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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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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GenAI adoption is changing how insurance companies operate, incumbents are meeting new competitors, and startups face a more selective dealmaking environment focused on profitability.

Industry leaders echo this reality: commentary from the InsurTech NY 2025 Spring Conference emphasized an increasingly fast-paced — and fast-changing — insurance industry.

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• Bolttech
• ClearSpeed
• DeepOpinion
• Hercules
• Laka
• Neat
• Optalitix
• Quantexa
• Reserv
• Sprout.ai
• WhatFix
• YuLife

We’ve used generative AI, combined with our proprietary data on these companies and their markets, to create the following scouting reports — in just one click on CB Insights.

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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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Insurtech does not exist in a vacuum, and the broader venture environment is centered on AI funding. In Q1’25, OpenAI raised nearly 31 times the total funding of all insurtechs combined, underscoring where capital is flowing.

AI capabilities are poised to reshape the future of insurance — whether through 100-day-old startups or 100-year-old incumbents adapting to a new competitive reality.

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

Key takeaways from the report include:

• Insurtech dealmaking increases for the first time in a year. Global insurtech deal count increased 17% quarter-over-quarter (QoQ), from 83 in Q4’24 to 97 in Q1’25. Property & casualty insurtech drove the increase, from just 51 deals — a near 8-year low — in Q4’24 to 70 in Q1’25.
• Median insurtech deal size tumbles 35% in 2025 YTD (year to date) to $4.0M. The median insurtech deal size has not been lower since 2019 ($3.4M). The decline stands out because median deal sizes across the broader venture environment rose 17% YTD to $3.5M, while insurtech’s fell.
• Early-stage insurtech funding reaches a nearly 8-year low — $179M. Early-stage insurtech funding fell 35% year-over-year (YoY) from $277M in Q1’24.
• Late-stage insurtech dealmaking paints a cautious growth picture. The 7 insurtechs that raised Series D+ deals in Q1’25 saw median headcount growth of just 3% over the past 12 months — far lower than insurtechs raising at earlier stages.
• Silicon Valley sees 1 in 5 global insurtech deals. Silicon Valley’s share of global insurtech equity deals has nearly doubled YoY, from 10.9% in Q1’24 to 21.9% in Q1’25. Funding to Silicon Valley-based insurtech increased to $0.3B — the highest level since Q4’23 ($0.4B).

Insurtech dealmaking increases for the first time in a year

Insurtech deal count increased 17% QoQ, from 83 deals in Q4’24 to 97 in Q1’25 — a reversal of the broader venture trend, where deal count declined 7% over the same period.

The rebound was driven by property & casualty insurtech, which jumped from just 51 deals — a near 8-year low — in Q4’24 to 70 in Q1’25. Meanwhile, life & health insurtech saw deal count dip to 27 in Q1’25.

This increase in activity followed an abnormally weak Q4, when funding had fallen to $0.8B. In Q1’25, insurtech funding surged 63% to $1.3B — slightly above the 10-quarter average of $1.2B. Notably, insurtech was the only fintech vertical to post a funding gain this quarter.

Nearly $400M toward three $100M+ mega-round deals contributed to the broader funding rebound:

• Quantexa, a data management and financial crime prevention platform, raised a $175M Series F deal.
• Openly, a homeowners-focused general agency and program administrator, raised a $123M Series E deal.
• Instabase, an AI platform for unstructured data, raised a $100M Series D deal.

Explore Quantexa’s $2.6B AI-driven rise with the full scouting report

Future implication: These mega-rounds signal investors’ readiness to write large checks for select insurtechs — even in a cautious funding environment. For incumbents, this underscores the importance of tracking well-capitalized startups that could pose competitive threats through 2025.

Median insurtech deal size tumbles in Q1’25

Half of the quarter’s top 10 insurtech deals went to AI-centered startups: Quantexa, Instabase, Nirvana, Taktile, and Naked. But unlike the broader venture market, insurtech lacked the depth of large-dollar AI deals needed to lift the median.

While the average insurtech deal size ticked up 6% to $15.8M in 2025 YTD, the median insurtech deal size tumbled from $5.4M in 2024 to $4.0M — its lowest point since 2019 ($3.4M). This trend diverged from the broader venture environment, where a spike in $100M+ mega-rounds pushed medians higher.

Early-stage insurtech saw a similar dynamic, with median deal sizes declining to $3.0M in 2025 YTD — even as the broader venture landscape saw an increase, from $2.0M in 2024 to $2.8M. Fertility-focused platform Gaia raised the largest early-stage insurtech deal in Q1’25 ($15M Series A).

Track 2.5K+ insurtech companies

Future implication: Smaller check sizes could give incumbent insurers an opening to partner with capital-constrained insurtechs — potentially securing more favorable terms and early access to emerging tech that would be harder to land in a hotter market.

Early-stage insurtech funding reaches a nearly 8-year low

Early-stage insurtech startups raised just $178.5M across 56 deals in Q1’25 — the lowest total since Q4’16 ($162.8M). Funding has dropped sharply over the past year, falling 35% from Q1’24.

Early-stage insurtech deal share has also tumbled over the past few years. In 2022, 71% of deals went to early-stage insurtechs, while in 2025 YTD, it was just 58%.

Still, the quarter delivered one notable early-stage highlight: AI claims platform Assured became just the second new insurtech unicorn since Q4’23. The startup raised an undisclosed Series A round at a $1B valuation, backed by ICONIQ Capital and Kleiner Perkins. 

Assured also ranks in the global top 4% of companies for hiring momentum and is actively prioritizing genAI-focused hires:

CBI customers: Explore all of Assured’s Hiring Insights

Future implication: The sustained drop in early-stage insurtech funding risks shrinking the industry’s future innovation pipeline. To stay ahead, insurance execs should prioritize identifying and building relationships with promising startups now — before competition for a smaller pool of standouts intensifies.

Late-stage insurtech dealmaking paints a cautious growth picture

The 7 insurtechs that raised Series D+ rounds in Q1’25 posted median 12-month headcount growth of just 3% — significantly lower than their earlier-stage peers. Only one of them — insurance customer communication platform Ushur — saw double-digit growth over the same period.

Ushur is also the only insurtech among the 7 with an above-average M&A probability within the next 2 years. This signals a potential standstill in the late-stage insurtech market, especially as the IPO pipeline remains frozen — just 2 insurtechs have gone public since 2023.

CBI customers: Ask ChatCBI a question about Ushur’s Scouting Report

Future implication: With just 3% median headcount growth, late-stage insurtechs are showing signs of stagnation. In a market where public investors expect clear growth momentum, more of these companies may be pushed toward M&A exits — often at compressed valuations.

Silicon Valley sees 1 in 5 global insurtech deals

Silicon Valley has now seen 2 consecutive quarters of elevated insurtech dealmaking. The share of global insurtech deals to Silicon Valley-based startups nearly doubled YoY, rising from 10.9% in Q1’24 to 21.9% in Q1’25. Comparatively, 9% of deals across the broader venture environment went to Silicon Valley-based companies in Q1’25.

2 of the quarter’s top 5 insurtech deals went to Silicon Valley-based insurtechs: Instabase and Nirvana ($80M Series C). As a result, Silicon Valley’s insurtech funding in Q1’25 increased to $0.3B — the highest level since Q4’22 ($0.4B). By comparison, Europe’s insurtech market saw $0.4B in funding across 26 deals in Q1’25, slightly edging out Silicon Valley’s total.

Silicon Valley also saw a major insurtech exit in Q1’25: Munich Re announced its acquisition of Palo Alto-based Next Insurance — one of insurtech’s most-promising startups — at a $2.6B valuation.

Future implication: As the world’s premier tech ecosystem, Silicon Valley remains a leading indicator for insurtech innovation. Insurance executives should track tech talent migration into insurtech as a signal of where future competitive threats may emerge.

MORE INSURTECH RESEARCH FROM CB INSIGHTS

• Our 6 predictions for the insurance space in 2025
• How genAI is reshaping the insurance value chain
• Insurtech 50: The most promising insurtech startups of 2024

The post State of Insurtech Q1’25 Report appeared first on CB Insights Research.

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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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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• CLARA Analytics
• Counterpart
• Empathy
• Federato
• Hyperexponential
• INSTANDA
• OutSystems
• Pinpoint Predictive
• Replicant
• Tremendous
• Upstage

We’ve used generative AI, combined with our proprietary data on these companies and their markets, to create the following scouting reports — in just one click on CB Insights.

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Now, the strategic question for insurers isn’t whether to adopt generative AI but how quickly.

We’ve developed 6 predictions — informed by CB Insights datasets, including financing and acquisition data, Business Relationships, Earnings Transcripts, and Exit Probability — that we think will guide competitive dynamics over the coming year:

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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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Just 113 investors made at least 2 equity insurtech investments during the year — a 72% drop from the high of 406 investors in 2021. As a result, insurtech dealmaking dropped to 362 deals, the lowest annual total since 2016.

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

Key takeaways from the report include:

• Insurtech dealmaking and funding continue to decline. Deal count fell 28% year-over-year (YoY) to 362 deals in 2024, while funding dropped 4% to $4.5B. Insurtech deals and funding are both at recent lows.
• Quarterly funding to P&C insurtechs is in the gutter. P&C funding dropped 43% quarter-over-quarter (QoQ) to $0.4B in Q4’24 — a 7-year low — with annual funding also declining to $2.6B. The year’s 2 largest deals in P&C went to AI-focused startups Altana AI and Akur8, highlighting investors’ appetite for specialized AI opportunities.
• Silicon Valley is dethroned as insurtech’s funding capital. Silicon Valley’s share of global insurtech funding dropped dramatically from 20% in 2023 to 10% in 2024, surpassed by New York at 15%. This was the first time since 2018 that Silicon Valley wasn’t No. 1.
• Early-stage insurtechs raise record-high deal sizes. The median early-stage insurtech deal size surged 52% YoY to $3.8M in 2024 — outpacing the broader venture landscape — as investors concentrate on a more selective group of innovators.
• Recently funded insurtechs show stronger business fundamentals and more efficient growth trajectories. Insurtechs that raised funding in 2024 have grown employee headcounts by a median of 20% over the last 12 months, far surpassing the 3% growth among those that raised during the funding boom of 2021.

Insurtech dealmaking and funding continue to decline

Insurtech deal count fell 28% YoY, from 500 deals in 2023 to 362 in 2024. The decline outpaced the broader venture environment, which saw deal count fall 19% YoY. 2024 was the worst year for insurtech dealmaking since 2016 (328 deals).

Deal volume among leading investors has also decreased. The number of investors that made 5 or more equity insurtech investments has fallen from 57 in 2021 to just 7 in 2024. Those that remain active now operate in a more favorable environment due to reduced competition across the marketplace.

Insurtech funding declined in 2024 as well, though by only 4% YoY. 

CBI customers: Track 2.5K+ insurtech companies

Quarterly funding to P&C insurtechs is in the gutter

Q4’24 marked a 7-year low for P&C insurtech funding, which fell 43% QoQ to $0.4B. The decline caused broader insurtech funding to halve QoQ, from $1.4B in Q3’24 to $0.7B in Q4’24.

P&C deal count also fell 10% QoQ to 45 in Q4’24, the lowest level since Q2’16.

Annual P&C insurtech funding declined to $2.6B in 2024, a 7-year low, underscored by just 2 P&C insurtech startups raising $100M+ mega-round deals: Altana AI, which offers an AI-powered supply chain risk platform, and Akur8, an AI-powered pricing platform. Those deals signal appetite for specialized AI products for the insurance industry, coinciding with a global surge in AI funding to over $100B last year.

Comparatively, life & health insurtech saw an increase in annual funding and dealmaking. Funding increased 64% YoY to $1.8B in 2024, while deals ticked up from 126 in 2023 to 128 in 2024.

Silicon Valley is dethroned as insurtech’s funding capital

The share of global insurtech funding to Silicon Valley-based startups halved YoY, falling from 20% in 2023 to 10% in 2024. Comparatively, New York led the way with 15% of global insurtech funding share in 2024, more than doubling from 7% the year prior.

Silicon Valley is the world’s leading tech ecosystem, and venture-wide funding to the region’s startups soared last year amid a boom in AI investment. Given the ecosystem’s prominence, diminished insurtech activity in Silicon Valley could lead to missed opportunities for insurance-focused AI advancements.

See how Silicon Valley fared in the broader venture market

Early-stage insurtechs raise record-high deal sizes

The median insurtech deal size increased from $4.1M in 2023 to $5.2M in 2024.

The increase was fueled by early-stage insurtechs, which saw median deal size surge 52% YoY, from $2.5M in 2023 to $3.8M in 2024. The size and growth rate both beat out the broader venture environment, where early-stage deal size increased 17% YoY to $2.1M.

Combined with the broader decline in dealmaking, larger check sizes indicate that investors are concentrating their investments on fewer bets. For the insurance industry, this dynamic points to a slimmer insurtech landscape with fewer high-growth participants moving forward.

On the other hand, late-stage insurtech deal sizes declined 19% YoY from $40M in 2023 to $32.5M in 2024.

The decline coincides with a restricted exit environment: Insurtech M&A exits fell from 57 in 2023 to 35 in 2024. 

Nevertheless, notable exits include CCC Intelligent Solutions’s acquisition of EvolutionIQ in December at a valuation of $730M, as well as Applied’s purchase of Planck in July. Both acquisitions targeted genAI-enabled startups, signaling a broader appetite for genAI insurance offerings.

Recently funded insurtechs show stronger business fundamentals

Insurtechs that raised funding in 2024 are growing headcounts faster than other insurtechs, by a median of 20% over the last 12 months and 40% over the last 24 months.

Comparatively, median headcount growth among insurtechs that raised a funding round at the height of the funding boom in 2021 is marginal — just 3% over the last 12 months.

The higher growth rates of recently funded insurtechs suggest a new breed of companies with stronger fundamentals — they’re not only able to raise capital in a selective market but are also demonstrating more efficient growth than their 2021-funded counterparts.

By the same logic, investors and partners (like established brokers and carriers) should monitor the landscape for outliers that represent organic growth opportunities — such as insurtechs that haven’t raised funding in several years but continue to grow headcount at a steady clip.

See the fastest-growing insurtechs by headcount growth

MORE INSURTECH RESEARCH FROM CB INSIGHTS

• How genAI is reshaping the insurance value chain
• Insurtech 50: The most promising insurtech startups of 2024
• ITC Vegas 2024: Insurance is facing an AI inflection point
• Tech Transforming the World: The Game Changers Roundtable

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Companies are responding by developing solutions like fire surveillance drones to better monitor wildfires, as well as firefighting robots to minimize the severity when they occur. In fact, over 500 US fire departments have already deployed surveillance drones.

To help companies and governments understand the current wildfire tech landscape, we mapped 130 companies across 15 markets. We then organized tech markets by the wildfire lifecycle: 

• Prevention & preparedness: Solutions in this category help forecast extreme weather events — including wildfires — and assess their damage potential. We break this category down into: 1) broader climate & weather risk; and 2) wildfire risk, which includes solutions specifically designed for wildfires.
• Detection & monitoring: These solutions use cameras, sensors, and analytics platforms to detect outbreaks early and track their progression to aid firefighting strategies.
• Firefighting: These technologies — such as drones and robots — support the suppression of wildfires or help create firebreaks to limit their spread.
• Damage assessment: This includes solutions to evaluate the destruction caused by wildfires after they occur.

Please click to enlarge.

To identify players for this market map, we included startups with a Mosaic score of 400 or greater and leading corporations developing wildfire tech. Categories are not mutually exclusive and are not intended to be exhaustive.

Track Mosaic health scores for companies in these markets

Market descriptions

Click the market links below for info on the leading companies, funding, and more.

Prevention & preparedness: Climate & weather risk

Climate & weather financial risk modeling focuses on quantifying the financial impacts of climate change and severe weather events, helping businesses forecast and mitigate monetary losses. Leading companies like Bloomberg and Morningstar serve many industries, from agriculture to insurance to government.

Geospatial analytics analyzes and interprets geographic data (e.g., satellite imagery, GIS) for various industries, providing spatial insights and risk assessments. Startups in this market have raised a combined $508M since 2023 — the most funding of any market in this map.

Weather risk intelligence emphasizes real-time weather monitoring and predictive modeling to reduce operational disruptions and manage day-to-day weather-related risks.

Climate risk intelligence provides deeper analysis of long-term climate change hazards, guiding strategic decision-making and resilience planning for businesses and governments.

Prevention & preparedness: Wildfire risk

Catastrophe modeling simulates large-scale natural disasters (e.g., hurricanes, earthquakes) to estimate potential losses, primarily for insurance and reinsurance purposes.

Wildfire risk intelligence zeroes in on wildfire hazards with analytics and forecasting tools, helping organizations anticipate fire spread and prioritize mitigation. This market has the highest average company Mosaic health score (662 out of 1,000) among wildfire-specific tech markets.

Detection & monitoring

Wildfire detection cameras use specialized imaging (thermal, infrared) to spot fire signatures early and relay alerts from fixed vantage points.

Wildfire detection sensors are ground-based devices that monitor environmental conditions (e.g., temperature, smoke) to detect potential fires in real time.

Fire surveillance drones provide aerial monitoring of wildfires using sensors like thermal imaging, enhancing situational awareness and firefighter safety. Companies in this market typically offer drones for a wider set of applications beyond wildfires. For example, Skydio, which has raised $400M since 2023, serves industries such as industrial inspection and defense, in addition to fire surveillance.

Wildfire detection & monitoring platforms integrate satellite/aerial data, IoT sensors, and AI in a software platform to track and predict wildfire behavior at scale. ICEYE and Pano AI rank as leading startups here, offering solutions for enterprises and governments through platforms that use advanced imaging systems and AI models to predict potential wildfire locations and facilitate real-time detection and monitoring.

Firefighting

Firefighting drones actively suppress fires by delivering water or fire-retardant agents, often equipped with thermal imaging to pinpoint hotspots. This is among the most nascent markets in the map, with 89% of deals since 2023 going to early-stage companies.

Firefighting robots are ground units equipped with sensors and suppression tools (e.g., water cannons), enabling safer and more efficient fire combat in hazardous areas.

Autonomous heavy equipment encompasses self-operating machinery (e.g., bulldozers, loaders) used in construction, mining, or creating firebreaks, reducing human risk.

Damage assessment

Drone inspection & damage assessment uses drones to capture high-resolution imagery of properties for quicker, more accurate insurance claims evaluations.

Aerial & satellite claims assessment leverages imagery from planes or satellites to evaluate property damage — often focused on large-scale or remote loss scenarios.

RELATED RESOURCES FROM CB INSIGHTS:

• Weather risk intelligence funding surges as extreme weather events pile up 
• Wildfires are causing insurers to leave markets. Can wildfire risk analytics reverse this trend? 
• The Aerospace & Space Tech expert collection
• The Insurtech expert collection
• The satellite & geospatial tech market map
• The AI in defense tech market map

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However, global CVC deal count dropped to its lowest level since 2018 as CVCs become more selective.

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:

• CVC-backed funding grows, deal activity slows. Global CVC-backed funding increased 20% YoY to $65.9B, but deal count fell to 3,434, the lowest level since 2018. All major regions saw deal volume declines, with Europe dropping the most at 10% YoY.
• CVCs are all in on AI. AI startups captured 37% of CVC-backed funding and 21% of deals in 2024 — both record highs. Counter to the broader decline in deals, CVCs ratcheted up AI dealmaking by 13% YoY as they race to secure footholds in the space before competitors gain an insurmountable edge.
• The flight to quality continues. Among deals with CVC participation, the annual average deal size hit $27.3M in 2024, tied for the second highest ever. Amid fewer deals, CVCs are increasingly aggressive when they do decide to invest.
• Early-stage deals dominate. Early-stage rounds comprised 65% of 2024 CVC-backed deals, tied for the highest share in over a decade. Biotech startups made up half of the top 20 early-stage deals.
• CVC-backed funding plummets in Asia. In 2024, Asia’s CVC-backed funding dropped 34% YoY to $7B — the lowest level since 2016. China is leading the decline, with no quarter in 2024 exceeding $0.5B in funding. CVCs remain wary of investing in the country’s private sector.

We dive into the trends below.

CVC-backed funding grows, deal activity slows

Global CVC-backed funding reached $65.9B, a 20% YoY increase. The US was the main driver, increasing 39% YoY to $42.8B. Europe also saw CVC-backed funding grow 18% to $12.3B, while Asia declined 34% to $7B.

$100M+ mega-rounds also contributed to the rise, ticking up 21% YoY to 141 deals worth over $32B in funding.

Meanwhile, deal count continued its decline, as both annual (3,434 in 2024) and quarterly (806 in Q4’24) totals reached their lowest levels in 6 years.

Annual deal volume fell by at least 6% YoY across each major region — the US, Asia, and Europe — with Europe experiencing the largest decline at 10%.

However, Japan-based CVC deal volume remains near peak levels, suggesting a more resilient CVC culture compared to other nations. Two of the three most active CVCs in Q4’24 are based in Japan: Mitsubishi UFJ Capital (21 company investments) and SMBC Venture Capital (15).

Track recent activity from 1,000+ CVCs

CVCs are all in on AI

AI is driving CVC investment activity, much like the broader venture landscape. In 2024, AI startups captured 37% of CVC-backed funding and 21% of deals, both record highs.

In Q4’24, the biggest CVC-backed rounds went primarily to AI companies. These include:

• AI search startup Perplexity’s $500M Series C, backed by Nvidia’s NVentures 
• Coding AI copilot Poolside’s $500M Series B, backed by the venture arms for Citigroup, HSBC, Capital One, LG, eBay, and Nvidia
• AI computing processor developer Lightmatter’s $400M Series D, backed by GV

CVCs are also investing in the energy companies powering the AI boom, such as Intersect Power, which raised the largest round at $800M (backed by GV).

Expect the trend to continue into 2025, as emerging AI markets mature further, such as AI agents & copilots for enterprise and industrial use cases; AI solutions for e-commerce, finance, and defense; and the computing hardware necessary to power these technologies.

The flight to quality continues

In 2024, the annual average deal size with CVC participation reached $27.3M, a 34% YoY increase and tied for the second highest level on record, exceeded only by the low-interest-rate environment of 2021.​

Median deal size also increased, though only by 8% to $8.6M.

Even though the number of CVC-backed deals declined in 2024, the increase in average annual deal size reflects a focus on companies with strong growth prospects. CVCs are prioritizing quality and committing more funds to a select group of high-potential investments.

Early-stage deals dominate

Early-stage rounds (seed/angel and Series A) made up 65% of CVC-backed deals in 2024, tied for the highest recorded level in more than a decade.​

In Q4’24, biotech companies were the early-stage fundraising leaders, accounting for 10 of the 20 largest early-stage deals. Biotech players City Therapeutics, Axonis, and Trace Neuroscience all raised $100M+ Series A rounds, with City Therapeutics and Axonis notably receiving investment from the venture arms of Regeneron and Merck, respectively.

Among all early-stage CVC-backed companies, the largest round went to Physical Intelligence, a startup focused on using AI to improve robots and other devices. Physical Intelligence raised a $400M Series A with investment from OpenAI Startup Fund.

Explore CVCs’ top early-stage company targets in Q4

CVC-backed funding plummets in Asia

Asia’s CVC-backed funding continued its downward trend in 2024, decreasing 34% YoY to $7B.

China was the main driver, with CVC-backed funding coming in at $0.5B or less every quarter in 2024.​ CVCs remain wary of investing in startups in the nation, which faces a variety of economic challenges, including a prolonged real estate slump, cautious consumer spending, strained government finances, and weakened private sector activity amid policy crackdowns.

In Japan, on the other hand, CVC activity remains robust. In 2024, funding with CVC participation ($1.7B) remained on par with the year prior, while deals (502) actually increased by 11%.

MORE VENTURE RESEARCH FROM CB INSIGHTS

• State of Venture 2024 Report
• State of Fintech 2024 Report
• State of Digital Health 2024 Report

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Venture funding surged past the $100B mark for the first time as AI infrastructure players pulled in billion-dollar investments. A wave of M&A deals and rapidly scaling AI unicorns further underscored the tech’s momentum.

Download the full report to access comprehensive data and charts on the evolving state of AI across exits, top investors, geographies, and more.

Key takeaways include: 

• Massive deals drive AI funding boom. AI funding hit a record $100.4B in 2024, with mega-rounds accounting for the largest share of funding we’ve tracked to date (69%) — reflecting the high costs of AI development. Quarterly funding surged to $43.8B in Q4’24, driven by billion-dollar investments in model and infrastructure players. At the same time, nearly 3 in 4 AI deals (74%) remain early-stage as investors look to get in on the ground floor of the AI opportunity. 
• Industry tech sectors lose ground in AI deals. Vertical tech areas like fintech, digital health, and retail tech are securing a smaller percentage of overall AI deals (declining from a collective 38% in 2019 to 24% in 2024). The data suggests that companies focused on infrastructure and horizontal AI applications are drawing greater investor interest amid generative AI’s rise.
• Outside of the US, Europe fields high-potential AI startup regions. While the US dominated AI funding (76%) and deals (49%) in 2024, countries in Europe show strong potential in AI development based on CB Insights Mosaic startup health scores. Israel leads with the highest median Mosaic score (700) among AI companies raising funding. 
• AI M&A activity maintains momentum. The AI acquisition wave remained strong in 2024, with 384 exits nearly matching 2023’s record of 397. Europe-based startups represented over a third of M&A activity, cementing a 4-year streak of rising acquisitions among the region’s startups. 
• AI startups race to $1B+ valuations despite early market maturity. The 32 new AI unicorns in 2024 represented nearly half of all new unicorns. However, AI unicorns haven’t built as robust of a commercial network as non-AI unicorns, per CB Insights Commercial Maturity scores, indicating their valuations are based more on potential than proven business models at this stage.
• Tech leaders embed themselves deeper in the AI ecosystem. Major tech companies and chipmakers led corporate VC activity in AI during Q4’24, with Google (GV), Nvidia (NVentures), Qualcomm (Qualcomm Ventures), and Microsoft (M12) being the most active investors. This reflects the strategic importance of securing access to promising startups while providing them with essential technical infrastructure.

We dive into the trends below.

For more on key shifts in the AI landscape in 2025, check out this report on the implications of DeepSeek’s rise.

Massive deals drive AI funding boom

Globally, private AI companies raised a record $100.4B in 2024. At the quarterly level, funding soared to a record $43.8B in Q4’24, or over 2.5x the prior quarter’s total. 

The funding increase is largely explained by a wave of massive deals: mega-rounds ($100M+ deals) accounted for 80% of Q4’24 dollars and 69% of AI funding in 2024 overall.

The year featured 13 $1B+ deals, the majority of which went to AI model and infrastructure players. OpenAI, xAI, and Anthropic raised 4 out of the 5 largest rounds in 2024 as they burned through cash to fund the development of frontier models. 

Overall, the concentration of funding in mega-rounds reflects the high costs of AI development across hardware, staffing, and energy needs — and widespread investor enthusiasm around the AI opportunity. 

But that opportunity isn’t limited to the largest players: nearly 3 in 4 AI deals (74%) were early-stage in 2024. The share of early-stage AI deals has trended upward since 2021 (67%) as investors look to ride the next major wave of value creation in tech.

CBI Customers: Track 15,000+ AI companies

Industry tech sectors lose ground in AI deals

Major tech sectors — fintech, digital health, and retail tech — are making up a smaller percentage of AI deals.

While the overall annual AI deal count has stayed steady above 4,000 since 2021, dealmaking in sectors like digital health and fintech has declined to multi-year lows. So, even as AI companies make up a greater share of the deals that do happen in these industries, the gains haven’t been enough to register in the broader AI landscape.

The data suggests that, amid generative AI’s ascendancy, AI companies targeting infrastructure and horizontal applications are drawing a greater share of deals. 

With billions of dollars flowing to the model/infra layer as well, investors appear to be betting that the economic benefits of the latest AI boom will accrue to the builders.  

Outside of the US, Europe fields high-potential AI startup regions

Although US-based companies captured 76% of AI funding in 2024, deal activity was more distributed across the globe. US AI startups accounted for 49% of deals, followed by Asia (23.2%) and Europe (22.9%). 

Comparing median CB Insights Mosaic scores (a measure of private tech company health and growth potential on a 0–1,000 scale) for AI companies that raised equity funding in 2024 highlights promising regional hubs. 

Explore 500+ high-potential AI startups

European countries dominate the top 10 countries by Mosaic score (outside of the US). Israel, which has a strong technical talent pool and established startup culture, leads the pack with a median Mosaic score of 700.

Overall activity on the continent is dominated by early-stage deals, which accounted for 81% of deals to Europe-based startups in 2024, a 7-year high.

The European Union indicated in November that scaling startups is a top priority, pointing to the importance of increased late-stage private investment in remaining competitive on the global stage.

AI M&A activity maintains momentum

The AI M&A wave is in full force, with 2024’s 384 exits nearly reaching the previous year’s record-high 397.

Acquisitions of Europe-based startups accounted for over a third of AI M&A activity in 2024. Among the global regions we track, Europe is the only one that has seen annual AI acquisitions climb for 4 consecutive years. Although the US did see a bigger uptick YoY (16%) in 2024, posting 188 deals. 

In Europe, UK-based AI startups led activity in 2024, with 32 M&A deals, followed by Germany (18), France (16), and Israel (12). 

Major US tech companies, including Nvidia, Advanced Micro Devices, and Salesforce, participated in some of the largest M&A deals of the year as they embedded AI across their offerings.

Search for recently funded AI companies with high M&A probabilities

AI startups race to $1B+ valuations despite early market maturity 

AI now dominates new unicorn creation. The 32 new AI unicorns in 2024 accounted for nearly half of all companies passing the $1B+ valuation threshold during the year. 

These AI startups are hitting unicorn status with much smaller teams and at much faster rates than non-AI startups: 203 vs. 414 employees at the median, and 2 years vs. 9 years at the median. 

CBI Customers: Dive into data on every unicorn

These trends reflect the current AI hype — investors are placing big early bets on AI potential. Many of these unicorns are still proving out sustainable revenue models. We can see this clearly in CB Insights Commercial Maturity scores. More than half of the AI unicorns born in 2024 are at the validating/deploying stages of development, while non-AI new unicorns mostly had to get to at least the scaling stage before earning their unicorn status.

Tech leaders embed themselves deeper in the AI ecosystem

In Q4’24, the top corporate VCs in AI (by number of companies backed) were led by a string of notable names: Google (GV), Nvidia (NVentures), Qualcomm (Qualcomm Ventures), and Microsoft (M12). 

As enterprises rush to harness AI’s potential, big tech, chipmakers, and other enterprise tech players are building their exposure to promising companies along the AI value chain.

Meanwhile, startups are linking up with these players to not only secure funding for capital-intensive AI development but also access critical cloud infrastructure and chips.

MORE AI RESEARCH FROM CB INSIGHTS

• What DeepSeek’s model releases mean for the future of AI
• Here’s how leading strategy teams are successfully driving generative AI adoption in their organizations
• The foundation model divide: Mapping the future of open vs. closed AI development
• 15 tech trends to watch closely in 2025
• Inside the AI drug discovery arms race: Record M&A activity, a biologics funding spree, and more
• The industrial AI agents & copilots market map

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However, some positive signals are emerging, including growing deal sizes and a pickup in M&A, with a focus on cybersecurity capabilities.

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

Key takeaways from the report include:

• Fintech dealmaking continues downward trend in 2024. Annual fintech deals and funding both dropped to 7-year lows in 2024. While deals dropped by 17% YoY to a total of 3,580, funding fell by 20% to $33.7B.
• One positive signal: bigger deals. The median fintech deal size increased to $4M in 2024 — marking a 33% jump YoY — with deal sizes rising across every major global region. Across fintech sectors, the biggest jump occurred in banking, where the median deal size rose by 70% YoY to reach $8.5M. Though fintech saw fewer deals overall in 2024, the increase in deal sizes suggests that investors are writing bigger checks for companies with compelling growth potential.
• M&A activity is also picking up. Fintech M&A exits jumped 24% quarter-over-quarter (QoQ) to 189 in Q4’24, with Stripe’s $1.1B purchase of stablecoin platform Bridge marking the quarter’s largest deal. Overall, fintech saw a total of 664 M&A exits in 2024 (up 6% YoY) as financial services companies sought to diversify their capabilities and build full-service platforms.
• Mature banking companies are catching the eyes of investors. Banking saw mid- and late-stage deals rise to 38% of its total deal volume in 2024 (vs. 21% in 2023), outpacing the 4 percentage point increase in fintech more broadly. Uncertainty about new banking technology and regulatory volatility — particularly among banking-as-a-service players — is likely driving investors to more proven solutions.
• Payments tech ends 2024 as a bright spot. Five of the top 10 equity deals in Q4’24 went to companies building payments solutions, from mobile payments apps to cross-border payments enablement tools to platforms digitizing B2B payments. This concentration of large deals within payments tech reflects the ongoing push to digitize commerce and business exchanges. 

We dive into the trends below.

Fintech dealmaking continues downward trend in 2024

In 2024, annual fintech funding and dealmaking both decreased YoY, hitting 7-year lows.

However, there are signs that the fintech market is steadying. The annual decline in funding was fintech’s smallest in 3 years. Meanwhile, at the quarterly level, funding rebounded to close the year strong, increasing 11% QoQ to reach $8.5B in Q4’24.

One positive signal: bigger deals

While there are fewer fintech deals overall, deal sizes are climbing. 

Following 2 consecutive years of decline, the median deal size in fintech jumped 33% YoY in 2024.

Across fintech sectors, banking saw the biggest jump in median deal size in 2024 — a 70% YoY increase to $8.5M. 

This shift reflects increased investor selectivity in the current market. Companies that pass more rigorous due diligence are attracting larger investments, even as overall deal volume remains constrained.

CBI customers: Track 20K+ fintech companies

M&A activity is also picking up

Fintech M&A deals jumped 24% QoQ in Q4’24. 

US-based companies captured 8 of the largest 10 deals, including the top 5. Stripe’s $1.1B acquisition of Bridge was the largest of the quarter.

The quarterly increase points to broader stirrings of an M&A resurgence: for the year, fintech M&A exits rose by 6% YoY to 664 deals in 2024. 

Acquirers are boosting capabilities across functions. For instance, Stripe’s purchase of stablecoin platform Bridge gives the company a stronger standing in the reinvigorated market for digital assets and boosts its cross-border payment capabilities. The deal also emphasizes stablecoins’ growing role in driving accessibility and stability within crypto’s current wave.

Bolstering cybersecurity was also a focus for acquirers in Q4’24, pointing to financial services companies’ push to integrate fraud detection in their product offerings. For example, in November 2024, IT company N-able bought Adlumin, which deploys its solutions to financial firms, to enhance its cybersecurity capabilities. In October, Socure — specializing in digital identity verification — acquired Effectiv to enhance its AI-driven fraud detection capabilities.

Search recently funded fintech companies with high M&A probabilities

Mature banking companies are catching the eyes of investors

Early-stage deals made up a larger share of fintech investment activity in 2022-23, suggesting that investors shifted their focus toward nascent innovation requiring smaller capital commitments during the market slowdown.

The trend shifted in 2024, particularly in the banking sector. While mid- and late-stage deal share rose by 4 percentage points YoY across fintech broadly, it jumped 17 percentage points in banking. 

See 140+ high-potential mid- and late-stage startups

Recent volatility in banking-as-a-service — such as Synapse’s bankruptcy in April — and intensified regulatory scrutiny are likely driving investors to more proven solutions.

Payments tech ends 2024 as a bright spot

Five of the 10 biggest fintech deals in Q4’24 went to payments companies, capping a relatively strong quarter for the sector. Despite a YoY decline, funding to payments companies rose by 20% QoQ to $1.8B in Q4’24.

Argentina-based mobile payments company Ualá secured a $300M Series E in Q4’24, tying home equity release firm Splitero for the largest round of the quarter.

Of the top payments deals, two went to companies automating accounts payable and other aspects of B2B payments (Melio and ASAAS). The opportunity to digitize B2B payments continues to expand, especially since businesses in many geographies still rely on manual processes.

B2B payments tech market ranking

Related resources from CB Insights:

• State of Venture 2024 Report
• 15 tech trends to watch closely in 2025
• Fintech 100: The most promising fintech startups of 2024
• The generative AI in financial services market map
• Prioritizing B2B payments tech: How 9 tech-driven markets stack up across maturity and momentum

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