery
• Lambda: $480M (In-Q-Tel, NVentures) for AI computing infrastructure and cloud services
• Together AI: $305M (Prosperity7 Ventures, Salesforce Ventures, SE Ventures, SK Telecom Ventures) for building open-source foundation models and infrastructure
• Harvey: $300M (Google Ventures, OpenAI Startup Fund, REV Venture Partners) for specialized AI solutions for the legal industry
• Innovaccer: $275M (Danaher Ventures, Microsoft’s M12) for healthcare data integration and AI-powered analytics

For parent corporations, these investments go well beyond financial returns. They provide strategic access to technologies that could determine competitive advantage in the AI era.

Track the latest CVC-backed AI deals

Early-stage deals hold at the highest levels in over a decade

Early-stage investments remain at a record share of CVC activity, accounting for 65% of all deals in Q1’25 — matching the same level seen over the past 2 years and up 7 percentage points from where it was in 2021.

The strategic shift comes with increasing commitment levels, as the median early-stage deal size grew to $5.8M in Q1’25. Rather than spreading smaller amounts across many startups, CVCs are making substantial, focused bets on promising early-stage companies.

Regional strategies show notable differences: Asia leads with 39% of early-stage CVC deals, compared to 33% in the US and 21% in Europe. This suggests that corporate investors in Asia are particularly aggressive in securing access to emerging technologies at the earliest possible stage.

Across all markets, this pronounced shift toward early-stage investing reflects a fundamental change in CVC strategy: corporate investors are prioritizing gaining early access to innovation rather than supplying later-stage growth capital, positioning themselves to shape technological development from the beginning rather than joining after validation.

Salesforce Ventures leads with the strongest Q1 portfolio

Among CVCs with 5+ investments in Q1’25, Salesforce Ventures leads with the highest average Mosaic score for its Q1’25 bets (891 out of 1,000), followed by Qualcomm Ventures (840). Salesforce Ventures’ Q1’25 investments include 2 of the largest rounds this quarter: Anthropic ($3.5B) and Together AI ($305M).

Meanwhile, Google Ventures was the most active CVC in Q1’25 with 17 companies backed, followed by Japan-based investors Mitsubishi UFJ Capital and SMBC Venture Capital with 15 companies each. With 11 companies each, In-Q-Tel and Mizuho Capital rounded out the top five, highlighting the dominance of US- and Japan-based corporate investors.

Track top CVC-backed companies by Mosaic score

MORE VENTURE RESEARCH FROM CB INSIGHTS

• State of Venture Q1’25 Report
• State of Fintech Q1’25 Report
• State of Digital Health Q1’25 Report

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Given this momentum, the ecosystem is larger and more challenging to navigate than ever.

Our annual AI 100 list is designed to cut through this noise and highlight the next wave of AI winners, with a focus on early-stage players that are showing strength in terms of market traction, investor quality, and talent.

Leveraging CB Insights datasets such as deal activity, industry partnerships, team strength, investor strength, patent activity, and our proprietary Mosaic Scores, we selected 100 winners out of a cohort of 17K+ companies. We also analyzed CB Insights’ exclusive interviews with software buyers and dug into Analyst Briefings submitted directly to us by startups.

Below, we map out the winners, categorizing them based on their core offering. Key trends and category definitions follow. Customers can track activity of all of these companies in this watchlist. 

Please click to enlarge. Data as of 4/23/25.

CBI customers: Get data on the winners

Key takeaways on the AI 100

1. AI agents dominate the conversation. These applications, which automate tasks and processes for human users, are the next wave of genAI. Having made their way into virtually every horizontal and enterprise function, AI agents are also coming for infrastructure and verticalized applications. AI agents and supporting infrastructure make up 21% of this year’s companies, and the investors we spoke with consistently cited this space as a priority. 
2. ML security has become table stakes. The need to secure AI applications has grown in lockstep with the proliferation of genAI and agentic AI. 46% of strategy team leaders point to security as the primary barrier to genAI adoption, according to a recent CB Insights survey. Machine learning security companies are hardening AI algorithms and foundational models like LLMs, while also defending against increasingly sophisticated AI-powered attacks. 
3. AI observability and governance are critical gaps. Widespread use of AI is exposing the technology’s cracks — hallucinations, lack of orchestration, and output inaccuracies. It’s clear that AI ubiquity can’t exist without robust monitoring. Companies are rising to meet this need. Startups in this year’s list cover areas like observability and governance, while a small cohort also monitors AI agents to ensure reliability and compliance.   
4. The future is physical. Looking ahead, AI will evolve beyond software AI agents to a physical state. Advances in disparate areas of AI development — including robotics, multimodal image and voice models, edge computing, synthetic data, and spatial intelligence — provide the scaffolding for physical AI, which pairs AI software with hardware to take action in physical environments. Industrial humanoids represent an early manifestation of this, while future permutations could include fully autonomous defense drones, home companion robots, and more.
5. Vertical applications are exploding. In 2024, the horizontal companies in this AI 100 cohort received more funding than their vertical and infrastructural counterparts — $1.6B compared to $1.2B each for infrastructure and vertical. But in 2025 so far, the funding picture looks very different: Vertical winners lead the way with $1.1B in funding raised.

Category breakdown

AI INFRASTRUCTURE 

On the foundation model front, infrastructure newcomers are rapidly releasing models that rival industry leaders, signaling a maturing market where technical excellence and novel approaches increasingly compete with raw computing power. We identified winners across large language, edge, reasoning, small language, and multimodal models. 

Meanwhile, as AI applications — particularly agents — become more autonomous and widespread, the need for robust monitoring, governance, and cybersecurity solutions has grown in lockstep. 

We’ve heard this in our conversations with AI investors, as well. Mozilla Ventures, a lead investor in Credo AI, views governance as a strategic imperative. Mohamed Nanabhay, Managing Partner, notes: 

 “…We think that the AI governance sector itself will take on a crucial role of creating value for enterprises, allowing companies that leverage governance to deploy AI faster through the reduction of risk with a greater competitive advantage as a result.”

Category definitions:

DATA

• Synthetic data: Artificially generated or altered information that mimics real-world data without privacy concerns. Aaru uses a multi-agent approach to create population simulations for predictive decision-making applications like consumer behavior and electoral modeling.  
• Data preparation & curation: Tools and platforms that clean, transform, label, and organize data to make it suitable for AI training and deployment, encompassing data cleaning and specialized data processing. Unstructured, for instance, helps organizations capture unstructured data from various documents and convert it into AI-friendly formats such as JSON to train LLMs.
• Vector databases: Solutions that provide enterprises with an easy way to store, search, and index unstructured data at a speed, scale, and efficiency that current relational (and non-relational) databases cannot offer. For example, Qdrant provides an open-source vector database that allows developers to build production-ready applications that use nearest neighbor search functionality.

DEVELOPMENT & TRAINING

• Foundation models: Pre-built AI algorithms and architectures that can be deployed, fine-tuned, or integrated into applications, spanning general-purpose foundation models and specialized domain-specific models. This category includes large language, edge, reasoning, small language, and multimodal AI models. For instance, Archetype AI‘s Newton model processes multimodal sensor data and natural language to provide insights and predictions about physical environments.
• Agent building & orchestration: This category covers AI agent development platforms for building, orchestrating, and monitoring agents. Companies like LangChain provide a framework for building context-aware reasoning applications with tools for debugging, testing, and monitoring app performance across the entire application lifecycle.
• Computer vision & spatial intelligence: Technology that enables AI systems to understand, interpret, and interact with physical spaces and 3D environments, including mapping, navigation, and spatial data processing capabilities. Notably, World Labs develops Large World Models (LWMs) that enable AI systems to perceive, generate, and interact with both virtual and real 3D environments using spatial intelligence.

OBSERVABILITY & EVALUATION

• AI observability platforms: These platforms monitor, measure, and assess AI model performance, reliability, and outputs, including tools for testing, benchmarking, and continuous improvement of AI systems. For instance, Arize’s platform allows teams to monitor, diagnose, and improve the performance of AI models and applications in production through tools based on open-source standards that integrate with existing AI infrastructure.
• Governance: Solutions that establish policies, processes, and controls for responsible AI development and deployment, covering risk management, compliance, ethical oversight, and transparency requirements. For example, Credo AI offers a platform that automates AI oversight, risk management, and regulatory compliance while providing AI auditing to ensure system integrity and fairness.
• Machine learning security (MLSec): Technologies that protect AI systems from vulnerabilities, attacks, and data breaches, including techniques for securing model training, inference, and data pipelines. Solutions developed by companies like Zama enable computation on encrypted data, allowing for privacy-preserving machine learning across industries that require data privacy and security.

ACCELERATED COMPUTING & HARDWARE

• Edge: Platforms that provide the infrastructure and models to operate AI on “edge” devices such as tablets, IoT, autonomous vehicles, or smartphones. For example, EdgeRunner AI constructs an ensemble of small, task-specific models that work together to solve complex problems locally on devices, ensuring data privacy and security for heavily regulated industries.
• Photonics: Solutions that use light (photons) instead of electrons for data processing, with the potential to significantly increase computing speeds. Companies in this category provide memory, interconnects, and system architecture. Xscape Photonics develops bandwidth-efficient photonics solutions to support AI/ML infrastructure. 
• Quantum: Companies providing novel techniques like model compression and hardware to support quantum commercialization. Multiverse Computing provides AI model compression technology to enable quantum AI workloads and processing.
• Chips: Traditional chips, in addition to chips to support new AI technologies. Etched develops chips designed specifically for transformer inference, capable of processing extensive data for applications such as real-time voice agents and content generation.

HORIZONTAL AI

This category includes industry-agnostic solutions across visual media, text, code, audio, and interfaces. These function-specific solutions address common business needs regardless of industry, offering specialized intelligence that complements both vertical applications and foundational infrastructure.

AI agents in particular are beginning to upend the way in which enterprises think about software. Decibel Partners, a lead investor in multi-agent platform Dropzone AI, sees a movement toward productizing agents as full systems. Jéssica Leão, a Partner at Decibel, articulates this vision further:

“…We’re going to see the software world change because, again, you’re selling agents almost as if you’re selling back-end software.”

Horizontal AI solutions are increasingly tailored to serve distinct business functions while remaining broadly deployable. Startups in this category are developing sophisticated AI systems that excel in capabilities like content generation, customer support, process automation, and software development — all of which can be applied across industries. 

Category definitions:

• Content generation: AI systems that create text, images, video, and other media forms — spanning automated content production and multimodal generation. For example, Moonvalley’s genAI video model helps filmmakers by enabling prompt adherence, motion generation, and physics simulation using cleaned, fully licensed data.
• Customer service: AI agents that autonomously handle customer service tasks or augment human agents. Sierra‘s platform, for instance, provides intelligent agents for customer support that engage in personalized interactions and integrate with existing call center technologies.
• Cybersecurity: AI-powered solutions that detect, prevent, and respond to digital threats, vulnerabilities, and attacks, covering network security, threat intelligence, and automated incident response. Companies like Binarly use AI to detect and remediate vulnerabilities in firmware and software supply chains.
• General-purpose humanoids: AI systems embedded in robotic bodies that mimic human capabilities, enabling physical interaction through perception and manipulation. For example, Figure develops autonomous humanoid robots that combine human-like dexterity with AI to perform a variety of tasks across industries like manufacturing, logistics, warehousing, and retail.
• Process automation: Intelligent systems that autonomously handle repetitive business workflows, increasing efficiency by eliminating manual tasks. Orby AI offers a platform that observes enterprise processes and generates executable automations — particularly for complex, data-heavy operations in industries like tech and finance. 
• Software development & coding: AI solutions that assist with software development, code generation, debugging, and programming tasks, including automated code completion tools. For instance, Poolside offers foundation models and APIs that can be fine-tuned using a company’s own codebase and documentation to support internal dev teams.
• Video security: Technologies that enable real-time analysis of video feeds, supporting faster detection and response to security threats. Coram AI develops cloud-based security camera systems with features like real-time AI alerts and natural language video search, allowing businesses to monitor properties remotely without extensive hardware replacements.

VERTICAL AI 

Vertical AI is on the rise, with this year’s vertical winners surpassing the other category winners to capture over $1B in combined funding in 2025 YTD. They span 10 industries that represent a convergence of high-value problems, rich data availability, and regulatory momentum.

Some of the VCs we spoke with see specialization as the way of the future. Lila Tretikov, Partner and Head of AI Strategy at New Enterprise Associates (a lead investor for Twelve Labs, World Labs, and Orby AI), told us:

“We believe that there is going to be specialization, even within the model layer. And there’s going to be innovation in this layer, especially as we look at verticalization for specific use cases.”

The most well-represented verticals on this year’s list are healthcare (8 companies) and life sciences (6 companies). The healthcare industry as a whole is seeing breakthrough applications across multiple AI modalities — from agentic AI systems that can augment clinical workflows, to advanced machine vision for medical imaging analysis, to AI-accelerated drug discovery platforms that dramatically reduce R&D timelines.

This year’s cohort also saw significant representation in gaming & virtual assets (5 companies), finance & insurance (4 winners), and aerospace & defense (4 winners). 

Category definitions:

• Aerospace & defense: AI solutions designed for aerospace engineering, aviation operations, military applications, and defense systems, including autonomous navigation and threat detection technologies. For instance, Quantum Systems creates eVTOL unmanned aerial systems that serve critical defense applications, most notably in Ukraine. 
• Auto & mobility: AI applications for autonomous vehicles, transportation optimization, fleet management, and mobility services. Companies like Wayve are developing AI systems that use LLMs to provide real-time natural language explanations of driving decisions, helping improve users’ confidence.
• Energy: Platforms that optimize energy production, distribution, and sustainability, including battery intelligence and AI assistance for electric grids. For example, Liminal leverages ultrasound and machine learning inspection solutions to improve battery cell quality, cost-effectiveness, and safety while enabling confident scaling of production. 
• Finance & insurance: AI solutions for financial services, banking, investment, and insurance sectors, covering payments, risk assessment, and portfolio monitoring. Skyfire’s financial stack enables AI agents to perform transactions without credit cards or bank accounts, allowing businesses to monetize their products, services, and data through AI agents.
• Gaming & virtual assets: AI technologies that enhance gaming experiences, virtual environments, digital asset management, and immersive entertainment, including content generation and NPC (non-player character) intelligence. Altera‘s platform creates digital human beings that can interact with users and perform tasks autonomously, bringing empathy and human-like traits to digital interactions.
• Healthcare: AI applications focused on clinical care delivery, medical operations, and patient management, including tools for clinical documentation automation, medical imaging analysis, decision support systems, remote patient monitoring, and healthcare supply chain optimization. In the dental field, Overjet provides an AI platform that enhances clinical care through radiographic analysis and optimizes claims processing for providers and payers.
• Life sciences: AI solutions for pharmaceutical research, drug discovery, protein engineering, biological data analysis, and therapeutic development, including platforms for multiomics analysis, antibody design, foundation models for biology, and scientific experiment automation. Lila Sciences has developed a platform that integrates AI with autonomous laboratories to design, conduct, observe, and redesign experiments for scientific discovery.
• Legal: AI tools for legal research, document analysis, contract management, compliance, and legal workflow automation, including case management, due diligence, and contract review. AI-powered tools like Eve help law firms streamline the full case lifecycle from intake to litigation by automating case intake, drafting legal documents, and managing discovery processes.
• Manufacturing: Technology that optimizes industrial processes like factory automation, using virtual development and simulation. PhysicsX applies machine learning to physics simulations that optimize design and engineering processes across industries including aerospace, medical devices, and electric vehicles.
• Supply chain: AI solutions that enhance logistics and supply chain operations, including warehouse management and route optimization & visibility. Dexory combines stock-scanning robots with a digital twin platform to provide real-time inventory and warehouse analytics for logistics and supply chain operations.

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