Some of the artificial intelligence industry’s fastest-growing startups are rapidly transforming into serial acquirers, utilizing mergers and acquisitions to fill product gaps, break into new markets, and bring specialized engineering and research teams directly in-house. A comprehensive review of recent Crunchbase data highlights this shifting strategic landscape, revealing that while AI giant OpenAI remains by far the busiest buyer in the ecosystem, other well-funded startups specializing in legal technology, customer service, and software development have also executed multiple acquisitions over the course of the year.
This aggressive buying spree has pushed the total number of acquisitions of AI startups by other venture-backed AI companies to 195 through September 29, according to Crunchbase data. This figure represents a notable 14% increase over the total volume recorded across the entire previous year. Yet, interestingly, the overall number of distinct buyers grew by just 2% during the same timeframe, indicating that an increasingly active core of repeat buyers is driving the vast majority of the transactional momentum in the market.
These corporate deals point toward a distinct new phase of competition within the broader artificial intelligence sector. Well-funded startups are increasingly turning to mergers and acquisitions as a shortcut to broaden their product suites and reach new customer segments much faster than they realistically could by building everything entirely from scratch. Within specialized verticals like legal technology, for instance, strategic acquisitions are actively bringing advanced research capabilities, regulatory monitoring tools, and complex litigation software directly into broader, more unified platforms.
David Eckstein, the Chief Financial Officer of Stockholm-based legal-tech startup Legora, articulated this calculated approach in a public social media post earlier this year while discussing his company’s back-to-back purchases of multiple smaller firms. Explaining the underlying corporate strategy, Eckstein noted that mergers and acquisitions are explicitly factored into how the company accelerates its ongoing product development. The central question the organization always asks before moving forward with a deal is whether the transaction will get them to their destination faster than they could possibly get there on their own.
Repeat buyers step up dealmaking
The data compiled by Crunchbase indicates that a significant portion of these AI acquirers have returned to the dealmaking table repeatedly over recent years. Across a broader three-year observation period, 67 distinct repeat buyers accounted for approximately 42% of all tracked transactions. OpenAI stood out as by far the most prolific buyer, executing a total of 20 AI-related acquisitions, including an impressive 10 deals completed within this year alone.
Other notable repeat buyers emerging this year include Anthropic and legal AI startup Legora, each of which has announced five distinct acquisitions. They are closely followed by fellow legal AI startup Harvey, which has recorded four acquisitions. In the customer-service and software development spaces, AI provider Sierra and coding company Cursor have each completed three acquisitions this year, while Cohere has announced two. Many of these active corporate buyers operate as vertical AI startups focused on acquiring complementary companies operating directly within their respective niches.
Several of the transactions closed this year carry substantial financial weight. Nscale’s reported $1.65 billion acquisition of Anyscale stands out as the largest transaction with a publicly recorded price tag, followed closely by Cyera’s $1 billion acquisition of identity security startup Oasis Security.
Further down the list of major transactions, Anthropic’s acquisition of Coefficient Bio—a developer specializing in artificial intelligence for pharmaceutical research—was valued at $400 million. Meanwhile, OpenAI’s $300 million acquisition of Glass Imaging, a Los Altos, California-based startup utilizing customized AI in camera hardware for computational photography, alongside Sword Health’s acquisition of Kaia Health for up to $285 million, rounded out the five largest recorded deals in the dataset through the end of September.
Despite these headline-grabbing figures, overall financial terms were publicly disclosed for only 12 of the 195 total transactions. This lack of widespread transparency makes it challenging to gauge the exact aggregate capital that AI startups are deploying toward acquisitions as a whole, though the sheer volume of deals underscores a broader shift in industry tactics.
Industry observers note that this wave of dealmaking has escalated sharply as more artificial intelligence companies embrace acquisitions as a permanent, recurring component of their corporate growth strategies. Rama Sekhar, a partner at Menlo Ventures—a prominent venture capital firm that has backed numerous artificial intelligence startups, including Anthropic and Legora—emphasized that speed is the ultimate currency in the modern AI landscape.
According to Sekhar, acquiring an existing team or product is almost always faster than building the capability organically. He points out that if a startup is not experiencing tenfold growth, it struggles to capture the attention of growth-stage investors, which ultimately creates a funding gap for smaller AI startups seeking a stable home. Furthermore, the exceptionally high valuations commanded by leading AI companies have provided them with a potent form of financial currency, allowing them to use their own stock to finalize acquisitions while minimizing equity dilution.
What AI startups are buying and why
A closer examination of the specific companies being targeted and acquired offers clear insight into what modern AI startups hope to achieve through their intensified merger and acquisition activities.
OpenAI’s purchases have spanned a remarkably wide spectrum, ranging from healthcare data systems and scientific-writing software to developer infrastructure, security tools, and specialized talent acquisition. The San Francisco-based organization signaled its intent early by announcing three separate acquisitions in January alone, setting an aggressive tone for its corporate development strategy throughout the year.
The company’s acquisition pipeline continued at a swift pace through the spring and summer months. In February, OpenAI participated in an acqui-hire transaction involving the open-source AI agent project OpenClaw and its creator, Peter Steinberger. Shortly thereafter in March, OpenAI announced its intention to acquire Astral, a developer of popular open-source tooling for software engineers, alongside the pickup of Promptfoo, an open-source utility designed specifically for testing artificial intelligence applications.
As the year progressed into June, OpenAI agreed to acquire Ona—formerly known as Gitpod—which provides secure cloud environments designed to allow both human developers and increasingly autonomous AI agents to continue working seamlessly after a user’s laptop is closed. Later in August, the company also absorbed Instant, an AI-powered presentation platform capable of automatically converting prompts, raw notes, and complex documents into fully editable presentation decks.
Vertical AI roll-ups
Well-funded vertical AI startups, particularly those operating within the legal technology sector, have mirrored this aggressive M&A behavior by snapping up smaller competitors to round out their core offerings, according to Crunchbase data.
San Francisco-based Harvey has strategically focused its AI-related purchases on filling critical functional gaps surrounding its central enterprise platform. Earlier acquisitions included Hexus, which developed specialized tools for creating product demos, video content, and user guides, as well as Lume, a company that built software designed to help businesses easily connect complex customer data and enterprise applications with modern artificial intelligence systems.
Another key addition was New York-based Benchmark, which created software enabling asset managers to capture actionable insights from past investments and seamlessly apply them to new financial deals. This particular acquisition significantly expanded Harvey’s footprint within the lucrative asset management sector. Continuing this trajectory, Harvey announced its fourth known acquisition of the year on September 9 by acquiring Guardrails AI, an organization that builds open-source tools for testing, monitoring, and managing autonomous AI agents.
Katie Burke, the Chief Operating Officer of Harvey, explained that the company’s corporate development strategy is fundamentally rooted in identifying exceptional technical talent with high accountability and deep domain experience within legal technology or closely adjacent industries. Pointing to Benchmark as a prime example, Burke noted that the startup’s co-founders understood the asset management space intimately, and their reputation came up so frequently in customer discussions that bringing them onboard felt like a natural alignment for the team.
Burke characterized Harvey’s overall approach to mergers and acquisitions as both selective and highly aggressive. She emphasized that the organization maintains an exceptionally rigorous standard for talent, and whenever leadership identifies a truly additive company, they move rapidly to integrate them—a pace they intend to maintain moving forward.
Meanwhile, Legora has pursued an even more sweeping rollup strategy within the legal technology arena. The Stockholm-based company’s five announced acquisitions for the year reflect a concerted effort to build a comprehensive, end-to-end platform for legal professionals by absorbing specialized teams focused on distinct facets of legal workflows and compliance.
In the customer service sector, Sierra’s acquisitions demonstrate a deliberate push to expand its geographic reach and push past the boundaries of conventional customer-service automation. In March, the company acquired Opera Tech, an enterprise AI startup based in Tokyo, as part of a broader expansion strategy into the Japanese market. This was followed by the acquisition of Fragment, a Paris-based firm that helps businesses automate complex operational workflows using artificial intelligence. By July, Sierra completed the acquisition of TakeOff, a young startup that had been operating for just 14 months while developing advanced long-horizon AI agents.
For the acquisition targets themselves, joining forces with a larger, well-capitalized platform frequently represents an attractive shortcut to massive scale, even when their standalone businesses are already experiencing rapid growth. Aakash Thumaty, the founder of TakeOff, detailed this perspective in a public blog post following his company’s acquisition by Sierra. Thumaty revealed that his startup was generating a near eight-figure annualized revenue run rate with a lean team of just three people.
While conventional advice for an AI startup growing at that pace might dictate raising additional venture capital, building out an independent sales team, and continuing on a standalone path, the reality offered a different calculus. Thumaty noted that although his company possessed capital, strong customer traction, and healthy momentum, the opportunity to join Sierra offered an unparalleled vehicle to accelerate their shared vision and construct it on a much grander global scale.
This surge in merger and acquisition activity across the technology landscape is being propelled by a combination of an expanding pool of eager corporate buyers and increasingly active serial acquirers who view consolidation as essential to survival and dominance. If the current transactional velocity persists through the final months of the year, industry analysts anticipate even greater consolidation and strategic dealmaking across the artificial intelligence sector in the near future.
