Today, we’re introducing Astra for Law: a new foundation for law firms and legal technology companies to build AI products and workflows around their expertise. It combines GPT‑6 Astra, our latest and most powerful model, with settings, tools, and context tailored for professional legal work. API customers including Harvey and Legora will be able to build on Astra for Law, bringing this intelligence into their own products and workflows. As our frontier models advance, we’ll bring these legal capabilities to our latest models. We are also expanding our work on privacy and governance to give law firms specific controls for confidential client work. Firms can also customize Astra for Law using our 26 new ecosystem plugins that connect Chat GPT to the specialist tools firms already use, like Relativity and Clio.

Astra for Law combines GPT‑6 Astra with a powerful legal search index and instructions for legal analysis and writing. Legal research often begins with finding the exact right authority, locating the relevant passages, and understanding how relevant and binding they are. The index helps Astra for Law do that work, and complements licensed content from providers such as Thomson Reuters. By using the legal search index, Astra for Law can search U.S. case law, statutes, regulations, court rules, and administrative decisions across a corpus of more than 230 million URLs, with sources added daily. Our work with Free Law Project brings its case-law collection covering more than 99.9% of published U.S. precedential case law into this research experience.

To measure how this configuration improves legal research, we tested Astra for Law’s complete setup on 200 U.S. legal research questions from the private validation set of Vals AI’s Legal Research Bench. At the highest reasoning effort for both systems, Astra for Law passed the evaluation’s overall correctness check on 54.0% of questions, compared with 38.7% for GPT‑6 Astra using web search alone – a 40% relative improvement. Astra for Law also produces more comprehensive answers. On case-law-focused questions, Astra for Law found 24% more reference cases than GPT‑6 Astra using web search alone at the highest reasoning effort. On the audited set of target passages, it retrieved up to 54% more relevant passages from the correct court opinions, when comparing the systems at the same reasoning effort. The result is a stronger research foundation for advising on a deal, assessing a dispute, or developing a legal strategy, with reliable authorities the lawyer can examine for herself.

Legal research is only the first step. Custom instructions for legal analysis and writing guide Astra for Law in applying that research to the client’s facts, developing arguments or deal terms, and identifying weaknesses and uncertainty. For example, when prompted to identify good law with similar fact patterns, Astra for Law could both pinpoint relevant precedent and match fact patterns better than other frontier models.