The influx of artificial intelligence (AI) innovation in the legal sector is now attracting talent from prominent Silicon Valley organizations.
Ethem Coban, previously a researcher at Meta, has recently left the tech giant to establish a legal technology startup, as reported by sources familiar with his move. Coban had focused on training Meta's language models to tackle legal inquiries effectively and is currently in discussions to secure $6 million in funding, valuing his new venture at $25 million.
Negotiations are still in their infancy, and the specifics of the investment could evolve over time.
This startup joins a rapidly expanding field in legal technology, once considered slow to adapt. Over the past two years, legal professionals have begun experimenting with tools leveraging advanced language models. Early adopters such as Harvey and Legora witnessed a surge in demand, sparking a flurry of investments in startups aimed at revolutionizing the legal practice.
This promising landscape is now drawing researchers from the very companies that are creating the foundational AI models.
Coban dedicated nearly two years to Meta, particularly at their Superintelligence Labs, where his efforts included refining models to improve their accuracy on legal matters and minimizing errors known as hallucinations. He has an academic background in law, having studied at American University and Goethe University in Frankfurt.
Meta has not responded to inquiries seeking comments on Coban’s departure.
In conversations with potential investors, Coban has articulated his vision for his new enterprise, which intends to assist law firms and corporate legal departments in crafting and personalizing AI models tailored to their specific knowledge areas. This initiative is based on the belief that organizations will increasingly prefer to develop their in-house AI systems, as it offers greater control over their data compared to relying on external vendors.
Legal firms are recognizing an opportunity to leverage extensive case files as a unique asset that cannot simply be purchased by competitors. For instance, Kirkland & Ellis, a top firm in terms of revenue, has allocated $500 million towards the creation of proprietary software, while Latham & Watkins is investing in Nvidia servers to tailor their models internally.
For Coban, the real challenge lies not in convincing law firms of the necessity of AI adoption, but rather in demonstrating that having an insider with profound knowledge of model design is advantageous for building these systems effectively.
