Cleary Gottlieb Partners with Stanford's Liftlab to Advance AI in Legal Services

Sep 19, 2025
Cleary Gottlieb is collaborating with Stanford Law School's Liftlab to integrate AI into legal services, as announced in a press release. The firm will serve as a Founding Advisor, focusing on AI-driven legal personas.

Cleary Gottlieb is collaborating with Stanford Law School's Liftlab to integrate artificial intelligence into legal services, announced in a press release. As a Founding Advisor, Cleary Gottlieb will work with Liftlab on research at the intersection of AI and legal practice, focusing on the development of 'Legal Personas'—AI systems designed to reason like experienced lawyers.

This partnership aims to enhance the training and development of Cleary's legal team by using AI to augment learning experiences and prepare lawyers to effectively use technology in client service. The collaboration provides a platform for exploring future possibilities in legal learning and development through rigorous research.

Cleary Gottlieb's Managing Partner, Michael Gerstenzang, emphasized the firm's commitment to innovation and excellence in client service, highlighting the importance of evolving training methods to harness AI's potential. The initiative is part of Cleary's broader strategy to lead in AI innovation within the legal industry.

We hope you enjoyed this article

Consider subscribing to one of our newsletters like Legal AI Weekly or Daily AI Brief.

Also, consider following us on social media:

Free newsletter

Legal AI Weekly

The source for the Legal AI software news, analysis, emerging applications: contract review, e-discovery, research.

Whitepaper

Tensordyne Napier: What If One Rack Could Do the Work of Nine?

Tensordyne

This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.

Read more
Free, six days a week

Daily AI Brief: the AI news that matters, in your inbox.