法律 AI 热潮从 Meta 超级智能实验室挖走研究员 Ethem Coban

The legal industry's artificial intelligence gold rush is luring talent from Silicon Valley's biggest labs.

Ethem Coban, a researcher at Meta, left the company earlier this month to launch a legal tech startup, according to a person familiar with the matter. Coban, who worked on teaching Meta's language models to reason through legal questions, has been in talks to raise $6 million at a $25 million valuation.

Talks are still early, and the terms of the deal could change.

The startup is the latest entrant in an increasingly crowded legal tech market. Long seen as laggards, lawyers have spent the past two years experimenting with tools built on large language models. Early movers like Harvey and Legora saw a crush of demand, setting off a wave of investment in startups promising to transform how lawyers work.

Now, that opportunity is attracting researchers from the companies building the underlying models.

Coban spent almost two years at Meta, most recently at its Superintelligence Labs, where he helped train models to give better answers to legal questions and reduce hallucinations, the person said. He previously studied law at American University and Goethe University in Frankfurt.

A spokesperson for Meta didn't respond to a request for comment.

Coban has told investors that his new company aims to help law firms and corporate legal teams build and customize models around their expertise. The bet is that companies will increasingly want to own their AI rather than license it from outside companies, because it gives them more control over their data.

Law firms also see a chance to turn mountains of case files into a competitive advantage that other firms can't simply buy off the shelf. Kirkland & Ellis, the industry's revenue leader, has committed $500 million to building proprietary software. Latham & Watkins has been buying its own Nvidia servers to customize models in-house.

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For Coban, the challenge won't be convincing law firms that they need artificial intelligence. It will be persuading them that someone who knows how the models work from the inside is best suited to build them.