Why More Startups Are Buying Other Startups In 2025

Despite a pickup in IPOs, startup exits and funding are still harder to come by than in years past. Add to that an increasingly competitive landscape for AI startups, and it鈥檚 no surprise that we鈥檝e seen an upturn in startups buying other startups this year.

The reasons for the rise in startups buying their brethren are varied. In many cases, consolidation is driven by market forces, including a more challenging fundraising environment and more affordable valuations for buyers. For other startups, it鈥檚 simply faster to buy another company than try to build out certain technologies themselves.

By the numbers

In the first half of 2025, there were 427 reported M&A deals globally in which startups bought other startups, according to Crunchbase . That compares to 362 in the same period last year, representing an 18% increase.

For comparison鈥檚 sake, in the full years 2021 and 2022, there were more than 1,000 deals in which startups bought other startups, per Crunchbase data.

Buyer鈥檚 market

, managing partner of investment banking firm , believes that we鈥檙e seeing more early-stage startups combining forces because the fundraising environment 鈥渉as become so challenging.鈥�

鈥淰enture capital is still tight, and without enough liquidity events to cycle capital back to LPs, VCs are being far more selective,鈥� he told Crunchbase News. 鈥淔or founders, it鈥檚 survival of the fittest 鈥� and that means getting creative to build a very tight investment thesis.鈥�

In many cases, a merger between two early-stage companies can create a stronger, more compelling narrative for investors, in Mufson鈥檚 view.

鈥淚t may broaden the customer base, consolidate IP, or, increasingly, bring in critical capabilities like AI,鈥� he added. 鈥淔or startups lacking in AI expertise, acquiring or merging with a team that has that technical depth can help accelerate product development and improve funding prospects in a highly competitive market.鈥�

Startup adviser , owner of Israel-based , agrees that the most significant driver of the startup-to-startup M&A uptick is the tightening of venture funding 鈥� despite a modest bump in venture funding globally in Q2.

鈥淪mall scale, startups which are far from being profitable have a hard time raising capital as VCs become more conservative, so they see M&A as the most logical option,鈥� he told Crunchbase News in an email interview.

Another driver, Sagie believes, is that valuations appear to be 鈥渟tabilizing at reasonable ARR multiplier ranges.鈥�

This allows for larger startups that raised large rounds in 2021 at 40x-70x ARR valuations to use cash reserves to acquire smaller startups at reasonable valuations.

鈥淪o rather than facing a down round, they鈥檙e deploying that capital toward acquiring startups, especially ones that offer one of the three “Ts: complementary tech, traction, or talent,鈥� Sagie added.

On the other side of the spectrum, the larger startups who are more financially sustainable with impressive unit economics and growth KPIs are even more attractive as startup buyers, in Sagie鈥檚 view, 鈥渁s their equity is a more valid asset versus an overpriced, cash burning unicorn.鈥�

Purchases include larger deals

Some of the deals this year have also been high-dollar transactions. And unsurprisingly, some of the larger deals involved AI companies.

Specifically in the AI arena, one of the buzziest M&A transactions was s May purchase of , the device startup co-founded by famed product designer , for a reported $6.5 billion.
OpenAI also tried to purchase artificial intelligence-assisted coding tool for $3 billion but that deal fell through. Instead, swept in to scoop up what was left of Windsurf after announced in mid-July that it was paying $2.4 billion to license Windsurf鈥檚 technology and for compensation.

Not all large M&A deals involved AI companies. Other notable startup purchases of peers this year include:

Prime brokerage was acquired by crypto payments company in a $1.25 billion transaction announced in early April;
In mid-May, announced its plans to acquire database management platform in a deal reportedly valued at ;
More recently, cybersecurity unicorn announced it was purchasing , a medical device security startup in a deal valued at just over $100 million; and
On July 1, Canada-based legal software company said it plans to acquire Spain鈥檚 from for $1 billion.

Also, many of the major acquirers raised large rounds before making their buys 鈥� with OpenAI in early April announcing a staggering $40 billion investment led by . That deal marked the biggest venture investment ever. Last December, Databricks raised $10 billion at a $62 billion valuation, marking one of the largest venture capital raises of 2024 and one of the largest on record.

Asset purchases and acquihires

, co-founder of SSM Law, notes an interesting trend she鈥檚 seeing: more asset acquisitions plus acquihires. This is where larger technology companies are buying the assets (think IP portfolio) of an early-stage company and taking one to three people from the founding team to integrate the technology and transition customer relationships.

SSM Law generally represents tech startups being acquired by larger, more established startups who have received more venture capital financing. An example of this would be an AI company that received a seed or Series A funding being acquired by a Series C or D company.

鈥淭he seller’s motivation to sell is often economic or market related 鈥� i.e., this company could not raise another round of venture capital or simply saw the writing on the wall that a big tech company was going to surpass them on 鈥榞o-to-market鈥� due to strategic acquisitions or consolidations,鈥� she told Crunchbase News in an interview.

The buyer’s motivation to buy is likewise economic, Mignano notes. It鈥檚 typically cheaper to buy the technology than build it, and cheaper 鈥渢o buy the team with a six-month golden handcuff earnout than recruiting.鈥�

But it鈥檚 also based on a rush to market, most particularly in the extremely competitive AI field.

鈥淔or AI companies, the buyer has immediate access to proprietary model architectures, inference platforms or edge-device integrations without the spend associated with AI training,鈥� she said. 鈥淭he buyer gets to immediately procure specialized datasets or fine-tuned models from a seller that effectively block out the competition in verticals with especially clunky sales cycles such as law, government or hospitals.鈥�

In general, Mignano believes that 鈥渂uyers are in a really good place right now.鈥�

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