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 Q1’25

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.

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.

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; Google Ventures 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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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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The humanoid robots market map

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

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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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Its Lattice operating system serves as a digital backbone for autonomous capabilities across land, sea, air, and space domains. Meanwhile, its Arsenal factory platform aims to modernize the defense manufacturing playbook by producing different autonomous systems on demand, potentially slashing production cycles from years to months while reducing costs.

Together, these strategies bring a startup mentality to defense and have helped Anduril reach a potential $28B valuation and $1B in revenue in 2024 — clear signals of traction among investors, government agencies, and global defense firms.

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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. 

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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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Initially known for data processing platforms in the defense and government sectors, Palantir has now embedded AI into its core products — AIP, Foundry, Gotham, and Apollo — to provide analytics and intelligence solutions across industries including automotive, defense, healthcare, manufacturing, and supply chain.

We analyzed Palantir’s investments, partnerships, and product moves since Q1’23 using CB Insights data to identify the 4 key areas driving its next chapter of growth — and the companies it’s aligning with to get there.

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Military technology is entering its AI era.

Funding to AI companies targeting defense applications has reached $1.5B this year. At the current rate, this year will set a new record for the sector.

Public-company execs also have defense on the brain. 

Last quarter saw earnings call mentions of “defense” reach an all-time high, according to CB Insights’ Earnings Transcript Analytics.

Growing geopolitical tensions combined with AI advances are fueling the investment surge. 

Much of the activity centers on multidomain operations (MDO) technologies — integrating systems across land, sea, air, space, and cyber — where AI is accelerating mission planning, threat detection, and battlefield connectivity. 

Below, we look at:

1. Recent partnerships and the year’s biggest deals
2. Anduril’s UUV announcement
3. Top investors in 2025

1. Recent partnerships and the year’s biggest deals

Major defense contractors are forming partnerships with AI startups to pilot more autonomous capabilities. 

For instance, defense contractor L3Harris partnered with Shield AI in February to combine L3Harris’ electronic warfare capabilities with Shield AI’s autonomous flight tech. 

The next month, L3Harris invested in Shield AI’s $240M Series F alongside a16z, Booz Allen Hamilton, and others. 

That round is the 3rd-largest AI defense deal we’ve seen in 2025 so far, surpassed only by:

• Saronic’s $600M Series C. Saronic develops autonomous surface vessels for naval defense.
• Epirus’ $250M Series D. Epirus creates high-power microwave systems for counter-drone and electronic warfare applications.

Meanwhile, last week, SandboxAQ (an Alphabet spinout) raised a $150M extension to its $300M Series E from December. Its AQNav product is a real-time navigation system that combines AI and quantum sensing, with the aim of operating in areas where GPS is jammed or otherwise unavailable.

SandboxAQ is a leader in the quantum sensing market, alongside players like Q-Ctrl and Aosense — both of which partnered with Lockheed Martin last month on quantum-led navigation for GPS-denied environments. 

2. Anduril’s UUV announcement

AI defense leaders are also making gains in commercializing more advanced autonomous systems. 

This week, Anduril unveiled an unmanned underwater drone equipped with torpedo-like capabilities. Anduril was last valued at $14B in August, making it the most highly valued private AI defense firm.

We featured Anduril in several areas of our recent AI in defense tech market map. Customers can use the below links to see how Anduril stacks up against competitors in these markets:

• Loitering munition unmanned aerial vehicles (UAVs): Drones that loiter over an area for extended periods of time, providing intelligence before engaging targets with a precision strike
• Tactical unmanned underwater vehicles (UUVs): Autonomous or remotely operated submersibles that carry out a range of military and strategic tasks below the water’s surface

CBI customers can unlock the full map here.

3. Top investors in AI defense tech in 2025

8VC and a16z rank among the top investors in AI defense tech this year — but they’re outpaced by one peer who has already backed 4 AI defense tech companies in 2025.

CB Insights customers can see who it is using this platform search.

Related CB Insights research:

• The AI in defense tech market map
• State of Venture Q1’25 Report
• The quantum information market map: The companies working on quantum computing, post-quantum cryptography, and more
• Analyzing a16z’s AI investment strategy: How the VC is funding the AI global takeover

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Opportunities across stages and geographies have fueled growth in deal sizes globally. So far in 2025, the median deal size sits at a record $3.5M.

While AI continues to dominate headlines and venture activity, sectors like fintech, digital health, and retail tech all recorded quarterly funding increases as investors diversify beyond core AI infrastructure plays.

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

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

• Quarterly funding jumps to $121B, even as deal count keeps falling
• AI now drives 1 in 5 global venture deals
• Eight early-stage AI companies raise $100M+ mega-rounds
• Early-stage deal sizes pace at an all-time high
• Billion-dollar M&A exits hit a new quarterly record

We also outline the key trends shaping venture dealmaking for the rest of 2025 — from AI agent specialization and the voice AI boom to crypto’s rebound.

Let’s dive in.

Top stories in Q1’25

1. Quarterly funding jumps to $121B, even as deal count keeps falling

Q1’25 saw global venture funding rise to $121B — the highest quarterly total since Q2’22 — driven by OpenAI’s $40B raise, which values the company at $300B. This ties OpenAI with ByteDance as the second-highest-valued private company globally (behind SpaceX at $350B).

The OpenAI funding round — led by SoftBank and backed by Microsoft, Thrive Capital, and others — marks the largest private funding round in history. Even excluding this deal, total funding in Q1’25 would have reached $81B, still the second-highest quarterly figure since Q3’22.

However, global deal count slid for a fourth straight quarter, to 5,846 deals, down 7% QoQ and 28% YoY.

The stark contrast between soaring funding and declining deal count highlights growing capital concentration. 

Mega-rounds (deals worth $100M+) accounted for 70% of all funding this quarter, up from 60% in Q4’24. A total of 145 mega-rounds closed in Q1’25 — the highest quarterly total since Q3’22, which saw 157.

While AI startups remain the primary beneficiaries of this capital concentration — grabbing more than half of the quarter’s funding — other sectors are showing resilience. Fintech funding increased 18% quarter-over-quarter to $10.3B, retail tech rose 18% to $6.5B, and digital health grew 47% to $5.3B.

2. AI now drives 1 in 5 venture deals

The influence of AI on venture capital continues to grow, with AI companies now capturing 20% of all venture deals globally — a new high, and up 2x since OpenAI’s launch of ChatGPT in 2022. 

In absolute numbers, AI companies secured 1,134 deals in Q1’25 — a 7% decline from the previous quarter but still the fourth straight quarter with over 1,100 AI deals.

The composition of AI dealmaking is evolving. Early-stage deals (seed and Series A) made up 70% of all AI deals in Q1’25, down from 75% in full-year 2024. Correspondingly, late-stage deal share has increased from 6% to 9%, indicating market maturation as more AI companies progress to advanced funding stages.

The focus of AI dealmaking has also evolved. While infrastructure investments dominated the early AI boom, we’re now seeing greater emphasis on vertical solutions and application-layer platforms that address specific industry challenges. Notable exceptions exist in emerging categories like voice AI, where infrastructure still attracts significant investment.

Geographically, US-based AI companies secured 52% of global AI deals in Q1’25, while Asia and Europe grabbed 21% a piece.

Explore 15,000+ AI companies in the Expert Collection

3. Eight early-stage AI companies raise $100M+ mega-rounds

Q1’25 set a new record with 8 early-stage AI companies raising rounds of $100M or more. These 8 companies raised a combined $1.8B — with an average round size of $222M — highlighting investors’ willingness to place substantial bets on AI startups earlier than ever.

The companies represent a diverse range of AI applications:

• Isomorphic Laboratories: $600M for AI drug discovery, spun out of DeepMind
• Apptronik: $403M for humanoid robots
• Lila Sciences: $200M for scientific research automation
• The Bot Company: $150M for household robots
• Endless: $110M for AI-led Web3 developer tools
• Nexthop: $110M for cloud-native AI infrastructure
• Reflection AI: $105M for coding AI agents
• MainFunc: $100M for an agentic search engine

What unites these companies is their focus on specific industry or technical challenges — not general-purpose AI models. This same trend appears among late-stage players that raised deals in Q1’25, with companies emphasizing enterprise applications, vertical use cases, and infrastructure optimization. 

The shift from infrastructure to applications also plays out at the tech market level. Among the 1,400+ tech markets that CB Insights tracks, those in the below chart saw the greatest number of AI deals in Q1’25. 

While LLM developers remain the top target for deals, they saw no growth in Q1’25 vs. Q1’24. On the other hand, vertical applications in industrials and healthcare — where AI is measurably improving automation — led in terms of YoY growth.

The top three vertical markets for AI deal growth in Q1’25 were automated guided vehicles (AGVs) and autonomous mobile robots (AMRs), radiology diagnostics — particularly those focused on multiple imaging modalities — and clinical documentation solutions.

See how markets stack up in the CBI Market Index

4. Early-stage deal sizes pace at an all-time high

The median early-stage deal size reached $2.7M in Q1’25, up from $2M in full-year 2024 — a 35% increase. This jump reflects both investors’ willingness to place larger bets on promising teams and the increased capital requirements for competitive AI development.

The increase is particularly notable against a backdrop of declining deal volume — investors are concentrating resources on fewer, more promising opportunities rather than spreading capital across a wide range of startups.

This environment creates both opportunities and challenges for founders. Well-positioned early-stage companies can secure larger initial rounds, but expectations for progress and growth are similarly elevated. The bar for follow-on funding will be higher for mid-stage rounds.

5. Billion-dollar M&A exits hit a new quarterly record

Q1’25 set a new record for billion-dollar M&A activity, with 12 VC-backed exits exceeding $1B in value, surpassing the previous high of 11 seen in both Q1’00 (dot-com bubble) and Q4’20 (peak ZIRP era). These 12 transactions had a combined value of $56B, driven primarily by Google‘s landmark acquisition of cloud security company Wiz.

The Wiz deal now stands as the most valuable M&A deal ever for a VC-backed private company, exceeding Meta‘s WhatsApp acquisition by more than $10B. It also marks Google’s largest acquisition to date — more than double the size of its Motorola Mobility purchase in 2012 — and sets a new record for cybersecurity exits, eclipsing Cisco’s $28B acquisition of Splunk.

The Wiz deal highlights the growing focus among big tech companies on AI-driven cloud security as enterprises prioritize securing their expanding digital footprints. 

It’s also part of a broader trend of high-profile unicorn exits that includes both IPOs (CoreWeave) and M&A transactions (Moveworks, Weights & Biases). 

In fact, looking back to 2024, billion-dollar IPOs delivered strong returns — averaging a 97% increase in market cap post-listing. This bodes well for other IPO hopefuls looking to brave the public markets in the coming months.

Predictions for venture dealmaking in 2025

Below, we use signals from public-company earnings calls, startup financing trends, and business relationships to predict which trends will dominate venture activity through the rest of 2025.

AI agents “niche down” and gain enterprise buy-in

AI agents are transitioning from concept to commercial application. They’ve become a frequent topic on corporate earnings calls, and according to a December 2024 CB Insights survey, 63% of organizations said they are placing significant importance on AI agents over the next 12 months. All respondents reported at least experimenting with agents.

These LLM-based systems represent an evolution beyond copilots. They can autonomously handle complex tasks — from sales prospecting to compliance decision-making — with limited human input. The market is expanding rapidly, with CB Insights data showing that over half of companies in the space were founded since 2023.

Investor interest is surging in parallel. AI agent startups saw more than 200 equity deals in 2024 — and activity is pacing toward similar levels this year.

Key investment themes emerging in the space include:

• Specialized agents for specific business functions (sales, legal, finance)
• Agent orchestration platforms that manage multiple agentic systems
• Safety and alignment tools for ensuring agent behaviors match human intentions
• Enterprise-grade agents with robust permissions and security frameworks

As agents become more capable and trustworthy, adoption will accelerate across industries.

Read more from our AI agent coverage:

• What’s next for AI agents? 4 trends to watch in 2025
• The AI agent market map

CBI customers: Track 250+ AI agent companies

Voice AI takes off amid technical advances

Voice AI is undergoing a technical transformation as models shift toward processing audio directly — bypassing the text intermediation stage — and approaching human-like conversation latency of under 300ms.

This technical progress has fueled substantial investment, with voice AI solutions raising $2.1B in 2024 and nearly $500M in Q1’25. 

One standout is ElevenLabs, which reached $100M in ARR just 3 years after its founding and raised a $180M round in January from investors including a16z, Salesforce Ventures, and Sequoia Capital.

Despite these promising signals, the voice AI market remains in early development. CB Insights data shows approximately 85% of companies in the space are at levels 1-3 on the Commercial Maturity scale. Nearly half are developing or validating their products, while 39% have just begun commercial distribution.

As voice interfaces become more natural and capable, we expect to see investment opportunities emerge in several areas:

• Domain-specific voice applications for industries like healthcare and legal
• Voice AI trained on local languages not typically covered by general-purpose AI systems
• Voice-first UI/UX for both consumer and enterprise applications

Crypto & blockchain rebound

After weathering a prolonged crypto winter, blockchain technologies are experiencing renewed institutional interest. Funding to crypto/blockchain companies reached $6.6B in Q1’25, putting the space on track to surpass $20B in annual funding. Earnings call mentions have climbed accordingly. 

Several crypto companies now rank among the most likely IPO candidates, with platforms like Blockchain.com and Kraken showing IPO probabilities 64x higher than the average company tracked by CB Insights — a notable shift in public-market viability for the sector. 

Another trend to watch is the growing institutional and government focus on stablecoins, as regulators develop frameworks to incorporate these digital assets into the traditional financial system. 

Defense tech comes into focus

Military technology is entering a new era as investment shifts toward autonomous systems and AI-driven capabilities.

According to former Joint Chiefs of Staff Chairman General Mark Milley, smart machines and robotics could account for one-third of the US military presence within the next 15 years.

Funding to AI defense tech startups has already reached $1.5B this year — leading to a projected $6B by year-end. Last quarter saw earnings call discussion of defense reach an all-time high.

Much of this activity centers on multidomain operations (MDO) technologies — integrating systems across land, sea, air, space, and cyber — where AI is accelerating mission planning, threat detection, and battlefield connectivity. Major defense contractors are forming partnerships with AI startups to enhance battlefield management systems, mission planning capabilities, and integrated defense connectivity platforms.

As geopolitical tensions persist, defense tech investment is likely to continue growing, with particular focus on autonomous systems, AI-enhanced battlefield analytics, and advanced cybersecurity solutions for critical infrastructure.

See 240+ AI defense companies in this market map

Conclusion

The venture capital landscape in Q1’25 reflects key contrasts: record funding alongside declining deal count, significant early-stage deals vs. heightened expectations for follow-on capital, and a resurgence in billion-dollar exits despite broader market caution.

AI continues to influence capital allocation decisions across the venture ecosystem, but we’re seeing a shift from general infrastructure investments to specialized vertical applications and industry-specific solutions. Meanwhile, sectors beyond AI are showing resilience, with fintech, digital health, and retail tech all posting quarterly funding increases.

For investors, the data suggests maintaining a disciplined approach to AI investments while remaining alert to opportunities in adjacent sectors. The companies that successfully blend AI capabilities with sustainable business models will emerge as the defining ventures of this era.

For more insights on venture trends and emerging technologies, explore our related resources:

• 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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M&A is back.

Below, we break down what’s driving the surge in deals, then zoom in on Nvidia’s latest purchase.

Buyers on the prowl

Q1’25 has already seen 11 $1B+ deals for VC-backed companies worth a combined $54.5B — blowing past quarters out of the water.

More than half of that value comes from Google’s $33B purchase of Wiz, the biggest VC-backed M&A exit of all time.

It’s not just tech startups — consumer & retail brands are getting snapped up too, like Pepsi’s $2B acquisition of Poppi.

But tech is leading the charge.

M&A activity in the sector rebounded 5% in 2024 and we expect it to gain more steam this year thanks to several factors:

• • Less regulatory pressure: Big tech players like Google are betting on a friendlier dealmaking climate with Lina Khan out as head of the FTC.
  • AI boom: Incumbents are anxious to get their hands on AI assets and infrastructure (see ServiceNow’s acquisition of MoveWorks and SoftBank’s acquisition of Ampere). 
  • Cheaper prices: Tech M&A valuations keep falling, encouraging strategic and financial buyers to get off the sidelines.

Nvidia’s M&A playbook

Among the Mag 7, Nvidia stands out for its aggressive acquisition strategy.

All told, Nvidia has snapped up 7 AI startups since 2021, with 4 of these in just the last year.

Last week it bought Gretel — reports place the exit valuation north of $320M (Gretel’s last disclosed valuation) but less than $1B.

Per CB Insights’ ESP ranking, Gretel is a leader in the synthetic training data market. 

Source: CB Insights — ESP ranking of players in tabular and text-based synthetic training data

Synthetic data offers a potential solve to 3 issues in AI development:

• A diminishing pool of high-quality text data to train more advanced LLMs.
• The need to preserve privacy by using anonymized data, critical to AI adoption in industries like healthcare and finance.
• The absence of real-world data to train physical AI models on tasks like driving cars or piloting humanoid robots.

CBI customers can see our analysis of 50 synthetic data providers here. 

By acquiring Gretel, Nvidia positions itself at the forefront of the synthetic data market and strengthens its position in emerging areas like physical AI.

Nvidia sees the physical domain as the next evolution of AI, according to CB Insights’ earnings call transcripts.

Source: CB Insights — Nvidia Q4 FY 2025 earnings transcript

Back in June 2024, we wrote about how Nvidia is investing in and partnering with companies focused on industrial applications, like digital twins and robotics, which can rely on AI for simulation and training.

See where else the $3T company is targeting growth in our Nvidia strategy map.

Related research from CB Insights:

• Analyzing Nvidia’s growth strategy: How the chipmaker plans to usher in the next wave of AI
• State of Venture 2024 Report
• 7 tech M&A predictions for 2025
• Generative AI is accelerating the timeline for fully autonomous driving

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The AI boom has set the stage for a wave of tech M&A this year.

After 2 consecutive years of decline, tech M&A deals were up in 2024, with some of the largest deals centering on AI. AI companies have also bucked the general downward trend in exit valuations, instead seeing nearly double the median acquisition price from 2023 to 2024.

Using CB Insights’ predictive signals, such as Mosaic and M&A Probability, we’ve identified 7 AI-related areas where we expect to see M&A activity this year, as well as high-potential acquisition targets for each.

See highlights below, and download the full report for the rationale behind each prediction, as well as M&A target shortlists.

Tech M&A prediction highlights

• Big tech players set their sights on humanoid robotic: As physical AI takes off thanks to the rise of LLMs, humanoid robotics is becoming big tech’s next battlefield. Among high-potential acquisition targets, 1x stands out for its dual focus on industrial and consumer humanoids (just in January, it acquired Kind Humanoid to accelerate household robot development). This makes it a prime target for Meta, which recently announced plans to enter the consumer humanoid market.
• Enterprise tech heavyweights compete for AI infrastructure dominance: We’re already seeing strong signals from cash-rich companies such as Cisco and IBM, which are future-proofing their business models with AI investments. Hardware-aware AI optimization players CentML and Nota AI — which help accelerate AI model deployment while reducing compute costs — appear in our AI infrastructure acquisition target list. These companies have already shown quantifiable efficiency improvements as well as validation from Nvidia as a partner or investor.

Source: CB Insights advanced search. Data is dynamic (as of 2/27/2025).

• Data center energy demands fuel interest in cooling tech: Companies offering immersion and liquid cooling solutions enjoyed a funding rebound last year, attracting a combined $120M in fresh funding. Hypertec and Submer are high-potential acquisition targets in this space.
• Professional services firms seek AI capabilities: GenAI is coming for knowledge jobs — and leading professional services firms are buying AI capabilities to get ahead of it. One area where we see high M&A potential for professional services firms is to cater to clients’ responsible AI needs, with potential acquisition targets such as Lasso Security and HydroX AI.
• Pharma companies target AI drug discovery startups: AI drug discovery M&A is surging, with 12 deals in the sector since 2023. That M&A deal volume reflects both a maturing technology and growing urgency among pharma players to bring AI tech in-house.
• SaaS giants fortify their offerings with AI agent acquisitions: While some believe AI agents signal the death of SaaS companies, we anticipate SaaS leaders will acquire AI agent companies to avoid disruption. We’re already starting to see this happen with ServiceNow acquiring Moveworks for close to $3B in March 2025.

Source: CB Insights — ServiceNow Acquisition Insights

• Coding AI agents drive next wave of AI agent consolidation: Explosive growth, soaring valuations, a fractured AI agent landscape, and rising doubts about revenue defensibility make the coding AI agents market ripe for consolidation. While some players like Cursor look too expensive for an acquisition, we’ve identified Warp, Vidoc, and Bito as likely targets with high Mosaic scores and higher-than-average M&A Probabilities.

What is Mosaic?

Mosaic is CB Insights’ proprietary metric that measures the overall health and growth potential of private companies using non-traditional signals. Mosaic is widely used as a target company and market screener to identify high-potential emerging tech companies, typically defined as those with a score of 510 or higher.

What is M&A Probability?

M&A Probability is CB Insights’ proprietary signal that measures a private company’s chance of an M&A exit within the next 2 years. It is used to quickly screen and triangulate companies based on exit likelihood.

Combining both Mosaic Score and M&A Probability makes it easy to shortlist acquisition targets.

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While AI copilots have already made inroads across industries, the next evolution — autonomous agents with greater decision-making scope — is arriving quickly. AI agent startups raised $3.8B in 2024 (nearly tripling 2023’s total), and every big tech player is already developing AI agents or offering the tooling for them.

Implications for enterprises will be far-reaching, from altering workforce composition (with new hybrid teams of humans and AI agents) to maximizing operational efficiency through full automation of routine tasks. 

Below we identify 170+ promising startups developing AI agent infrastructure and applications. 

CBI customers: Track 250+ AI agent companies

We selected companies for inclusion based on Mosaic health scores (500+) and/or funding recency (since 2022). We included private companies only and organized them according to their primary focus. This market map is not exhaustive of the space.

Want to be considered for future AI agent research? Brief our analysts to ensure we have the most up-to-date data on your company. 

Outlook on AI agents

Fully autonomous agents remain limited due to issues pertaining to reliability, reasoning, and access. Most agent applications today operate with “guardrails” — within a constrained architecture where, for example, the LLM-based system follows a decision tree to complete tasks. 

Agents featured on this map include some combination of the following components: 

• Reasoning: Foundation models that enable complex reasoning, language understanding, and decision-making. These models evaluate information and form the cognitive core of the agent.
• Memory: Systems that store, organize, and retrieve both short-term contextual information and long-term knowledge.
• Tool use: Integration capabilities that allow agents to interact with external applications, APIs, databases, the internet, and other software. 
• Planning: The agent’s architecture for breaking down complex tasks into more manageable steps, reflecting on performance, and adapting as necessary.  

We expect more startups to move up the scale of autonomy as AI capabilities advance. Improvements in reasoning and memory will enable more sophisticated decision-making, adaptability, and task execution.

For example, in September 2024, legal AI startup Harvey announced that OpenAI’s o1 reasoning model, supplemented with domain-specific knowledge and data, was enabling it to build legal agents. The company, which raised $300M at a $3B valuation in February 2025, has doubled its sales force in the last 6 months, indicating rising market demand.

While the above market map highlights the private landscape (with a focus on enterprise applications), tech giants and incumbents are also launching agents. We predict big tech and leading LLM developers will own general-purpose AI agents, but there are many opportunities for smaller, specialized players. 

Looking ahead, watch for new form factors outside of the copilot/chatbot interface that will push the boundaries of what an “agent” is. Early indications of this include “AI-native” workspaces — tools and platforms built from the ground up around AI capabilities, rather than layering AI features on top of a traditional product. For instance:

• Eve’s legal platform aims to automate aspects of the whole case lifecycle (from case intake to drafting). 
• Hebbia’s Matrix product builds spreadsheets that mine information from files (in rows) and deliver answers to questions (in columns), proactively discovering, organizing, and surfacing data.
• With its Dia product, The Browser Company is exploring web browsing interfaces that can summarize content, automate repetitive web tasks, and even anticipate next actions.

Category overview

AI agent infrastructure

This segment covers companies building agent-specific infrastructure. (We excluded general genAI infrastructure markets like foundation models and vector databases from the map.)

Development tools

A diverse ecosystem of tools has emerged to support agents’ development. These range from memory frameworks like Letta that enable persistent, retrievable memory across interactions; to tools that allow agents to take action via integration (e.g., Composio), authentication (e.g., Anon), and browser automation (e.g., Browserbase).

Another set of companies is giving agents more utility across payments (which includes companies developing crypto wallets for agents as well as virtual cards) and voice (development platforms and tools for testing AI voice applications as well as speech models).

Meanwhile, demand for simplified, comprehensive deployment options is driving the rise of AI agent development platforms — the most crowded infrastructure market on our map. 

LLM developers including Cohere (with its North AI workspace) and Mistral have launched their own agent development frameworks, while Amazon, Microsoft, Google, and Nvidia all offer AI agent development tooling. With many enterprises favoring established vendors due to lower risk, big tech companies have significant advantages here.

Trust & performance

Concerns around reliability and security have helped establish a market for agent evaluation & observability tools. Early-stage companies are targeting applications such as automated testing (e.g., Haize Labs) and performance tracking (e.g., Langfuse). 

Multi-agent systems, where specialized sub-agents work together to complete tasks, also show promise in improving accuracy. Insight Partners-backed CrewAI’s multi-agent orchestration platform is reportedly already used by 40% of the Fortune 500. 

Vendors are also tackling reliability concerns directly. Based on our briefings with 20+ AI agent startups in Q1’25, companies are using 5 primary methods to build user trust: 

1. Transparency
2. Human oversight
3. Technical safeguards
4. Security & compliance
5. Continuous improvement 

Horizontal applications & job functions

Horizontal AI agent startups make up nearly half of the map and overall landscape. 

This segment primarily features startups targeting enterprises, with industry-agnostic applications across job functions like HR/recruiting, marketing, and security operations. Companies in the productivity & personal assistants market, including OpenAI with its Operator agent, are targeting consumers and employees directly.  

The AI agent markets with the most traction — based on companies’ median Mosaic health scores — are customer service and software development (which includes coding and code review & testing agents). These markets are also among the most crowded due to the value agents bring to well-defined workflows and testable environments. 

We see this reflected in adoption, particularly at the customer service layer: Among 64 organizations surveyed by CB Insights in December 2024, two-thirds indicated they are using or will be using AI agents in customer support in the next 12 months. 

Overall, horizontal AI agent applications are more commercially mature compared to the infrastructure and vertical segments, with over two-thirds of the market deploying or scaling their solutions based on CBI Commercial Maturity scores. 

Vertical (industry-specific) applications

We expect increasing verticalization as startups carve out niches by solving industry-specific customer problems, especially in areas with strict regulatory scrutiny and data sensitivity.

This category features companies catering to industries including: 

• Financial services & insurance: The most crowded vertical category on the map with 11 companies, startups here are targeting a variety of finserv workflows such as financial research (Boosted.ai and Wokelo), insurance sales & support (Alltius and Indemn), and wealth advisory prospecting & operations (Finny AI and Powder). 
• Healthcare: Solutions in this market aim to reduce the volume of manual tasks for healthcare professionals across use cases like clinical documentation, revenue cycle operations, call centers, and virtual triage. Solutions from companies like Thoughtful AI (revenue cycle operations) and Hippocratic AI (staffing marketplace) are targeting end-to-end healthcare workflows. 
• Industrials: These companies look to optimize processes and equipment — including control systems, robots, and other industrial machines — without relying on consistent human intervention. For example, Composabl launched an agent platform in May 2024 that uses LLMs to create skills and goals for agents that can control industrial equipment. Public companies like Palantir are also active in this space. Learn more in our industrial AI agents & copilots market map. 

RELATED RESEARCH

• What’s next for AI agents? 4 trends to watch in 2025
• The enterprise AI agents & copilots market map
• The Multi-Agent AI Outlook
• Future of the workforce: How AI agents will transform enterprise workflows

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