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

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

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Military technology is entering its AI era.

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

Public-company execs also have defense on the brain. 

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

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

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

Below, we look at:

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

1. Recent partnerships and the year’s biggest deals

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

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

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

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

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

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

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

2. Anduril’s UUV announcement

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

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

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

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

CBI customers can unlock the full map here.

3. Top investors in AI defense tech in 2025

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

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

Related CB Insights research:

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

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

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Prior to heading up OpenAI, he was president of Y Combinator, one of the most successful startup accelerators in the world, from 2014 to 2019.  

Behind the scenes, Altman is a remarkably active angel investor — with over 100 investments since 2010, including rounds to Stripe, Reddit, and Instacart. 

In addition to his individual investments, he is the founder of VC firm Hydrazine Capital and investment fund Apollo Projects, launched with his brothers Max and Jack Altman. Altman Capital, which is managed by Jack, also counts Sam as a limited partner. 

His investments highlight wide-ranging interests, including lab-grown meat, longevity, energy, education — and, of course, artificial intelligence.

We mapped out Sam Altman’s universe of portfolio companies by category since 2019. We also note where companies have publicly disclosed a relationship with OpenAI.  

Below the graphic, we break down the most notable areas of activity. 

Sam Altman’s investments overlap with OpenAI’s strategy

Several of the companies Altman has backed also have relationships with OpenAI. For instance, Altman has backed 3 rounds to Humane, which recently released its “Ai Pin” — a wearable device whose core feature is a personal assistant powered by ChatGPT.

Two of Altman’s other investments — B2B payments automation platform Slope (Series B) and coding assistant Warp (Series B) — have both disclosed that OpenAI’s models are in part powering their products.

Meanwhile, OpenAI signed a letter of intent to spend $51M on AI chips from Rain in 2019. Altman had previously invested in the company’s seed round.

AI-powered language learning app Speak, whose Series A Altman backed in 2022, has since raised successive rounds from OpenAI’s Startup Fund and other investors. 

While OpenAI is not an investor in the OpenAI Startup Fund (the fund’s backers include Microsoft and other OpenAI partners), Speak said its Series B raise “unlocks a deeper relationship where OpenAI’s systems will power more of Speak’s user experience, and Speak will gain advanced access to new systems in development.”

With $40B of fresh capital, OpenAI will likely become increasingly acquisitive, focusing on two key areas, infrastructure (building the base for continued growth at the foundational level) and applications (focusing on revenue-generation as the company transitions to for profit).

Three new investments from the last twelve months stand out:
1) AirOps (Jun ’24 via Alt Capital): A platform that allows users to create, test, deploy, and scale AI applications.
2) CrewAI (Oct ’24 via Alt Capital): A platform for building, deploying, and managing AI agents.
3) Exowatt (Apr ’24): Renewable energy company that provides modular solutions for energy generation and storage.

Two biggest bets Outside of AI are in energy & longevity 

In November 2021, Sam Altman contributed $375M to nuclear fusion startup Helion’s $500M Series E raise — his largest personal investment to date. 

Altman wrote on his blog at the time of the investment: “Helion is by far the most promising approach to fusion I’ve seen.” In May 2023, OpenAI-backer Microsoft signed an agreement to buy electricity from Helion later this decade. 

Altman’s other major bet is anti-aging startup Retro Biosciences. He’s invested a total of $180M in the company, which aims to extend life spans via cellular reprogramming.

Notable exits

Altman has invested in numerous edtech startups over the years. One of them — Codecademy, which he backed in 2011 — was acquired for $525M by SkillSoft in December 2021. 

Other early investments that went on to exit include Instacart (the company IPO’d in September 2023) and Cruise (acquired by General Motors in 2016). 

In addition, Altman is behind 3 SPACs:

• AltC Acquisition Corp., where he is executive officer, is planning a merger with nuclear fission startup Oklo (where he is chairman of the board).
• He is on the board of directors for Bridgetown Holdings, which merged with fintech MoneyHero in October 2023, and Bridgetown 2 Holdings, which merged with proptech company PropertyGuru in 2022.

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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.

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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 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.

After divesting its logistics business in 2023, the company refocused on its core strength: powering commerce infrastructure. Since then, Shopify has accelerated its growth through targeted partnerships, acquisitions, and product development — growing its share of the US e-commerce market from 10% to 12% and boosting revenue by 26% in FY2024. 

Now, Shopify is primed to take on new challenges. From enabling immersive shopping experiences to onboarding enterprise clients and monetizing its data through advertising, the company is laying the foundation for a more ambitious role in global commerce.

Drawing on CB Insights data across investments, acquisitions, integrations, and earnings transcripts, we identify 3 key areas that reveal where Shopify is heading next:

• Powering immersive and unified shopping experiences: Shopify’s relationships with gaming, payments, and agentic commerce players will enable always-on, cross-platform shopping — with Shopify infrastructure at the ecosystem’s core.   
• Becoming the go-to enterprise commerce platform: Through system integrator partnerships, composable solutions like Commerce Components, and unbundled tools like Shop Pay, Shopify is positioning itself as a modular alternative to Salesforce and Adobe.
• Turning customer data into new ad revenue streams: With proprietary tools like Shopify Audiences and new integrations with CDPs and campaign platforms, Shopify is laying the groundwork for a retail media network — creating new ways to monetize merchant and shopper data at scale.

In the graphic below, we show where Shopify has already built momentum across its three strategic pillars — and where we think it’s heading next, including our predictions on future partners and acquisitions.

These priorities signal how the e-commerce giant could reshape buying experiences and challenge established players across advertising, enterprise software, and commerce infrastructure.

We dive into each prediction below. 

1. Powering immersive and unified shopping experiences.

Shopify’s growing US e-commerce share reflects a deliberate strategy to embed commerce capabilities into more contexts. Its integrations with platforms like Roblox and Perplexity AI suggest a vision of always-on, channel-agnostic shopping where Shopify is the core infrastructure across both traditional and emerging environments.

Enabling shopping at any time, on any platform

In late 2024, Shopify took a step into the world of agentic commerce by integrating with Perplexity’s new AI shopper, Buy with Pro. This has enabled consumers to browse and transact directly via Shop Pay within Perplexity’s interface. 

Around the same time, it became Roblox’s first commerce integration partner, giving Shopify merchants access to 80M+ daily users through in-game storefronts powered by Shopify Checkout.

Source: CB Insights — Shopify Q3’24 earnings call

To that end, Shopify is expanding the functionality of its own products. For example, in 2024, it introduced “tap to pay” for its Point of Sale (POS) app and introduced offline payment capabilities, reinforcing its commitment to connecting online and physical experiences. Its integration with loyalty platform Gatsby enables merchants to engage customers across both environments.

Meanwhile, its partnership with India-based Cashfree Payments — enabling local on-site card processing — is part of a broader effort to tap into local economies through regional POS providers.

Using CB Insights’ Mosaic score, which measures business momentum, we sorted early- and mid-stage POS companies in a few key markets (EU and APAC) where Shopify could expand. Focusing on companies that serve retailers, we surfaced these 3 potential partners:

• Flatpay (Mosaic: 783) is a Danish company offering simplified payment processing solutions for small and medium-sized businesses. 
• Teya (Mosaic: 758), based in London, provides payment processing and financial services for small and medium-sized businesses across Europe. 
• Dtcpay (Mosaic: 735) is a Singapore-based digital payment platform. Its solution includes multi-currency swaps to convert fiat and stablecoins. 

Get the full list of potential partners in the EU and APAC

2. Becoming the go-to enterprise commerce platform.

Shopify has built the foundation to move beyond its traditional small-business customer base and compete directly with enterprise commerce platforms like Salesforce Commerce Cloud and Adobe Commerce. The company is positioning itself as a modular, flexible infrastructure layer — designed to meet the needs of large, complex merchants.

Partnerships with migration solutions clear a big hurdle

One of the biggest barriers for enterprise merchants is the complexity of migrating from legacy platforms. To address this, Shopify has steadily expanded its network of system integrators (SIs) since 2022, forming partnerships with Deloitte, EY, and KPMG to streamline onboarding and implementation.

Source: CB Insights — Shopify Q3’23 earnings call

In April 2024, Shopify deepened this strategy with a joint partnership alongside Google Cloud and Cognizant to offer end-to-end digital commerce solutions. These alliances signal Shopify’s increasing traction among enterprise IT buyers — and the company’s evolving go-to-market motion.

Shopify has also added specialized migration and enablement partners to its app store. In August 2024, it onboarded Pivotree, a digital commerce design firm, and in January 2025, expanded its relationship with Anatta to support enterprise migration needs.

Streamlining checkout and payments for large merchants

Simplifying payment workflows remains a core part of Shopify’s enterprise pitch. Its a la carte checkout solution, Shop Pay, is now offered independently and has been adopted by large brands like Coach. Shopify has layered on key partnerships to support broader payment functionality:

• In June 2023, it partnered with Adyen to enable more efficient processing for global enterprise merchants.
  
• In September 2024, it expanded its integration with PayPal, making it a card processor for Shopify and streamlining order management, reporting, and chargebacks.

Shopify has also supported crypto payments via its app store. In 2024, Solana Pay — powered by Helio (now owned by MoonPay) — added support for more tokens, loyalty programs, and stablecoin conversion, expanding Shopify’s optionality for cutting-edge payment rails.

The company is also offering other point solutions to serve enterprise merchants’ needs. In October 2024, it partnered with AI search company Coveo to offer tools for AI-driven product discovery, personalized recommendations, and more, focusing on more prominent retailers.

Learn more about companies using generative AI in e-commerce

Its integrations with tax technology leaders Vertex and Avalara further support its enterprise expansion, enabling complex compliance for cross-border transactions.

Source: CB Insights — Shopify business relationship insights

The tax compliance software market offers Shopify more potential tax compliance partners as it expands its reach with enterprise customers. Using the market’s ESP, which identifies and ranks leading private companies in a given technology landscape, we can highlight challenger companies on the rise that could be valuable relationships for Shopify:

• Sovos provides global tax compliance and regulatory reporting software solutions. 
• Exactera offers AI-powered tax compliance solutions for transfer pricing, income tax provision, and R&D tax credits.
• Neo.Tax also builds AI-powered tax automation software for startups and small businesses.

These moves underscore Shopify’s shift toward a composable, enterprise-grade stack — built to compete with legacy vendors by offering faster implementation, flexible tooling, and global readiness.

3. Shopify will use its reach and first-party data to power advertising for its merchants.

Shopify has long equipped its merchants with tools for personalization and customer acquisition. But its recent product upgrades and tech partnerships point to a broader ambition: turning its vast merchant network and rich first-party data into a full-fledged advertising business.

The activity hints at Shopify building its own version of a retail media network—one that could allow the company to sell ad space to merchants and outside brands, putting it in competition with advertising leaders like Amazon, Google, and Walmart.

To start, Shopify has expanded access to 2 of its own ad-focused products:

• The newest iteration (v2.4) of its customer acquisition tool, Shopify Audiences, launched in June 2024, helps merchants target narrower customer groups and maximize ad performance across networks and platforms. Some merchants have seen CAC reductions of up to 50%. 
• In December 2024, the company made its advertising tool, Shop Campaigns, available to all merchants in the US and Canada. Previously, only higher-tier Shopify Plus merchants could use the product. 

But Shopify’s leadership sees potential in advertising for Shopify beyond its proprietary products:

Source: CB Insights — Shopify Q1’24 earnings call

To unify and activate customer data, Shopify has partnered with third-party platforms that aggregate behavioral and transactional insights:

• In October 2024, Blueshift made its solution available on the Shopify app store. Its tools include a customer data platform, automated decision-making for recommendations, and a cross-channel marketing platform.
• Also in October 2024, Trellis announced an integration with Shopify. The relationship integrates shopper data into Amazon Marketing Cloud, connecting shopper insights across platforms to more effectively target messaging. 

Looking ahead, Shopify may deepen its capabilities in data orchestration by offering its own customer data platform (CDP) or data clean room solution. We ranked the companies in the CDP market by their M&A probability and Mosaic score (600+) to isolate potential M&A targets for Shopify:

• Optimove leverages AI to orchestrate personalized multichannel campaigns for B2C companies.
• Simon specializes in personalization and customer journey orchestration for retail, travel, and subscription businesses. 
• Hightouch is a composable customer data platform specializing in data activation and reverse ETL services.

Shopify is also building new demand channels for merchants. In 2024, it partnered with Mirakl to enable third-party marketplace creation and with Target to feature Shopify merchant products on the retailer’s digital shelves.

These moves suggest Shopify is building more than merchant tools — it’s assembling a vertically integrated commerce and media stack that could challenge the dominance of legacy ad platforms and redefine how brands connect with shoppers.

Research: How generative AI could supercharge retailers’ ad networks

RELATED RESEARCH FROM CB INSIGHTS:

• The future of the customer journey: AI agents take control of the buying process
• How generative AI could supercharge retailers’ ad networks
• 7 tech M&A predictions for 2025
• Interviews with Shopify customers

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M&A is back.

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

Buyers on the prowl

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

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

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

But tech is leading the charge.

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

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

Nvidia’s M&A playbook

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

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

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

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

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

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

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

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

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

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

Source: CB Insights — Nvidia Q4 FY 2025 earnings transcript

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

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

Related research from CB Insights:

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

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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.

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

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

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

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

Tech M&A prediction highlights

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

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

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

Source: CB Insights — ServiceNow Acquisition Insights

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

What is Mosaic?

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

What is M&A Probability?

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

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

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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.

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Clinical development represents one of pharma’s costliest and riskiest investments.

Trials average $55M each, per a study in JAMA Health Forum, and can take more than a decade to complete. However, over 90% of drugs still fail. AI is emerging as a game-changing force in clinical development, tackling its biggest pain points head-on.

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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

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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:

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

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Estimates indicate that US hospitals lose $262B annually to revenue cycle inefficiencies, while drugmakers spend more than $1B on average to develop a single drug. Meanwhile, the healthcare workforce in the US faces high burnout and a projected shortage of 124,000 physicians by 2034, according to the Association of American Medical Colleges.

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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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AI chatbots saw a record 427M app downloads last quarter — up 42% vs. Q3.

Now Meta wants in on the action. 

The tech giant reportedly plans to spin Meta AI into a standalone app to compete with ChatGPT, Google’s Gemini, Perplexity, and other chatbot apps.

ChatGPT is still king with nearly a quarter of AI chatbot app downloads in 2024 and 400M weekly active users across platforms (not just mobile).

But Meta has a massive in-built user base, including ~700M people who already interact with Meta AI features each month across apps like Facebook and Instagram.

The battle for attention is on.

Source: X

One of the differentiators for social AI applications will be emotional intelligence — an area where OpenAI’s latest model, GPT-4.5, shows promise. 

While many headlines have focused on the model’s eye-watering costs, one notable advance is its reported ability to interact with greater empathy (an area where Anthropic’s Claude has so far been superior).

This matters because the more natural AI sounds, the easier it will be for consumers to see it fitting into their lives.

It also makes AI even more formidable in both personal and business settings if the AI can be both higher IQ and EQ than most of us pesky ol’ humans.

Businesses are catching on: More public cos are citing AI as a “friend” or “companion” on earnings calls in an effort to make B2C services more personal.

Mercedes-Benz, for instance, envisions drivers chatting with its MBUX voice assistant (which is built on ChatGPT) like a friend.

Source: CB Insights — Mercedes-Benz Q4’24 earnings call

Beyond emotional connection, AI developers are also making their chatbots more useful through agentic capabilities. This dual focus on both feeling and function will shape the competitive landscape moving forward.

While still constrained by reliability and access issues, web-browsing agents like OpenAI’s Operator signal a future where humans interact regularly with AI agents that take actions on their behalf.

Already nearly every tech giant, plus leading LLM developers like OpenAI and Anthropic, have developed AI agents or are building out tools for others to develop them.

In a head-to-head matchup, OpenAI and Meta would bring distinct sets of advantages.

OpenAI has already built user habits with ChatGPT and is now layering agent capabilities on top. Meta must convince users its AI offering brings something meaningfully different.

But Meta’s experience in the social realm, combined with its existing algorithms, could give it an edge in creating AI that feels like it belongs in human conversations.

Watch for both companies to rapidly iterate on their consumer agent offerings in the coming months.

Related AI research from CB Insights:

• What’s next for AI agents? 4 trends to watch in 2025
• The future of the customer journey: AI agents take control of the buying process
• The foundation model divide: Mapping the future of open vs. closed AI development
• State of AI Report: 6 trends shaping the landscape in 2025

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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.

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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

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But AI and blockchain solutions are driving innovation to create new revenue streams and stoke the existing ones. Early-stage deals in those spaces helped drive a rally in funding and dealmaking in gaming in 2024. Annual funding nearly tripled to $3.2B across 317 deals, with early-stage companies securing 77% of investments — up from 70% in 2023. 

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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. 

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