兔子先生传媒 Data Shows AI鈥檚 Most Active Startups Are Becoming Serial Acquirers

Some of the AI industry鈥檚 fastest-growing startups are becoming serial acquirers, buying smaller companies to fill product gaps, enter new markets and bring specialized teams in-house, a review of 兔子先生传媒 data shows. While AI giant is by far the busiest of these buyers, well-funded startups in legal tech, customer service and software development have also made multiple acquisitions this year.

The buying spree has pushed acquisitions of AI startups by other venture-backed AI companies to 195 through Sept. 29, according to 兔子先生传媒 data 鈥� 14% more than in all of 2025. Yet the number of buyers grew just 2%, indicating that increasingly active acquirers are driving much of the increase.

Those deals point to a new phase of competition in the AI sector: Well-funded startups are using M&A to broaden their products and reach new customers faster than they could by building everything themselves. In legal tech, for example, acquisitions are bringing research, regulatory monitoring and litigation tools into broader platforms.

CFO described that calculus in a earlier this year explaining the company鈥檚 back-to-back purchases of multiple startups: 鈥淢&A is explicitly part of how we accelerate what we’re building. The question we always ask is: does this deal get us somewhere faster than we’d get there ourselves?鈥�

Repeat buyers step up dealmaking

Some of the AI acquirers have returned to the dealmaking table more than once in recent years, 兔子先生传媒 data shows. Across the three-year period, 67 repeat buyers accounted for about 42% of all transactions tracked. OpenAI was by far the most active, with 20 AI-related acquisitions, including 10 this year.

This year鈥檚 other repeat buyers include and legal AI startup Legora, which have each announced five acquisitions, followed by legal AI startup with four. Customer-service AI provider and coding company have each made three acquisitions this year, while announced two. Many of the buyers are vertical AI startups acquiring companies in their respective areas.

Several of this year鈥檚 transactions are sizable.鈥檚 reported $1.65 billion acquisition of was the largest with a recorded price, followed by鈥檚 $1 billion acquisition of identity security startup.

Anthropic鈥檚 acquisition of, which develops AI for pharmaceutical research, was valued at $400 million. 翱辫别苍础滨鈥檚 $300 million acquisition of, a Los Altos, California, startup that uses customized AI in camera hardware for computational photography, and鈥檚 acquisition of, valued at up to $285 million, rounded out the five largest deals recorded in the dataset through Sept. 29.

Overall, prices were disclosed for only 12 of the 195 deals, making it difficult to gauge how much AI startups are spending on acquisitions overall.

Dealmaking has clearly picked up as more AI companies turn to acquisitions 鈥� and, in some cases, make them a recurring part of their growth strategy. 1

鈥淚t鈥檚 all about speed in the AI world,” according to , partner at , which has backed numerous AI startups including Anthropic and Legora. “It鈥檚 faster to acquire a team or product than build it yourself. If you鈥檙e not growing 10x, you鈥檙e not interesting to growth investors, which leaves a gap in the funding market for AI startups that need a home. High valuations have also given AI startups cheap currency to use their stock to get these deals done with minimal dilution.”

What AI startups are buying 鈥� and why

The specific companies being acquired offer insight into what AI startups hope to gain from their stepped-up M&A activity.

翱辫别苍础滨鈥檚 purchases have ranged widely, from healthcare data and scientific-writing software to developer infrastructure, security tools and specialized talent. The San Francisco-based company announced three acquisitions in January alone, setting the tone for a busy M&A year.

In January, it acquired:

, which built AI software to help executive coaches automate leadership assessment reports.
, an AI-powered health app that aims to unify scattered medical records from hospitals, labs, wearables and consumers.
, which provides LaTeX editing, error detection and team collaboration.

In February, OpenAI participated in an deal involving open-source AI agent and its creator, . Then in March, it announced plans to , a creator of open-source tools for software developers. It also snapped up , an open-source tool for testing AI applications.

In June, OpenAI agreed to buy , formerly known as Gitpod, which provides secure cloud environments where developers 鈥� and, increasingly, AI agents 鈥� can continue working after a user鈥檚 laptop is closed. In August, it also picked up , an AI presentation company that converts prompts, notes and documents into editable presentations.

Vertical AI roll-ups

Well-funded vertical AI startups, particularly in legal tech, have also been busy this year buying smaller companies, an analysis of 兔子先生传媒 data shows.

San Francisco-based Harvey鈥檚 AI-related purchases have focused on filling gaps around its core platform. developed tools for creating product demos, videos and guides, while built software that helps companies connect customer data and applications with AI systems.

New York-based developed software that helps asset managers capture insights from previous investments and apply them to new deals. That acquisition helped expand Harvey鈥檚 presence in the asset management space. Its fourth known acquisition this year, announced Sept. 9, was , which builds open-source tools for testing, monitoring and managing AI agents.

, COO of Harvey, told 兔子先生传媒 News that the company鈥檚 M&A strategy is rooted in finding 鈥渢echnical talent with high ownership and deep experience in legal tech or an adjacent space to legal.鈥�

She pointed to Benchmark as an example. The co-founders, she said, 鈥渒now the asset management space cold, and their name was dropped so many times in customer conversations that it was a natural fit for them to join our team.鈥�

Burke further described the startup鈥檚 M&A strategy as 鈥渟elective but aggressive.鈥�

鈥淲e hold an incredibly high bar for talent and when we identify an additive company, we move quickly and will continue to do so this year and beyond,鈥� she added.

Legora has pursued an even broader legal-tech rollup. The Stockholm-based company鈥檚 five announced acquisitions this year include:

, a nine-person Canadian startup whose agents work inside Word and Outlook;
, a Stockholm company building AI-native legal research tools;
, an Australian regulatory-intelligence platform that monitors more than 100 areas of law for changes;
, whose AI agents analyze documents and data for commercial real estate companies; and
London-based , which helps litigation teams extract facts from large collections of documents, identify inconsistencies and build case timelines.

Sierra鈥檚 acquisitions reflect an effort to expand both geographically and beyond conventional customer-service automation. In March, it acquired Tokyo-based enterprise AI startup as part of its expansion in Japan, followed by Paris-based , which helps businesses automate operational work with AI. In July, Sierra bought , a 14-month-old startup developing 鈥渓ong-horizon鈥� agents.

For acquisition targets, joining a larger platform can offer a shortcut to scale even when their own businesses are growing rapidly. TakeOff founder wrote in a July that his company was posting a 鈥渘ear 8-figure run rate鈥� with a team of just three people. 鈥淭he advice for an AI startup growing at our pace is to hire out a sales team, raise again, and keep going,鈥� he wrote. 鈥淲e had capital, customers, and great traction,鈥� but the Sierra acquisition offered an opportunity to 鈥渁ccelerate our shared vision and simultaneously build it at a grander scale.鈥�

The surge in M&A activity is driven by both a wider pool of buyers and increasingly active serial acquirers. At this pace, we should expect even more in the months and years ahead.

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