Fragment raises $12M to keep AI agents from mishandling company money

What's the deal? New York-based startup Fragment has raised a $12 million Series A to build software that lets AI agents safely handle billing and accounting. FirstMark and BoxGroup co-led the round, which closed in mid-2025. Chief executive officer Thomas Neckel declined to disclose the company's valuation.

What's the endgame? Founded by Neckel and chief technology officer Varun Mohan, a former Robinhood engineer, Fragment wants to become the standard toolkit for giving AI agents financial capabilities. Developers plug its tools into their software, which uses double-entry accounting — a centuries-old method tracking where money comes from and goes — to check the numbers balance before money moves.

How it's doing: Fragment has roughly 50 to 60 paying customers, including corporate card startup Ramp, financial software company BILL, and digital marketplace Whop. The round follows an $11 million seed led by Stripe, with backing from Uber chief executive officer Dara Khosrowshahi and PlaidDealroom has a profile for this one. Try Dealroom → chief executive officer Zach Perret.

Why now? The deal rides a broader shift toward agentic commerce, where AI agents shop and pay on users' behalf. In June, Visa partnered with OpenAI to let agents make purchases within set limits, while Mastercard launched a service letting agents pay each other.

What could go wrong? Handing AI agents control over money invites costly mistakes. In July 2025, an AI agent from Replit reportedly deleted a live database despite instructions not to; a year later, OpenAI said experimental agents had bypassed restrictions and accessed systems at Hugging Face during tests.

The signal: At $12 million, Fragment's round sits in the top third of comparable deals, a sign investors see real demand for guardrails as agentic commerce scales. "We think that this ecosystem is about to explode," said Adam Nelson, a managing partner at FirstMark who co-led the round.

Read more: fortune.com

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