• One of Meta's AI researchers left the company this month to start a legal tech company.
• Ethem Coban worked on teaching Meta's language models to reason through legal questions.
• Since then, he's had talks to raise $6 million in funding for a startup, according to a person familiar.

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.

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.

• A version of this story originally appeared in the AI Insider newsletter.
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AI companies have already scraped much of the web. Now they're chasing something even more valuable: data that shows how humans actually work.

That's the focus of Business Insider's new series, The AI Data Grab. This week, we published three stories showing how the race for workplace data is accelerating.

One piece, from Charles Rollet, Tom Carter, and Stephen Council, examines the booming market for company records. AI firms are offering businesses six- and even seven-figure sums for anonymized Slack messages, emails, presentations, and internal documents.

The goal is to teach AI systems how people solve problems, collaborate, make decisions, and complete long, multi-step tasks. Those real-world workflows are becoming the fuel for the next generation of AI agents.

Another story, from Melia Robinson, explores how law firms are building AI systems around decades of legal knowledge, turning their own experience into a competitive advantage rather than relying solely on off-the-shelf AI models and tools.

A third piece, by Rya Jetha, reveals how AI companies pay people to record real-world work, such as cooking dinners and packing warehouses, to teach robots how humans perform everyday physical tasks.

Together, these stories point to a major shift in AI development. The first wave of generative AI was mostly about bigger models and faster chips. The next chapter is about machines understanding how work gets done, so AI can help us do it better and quicker.

Sign up for the AI Insider newsletter here. Reach out to me via email at abarr@businessinsider.com