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

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

Want to see more research? Join a demo of the CB Insights platform.

If you’re already a customer, log in here.

The post From the battlefield to the factory, Palantir is going on an AI offensive appeared first on CB Insights Research.

It looks like voice AI may have found its sweet spot: ordering fries with that.

Yum! Brands — which owns Taco Bell, KFC, and Pizza Hut and has a larger restaurant footprint than any other company globally — recently announced a partnership with Nvidia to deploy AI (including AI voice ordering) throughout hundreds of restaurants starting in April. 

Similarly, Jersey Mike’s Subs has partnered with SoundHound on a 50-store pilot of AI voice ordering, while Wendy’s now uses Google Cloud LLMs to process orders in English and Spanish.

Voice AI stands to reduce labor costs in high-turnover positions while also increasing order throughput and accuracy. It also means staff can be redeployed to food preparation or customer service roles that drive higher satisfaction.

But fast food is just the tip of the iceberg for voice AI.

Below, we get into:

• Why voice AI matters 
• Market maturity
• Challenges to adoption

Why does voice AI matter?

For customer interactions, voice conversations offer a far more expressive mode of communication than text-based channels. 

Yet the industry remains stuck in a purgatory of robo-call decision trees and endless holds. 62% of customer calls to SMBs go unanswered, while upwards of 70% of business calls that connect still end up putting customers on hold, with most hanging up within minutes. 

Advances in AI speech models could break this cycle. Voice AI models are shifting toward processing audio directly — rather than needing to translate it to text, process it using an LLM, then convert it back into speech — and are getting closer to the cadence of human conversation (<300ms latency).

The progress has fueled a surge in equity funding to voice AI solutions, which grabbed $2.1B in 2024, per CB Insights’ funding data. Momentum has continued in 2025 so far, with companies raising nearly $500M in Q1’25.

ElevenLabs‘ $180M round from investors including a16z, Salesforce Ventures, and Sequoia Capital was a big part of this year’s strong start. ElevenLabs has already hit $100M in ARR — just 3 years after its founding.

On the whole, though, the voice AI market remains in its early stages — and faces growing pains.

The market is still nascent

Most of the voice AI market remains in the earlier stages of commercial maturity, with 85% in levels 1, 2, or 3 on CB Insights’ Commercial Maturity scale. More than half are still developing or validating their products, while 39% are beginning commercial distribution and starting to gain customers.

Most startups here were founded in just the last 3 years, as the chart below demonstrates. 2023 was a breakout year, seeing the number of companies founded grow 2x year-over-year, from 35 to 70.

This growth has been driven by advancements in voice AI models — including OpenAI‘s Realtime API for speech-to-speech applications, launched in late 2024 — which jumpstarted applications across use cases.

One additional signal that voice is hot: companies building voice AI applications are making up larger chunks of Y Combinator’s recent cohorts.

CBI customers can dive into the data on 270 companies developing voice AI capabilities — with a focus on voice generation — here.

Growing pains

Despite the excitement, challenges remain around reliability and trust. 

Voice AI agents still struggle with complex conversations and unpredictable inputs, leading most enterprises to start out by deploying them in low-stakes scenarios.

In theory, fast-food ordering should be a natural fit — interactions are brief and highly predictable. The AI only needs to understand a limited vocabulary of items and modifiers.

But the reputational risk of even the occasional mishap can be high. McDonald’s, for instance, started a voice AI pilot with IBM back in 2021, but pulled it in 2024 after videos of inaccurate orders went viral on TikTok. 

Customer acceptance of voice AI interaction also varies dramatically by region. As one Cognigy customer told us:

Meanwhile, a strategic divide is emerging in the voice AI market: cloud vs. edge processing.

Cloud-based solutions from tech giants offer advanced capabilities but raise privacy concerns, while edge-based platforms process data locally with better privacy but more limited features.

A medtech executive highlighted this tradeoff, telling us they chose Sensory over Microsoft or Amazon despite losing out on more robust capabilities:

This divide will shape which players win in different sectors, with edge solutions likely dominating in sensitive industries like healthcare and financial services, while cloud platforms prevail in consumer and retail applications.

For more on how AI will shape every aspect of the customer experience, get the free report here.

RELATED RESOURCES:

• Data on 270 voice AI companies
• Market report on voice AI development platforms
• State of Venture Q1’25 Report

For information on reprint rights or other inquiries, please contact reprints@cbinsights.com.

The post Voice AI’s sweet spot: ordering fries with that appeared first on CB Insights Research.

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 Salesforce’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

For information on reprint rights or other inquiries, please contact reprints@cbinsights.com.

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

M&A is back.

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

Buyers on the prowl

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

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

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

But tech is leading the charge.

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

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

Nvidia’s M&A playbook

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

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

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

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

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

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

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

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

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

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

Source: CB Insights — Nvidia Q4 FY 2025 earnings transcript

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

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

Related research from CB Insights:

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

For information on reprint rights or other inquiries, please contact reprints@cbinsights.com.

The post Nvidia’s next big bet? Physical AI appeared first on CB Insights Research.

According to CB Insights headcount data, AI firms such as Glean, Scale, and OpenAI have increased their workforce in the country by as much as 67% over the last six months. The country’s domestic AI companies have also seen 32% headcount growth over the same period.

Notably, India is now OpenAI’s second-largest market — with a user base that tripled in the past year — while global tech giants like Microsoft and Nvidia have made substantial infrastructure investments in the country.

Want to see more research? Join a demo of the CB Insights platform.

If you’re already a customer, log in here.

The post Global AI race heats up in India with unprecedented hiring spree appeared first on CB Insights Research.

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

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

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

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

Tech M&A prediction highlights

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

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

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

Source: CB Insights — ServiceNow Acquisition Insights

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

What is Mosaic?

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

What is M&A Probability?

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

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

For information on reprint rights or other inquiries, please contact reprints@cbinsights.com.

The post 7 tech M&A predictions for 2025 appeared first on CB Insights Research.

As AI agents dominate the conversation, customers are growing skeptical about whether they can live up to the hype.

In March, we’ve interviewed 40+ customers of AI agent products and are hearing of 3 primary pain points right now:

1. Reliability
2. Integration headaches
3. Lack of differentiation

1. Reliability

This is the #1 concern raised by organizations adopting AI agents, with nearly half of respondents citing reliability & security as a key issue in a survey we conducted in December. 

According to CBI’s latest buyer interviews, AI agent reliability varies dramatically across providers. Many customers report a gap between marketing and reality.

“Whatever was promised didn’t work as great as said,” one LangChain user told us about the company’s APIs. “We encountered cases where we were getting partially processed information, and the data we were trying to scrape was not exactly clean or was hallucinating.”

For many customers, reliability is largely a function of how complex the data and use cases are. For instance, the LangChain customer saw ~80% accuracy for simpler tasks, but “for complex tasks, the accuracy dropped to around 50%.” 

Organizations are tackling the reliability issue with 1) human oversight; and 2) more extensive model training.

An Ema customer, for instance, first has a subject-matter expert review outputs, and once “more than 90% of the responses that we have tested are now accurate, we let it fly.”

A customer for CrewAI, which orchestrates teams of AI agents into “crews,” takes an even more involved approach:

The customer still needs to intervene with their own ML algorithms when CrewAI is unable to handle outliers or unconventional data structures. If CrewAI is able to tackle these cases in the future, “that would be a huge leap forward.” 

Source: CB Insights — AI agent market map featuring CrewAI and LangChain in the infrastructure category 

2. Integration headaches

Integration limitations rank as another top customer pain point.

For one, lack of interoperability poses long-term challenges, as this Cognigy customer notes:

An Artisan AI customer echoes this: “It was a bit of a gamble that we were signing up for a product where they didn’t have quite all the integrations that we wanted.”

Where customers see real value from these tools is when they can support seamless data flow, especially through their existing tech stack. This buyer went with Decagon because of its integrations:

3. Lack of differentiation

More than half of private capital flowing into the AI agent space has gone to horizontal applications — but these markets, like customer support and coding, are becoming highly saturated.

“There’s so many short-term moats, but in the long term there is no moat,” one customer observed. “Whatever you build will be rapidly reproduced.”

In a crowded market, specialization will determine success.

Hebbia, for instance, has tailored its solution to financial players. An exec at a PE firm framed this as a selling point when getting internal buy-in: “When I bring tools to the deal team that live and breathe diligence and deal execution, ensuring that it’s aligned to what they know and understand and [that it] speaks their language is incredibly important.”

While many horizontal AI agents are actively deploying or even scaling their solutions, vertical AI agents remain nascent, with half still in the first 2 levels of Commercial Maturity. 

They’ll gain more momentum this year as enterprises prioritize solutions that are highly tailored to the needs of individual industries. 

CB Insights customers can read our latest interviews with AI agents’ customers here.

The post We spoke to 40+ customers of AI agents — here’s where the tech is falling short appeared first on CB Insights Research.

Small teams are getting big payouts.

That’s what the M&A data for 2025 says.

Using CB Insights M&A transaction and headcount data for Q1’25 so far, we found that tech companies acquired for $100M or more had just 100 employees at the median.

Our analysts dove into the tech M&A landscape in a live briefing on March 18 — download the recording here.

We zoomed in on the companies exiting with teams of 100 employees or under, and they’re typically:

• young (7 years old on average)
• bootstrapped (a majority have raised under $20M in equity funding)

See the top 10 by valuation-to-employee ratio below.

CBI customers can explore these 10 startups here.

The top exit by that metric went to Voyage AI, which offers embedding models and ranking tools to improve AI search and retrieval.

With just 19 employees and a price tag of $220M — up 2x since its funding round last September — Voyage AI’s sale to MongoDB equated to $11.6M per employee.

Bon voyage

For MongoDB, Voyage AI represents an opportunity to own more of the AI development process and build customer trust, specifically around output reliability.

Source: CB Insights — MongoDB Q4 FY 2025 earnings call

This is one of the main hurdles to broader AI adoption.

In a December 2024 survey we conducted on AI agents — the clear next evolution for enterprise genAI deployment — nearly half (47%) of respondents cited reliability & security as a top obstacle.

To address this concern, platforms that help businesses organize, maintain, and leverage their data effectively will become even more important.

Acquisition radar

MongoDB isn’t the only one acquiring AI startups to stitch together more unified AI development tools.

Data management giants Databricks and Snowflake have been on AI acquisition sprees, acquiring 5 AI startups a piece since 2023 — more than any other acquirers globally.

The question is: Who’s next?

We expect the next wave of AI M&A targets to be those building out AI agent infrastructure.

Drilling down further, there are 47 startups with teams of 100 employees or less.

The most likely M&A targets, ranked using CB Insights’ Exit Probability, are:

• Letta (agent memory)
• Coval (agent evaluation & observability)
• Fixie (voice AI)

Source: CB Insights — Platform search of AI agent infrastructure startups

Another top contender is Unstructured, in the data curation space — the company has received previous backing from the venture arms of both MongoDB and Databricks.

Customers can unlock the full list of AI agent infra targets here.

RELATED RESEARCH FROM CB INSIGHTS:

• Tech M&A Predictions for 2025
• Databricks wants to be a one-stop shop for AI. Here’s how it plans to get there
• Our 6 predictions for the insurance space in 2025
• State of Venture 2024 Report

For information on reprint rights or other inquiries, please contact reprints@cbinsights.com.

The post Small teams, big exits: $100M+ tech acquisitions in 2025 are going to lean startups appeared first on CB Insights Research.

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

For information on reprint rights or other inquiries, please contact reprints@cbinsights.com.

The post The AI agent market map appeared first on CB Insights Research.

These LLM-based systems mark an evolution beyond copilots: AI agents can accomplish complex tasks on a user’s behalf with minimal intervention, from sales prospecting to compliance decisioning. 

In the rapidly growing landscape for agent infrastructure and applications, over half of companies in the market have been founded since 2023. Meanwhile, funding to startups in the space nearly 3x’d in 2024.

Want to see more research? Join a demo of the CB Insights platform.

If you’re already a customer, log in here.

The post What’s next for AI agents? 4 trends to watch in 2025 appeared first on CB Insights Research.

The 2024 Change Healthcare cyberattack demonstrates the far-reaching consequences of cybercrime in healthcare. This attack compromised the protected health information of at least 100M people and cost parent company UnitedHealth around $3B.

Want to see more research? Join a demo of the CB Insights platform.

If you’re already a customer, log in here.

The post The cybersecurity in healthcare market map appeared first on CB Insights Research.

Imagine: your personal AI agent notifies you that a hair dryer you’ve been eyeing is now on sale. The product page highlights benefits tailored to your curly hair, while the agent confirms it will arrive before your upcoming trip.

With your approval, the agent handles the purchase through your secure wallet. Later, it proactively suggests complementary hair care products for the summer season.

This world of autonomous commerce isn’t as far off as it seems. Tech and e-commerce leaders — including OpenAI, Nvidia, Amazon, Walmart, Google, and Apple — are already building AI systems that are steps away from conducting transactions. 

AI agents will impact each stage of the customer journey, streamlining the path to purchase and fundamentally transforming how businesses build relationships with consumers and drive loyalty.

We use CB Insights data on early-stage fundraising, public companies, and industry partnerships to analyze how generative AI — especially AI agents — is transforming the customer journey.

In the 11-page report, we cover 3 predictions that emerged from our analysis: 

1. First-party transaction data will shape the future of AI-driven personalization. As personalization becomes more sophisticated at the awareness and consideration stages, companies with direct access to first-party data will have an edge.
2. Direct-to-agent (D2A) commerce will kill traditional loyalty. With AI agents handling browsing and shopping, traditional loyalty programs will lose effectiveness as agents optimize shopping across a select group of merchants.
3. A few AI agents will own the customer relationship. Companies like Amazon, Google, and Apple — with critical distribution and financial services infrastructure — are well-positioned in commerce.

RELATED RESEARCH FROM CB INSIGHTS

• How generative AI could supercharge retailers’ ad networks
• AI is revitalizing the “virtual try-on” space — this is what’s coming next, including interactive Google ads
• The enterprise AI agents & copilots market map
• 15 tech trends to watch closely in 2025
• Generative AI — e-commerce search
• AI-optimized e-commerce UX
• Generative AI — customer support operations

For information on reprint rights or other inquiries, please contact reprints@cbinsights.com.

The post The future of the customer journey: AI agents take control of the buying process appeared first on CB Insights Research.

Rather than full automation, the industry is embracing a more nuanced approach where technology augments human capabilities, creating hybrid workplaces where workers are upskilled to work alongside and manage robotic systems. 

Today’s modular and scalable automation solutions enable incremental modernization, allowing logistics providers to start small, prove ROI, and gradually expand their automated operations while maintaining market adaptability. 

Want to see more research? Join a demo of the CB Insights platform.

If you’re already a customer, log in here.

The post The automated warehouse market map appeared first on CB Insights Research.

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

For information on reprint rights or other inquiries, please contact reprints@cbinsights.com.

The post The wildfire tech market map appeared first on CB Insights Research.

Open-source AI is drawing unprecedented attention from developers and enterprises, driven in part by DeepSeek’s recent model releases.

Cost pressures and demands to improve the performance of generative AI applications are driving enterprise interest in the ecosystem as organizations seek more flexible and cost-effective alternatives to proprietary solutions. 

Want to see more research? Join a demo of the CB Insights platform.

If you’re already a customer, log in here.

The post Should enterprises adopt closed-source or open-source AI models? appeared first on CB Insights Research.

January was a busy month for the generative AI space, headlined by DeepSeek‘s R1 model launch — matching OpenAI’s o1 model capabilities at just 5-10% of the cost, while open-sourcing the technology.

Want to see more research? Join a demo of the CB Insights platform.

If you’re already a customer, log in here.

The post This month in genAI: DeepSeek launches R1, OpenAI releases Operator agent, and Nvidia goes on partnership spree appeared first on CB Insights Research.

A key factor in the slowdown was a sharp drop in funding from mega-rounds ($100M+ deals), which dropped 47% year-over-year (YoY) in 2024. This coincided with high-profile bankruptcies of established climate tech startups like battery manufacturer Northvolt.

However, this turbulence wasn’t limited to the private markets — public players like Lilium and Arrival also filed for insolvency/bankruptcy over the period, highlighting the commercialization challenges facing capital-intensive industries like climate tech.

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

Key takeaways from the report include:

• Climate tech investment activity continues to contract. Global climate tech funding fell for the second year straight in 2024, dropping by 40% YoY, with mega-round funding falling by 47%. However, the space still saw notable mega-rounds. This included deals to players modernizing the power grid, drawing participation from tech giants racing to secure clean energy for computing infrastructure.
• Grid tech and nuclear are gaining momentum to meet AI’s energy needs. Within climate tech, markets targeting the grid and power generation show the strongest growth potential, according to CB Insights Mosaic startup health scores. This momentum is driven in part by the massive energy demands (and expected continued demand) of AI data centers.
• Electric vehicle technology sees record pullback in deals. After years of steady growth, electric vehicle (EV) tech deal activity plunged 61% YoY in 2024 — its steepest decline on record. This points to broader challenges in the sector, like lower consumer demand for EVs and increased capital costs for scaling manufacturing operations.
• Climate tech M&A exits decline once again. Climate tech M&A exits dropped by 25% YoY to hit 284, the lowest count since 2020. At the quarterly level, M&A exits steadily declined over the course of 2024, falling from 104 in Q1’24 to 39 in Q4’24. Growing skepticism around environmental, social, and governance (ESG) initiatives could be a contributing factor.

We dive into the trends below.

Climate tech investment activity continues to contract

Global climate tech funding dropped for a second consecutive year in 2024. It fell by 40% YoY, with mega-round funding falling by 47% over the same period.

The funding slowdown played out differently across the globe. US climate tech showed resilience YoY with relatively steady funding despite fewer deals. Meanwhile, other countries saw steep declines in climate tech dollars, with China experiencing the sharpest drop (-66% YoY).

Amid the overall funding decline, climate tech still saw several notable mega-rounds. This included deals in Q4’24 for companies modernizing the power grid:

• Crusoe secured $600M at a $2.8B valuation to support its efforts to use waste natural gas to power large-scale data centers
• X-energy received $500M as it works to build small modular reactors (SMRs) capable of generating more than 5 gigawatts of electricity by 2039
• Form Energy secured $405M to accelerate production of its iron-air batteries capable of 100-hour energy storage

Notably, some of these deals drew participation from big tech companies racing to secure clean energy for computing infrastructure. For example, Amazon (via the Climate Pledge Fund) invested in X-energy’s nuclear development, and Nvidia invested in Crusoe’s sustainable computing infrastructure, reflecting big tech’s interest in solutions that can help meet rising AI data center demands.

Grid tech and nuclear are gaining momentum to meet AI’s energy needs

Comparing median CB Insights Mosaic scores (a measure of private tech company health and growth potential on a 0–1,000 scale) for climate tech companies that raised equity funding in 2024 reveals the most promising markets in climate tech.

Grid tech and nuclear markets — covering technologies directly integrated into and operated by utilities to enhance power system reliability, flexibility, and clean energy integration — dominate the top 10 climate tech markets by median Mosaic score, highlighting their growth potential.

Surging energy demand from AI data centers is in part responsible for these markets’ momentum. For example, nuclear fusion and small modular reactors could provide continuous clean power generation, grid storage enables reliable renewable energy delivery, and virtual power plants help optimize massive power loads.

See 100+ high-potential climate tech companies

Electric vehicle technology sees record pullback in deals

Electric vehicle tech deals experienced their steepest decline on record in 2024, with deal count plunging 61% YoY to 243.

High-profile bankruptcies underscored the sector’s capital-intensive manufacturing challenges in 2024. Battery manufacturer Northvolt filed for bankruptcy a year after raising $1.2B, as it struggled to scale production efficiently. Electric van maker Arrival — which went public in 2021 at a $13B valuation — also filed for bankruptcy last year amid mounting production costs and the inability to raise funding.

Even the auto industry’s most prominent EV champions scaled back their electric ambitions throughout the year:

• GM delayed its Orion Assembly EV truck plant by 6 months and cut 2024 EV targets by 17%
• Toyota postponed US EV production to 2026
• Ford canceled plans to produce an all-electric three-row SUV, pivoting to a hybrid approach instead
• Volvo dropped its 2030 all-electric goal

Climate tech M&A exits decline once again

In 2024, climate tech M&A exits fell by 25% YoY to hit 284 — the lowest count since 2020.

At the quarterly level, M&A exits steadily declined over the course of 2024, falling from 104 in Q1’24 to 39 in Q4’24.

The decline in M&A activity coincided with key changes in market conditions, including the rise of economic headwinds, political uncertainty, and growing skepticism around environmental, social, and governance (ESG) initiatives.

For example, ESG tech markets collectively saw equity funding decline 54% YoY in 2024. On the corporate side, mentions of ESG in earnings calls have trended down since peaking in Q1’22.

As skepticism toward ESG initiatives grows, some companies appear to be placing lower priority on climate tech acquisitions that were previously considered strategic imperatives.

See recently funded climate tech companies with high M&A probabilities

MORE CLIMATE TECH RESEARCH FROM CB INSIGHTS

• Data centers are reshaping nuclear development, driving billions in new power infrastructure investment
• Why fleet management leaders are racing to acquire next-gen telematics capabilities — and which M&A targets could be next
• The AI data center value chain: 12 high-momentum technologies powering the future of AI
• The top 25 utility companies by AI readiness
• Big Tech in Energy: How Amazon, Google, Microsoft, & Nvidia are advancing the global energy transition
• Sodium-ion batteries are poised for a breakout moment — energy players should prepare

For information on reprint rights or other inquiries, please contact reprints@cbinsights.com.

The post State of Climate Tech 2024 Report appeared first on CB Insights Research.

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

The post State of CVC 2024 Report appeared first on CB Insights Research.

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

For information on reprint rights or other inquiries, please contact reprints@cbinsights.com.

The post State of AI Report: 6 trends shaping the landscape in 2025 appeared first on CB Insights Research.