On September 17, OpenAI published a blog post introducing Astra for Law, an AI foundation platform designed specifically for legal use. Its confidence comes from the scale of its data: the legal search index covers more than 230 million URLs and includes the CourtListener case database, which covers over 99.9% of published U.S. case law—effectively bringing almost all publicly available U.S. case law into the model's retrieval scope.

The performance was validated using a private test set from the Vals AI legal research benchmark, consisting of 200 U.S. legal questions. At the highest reasoning intensity, Astra for Law achieved an overall accuracy rate of 54.0%, while GPT-6Astra, which relied only on web searches, reached 38.7%, a difference of more than 15 percentage points. Specifically, in case law-oriented questions, Astra for Law found 24% more relevant cases; in audited target paragraph sets, it extracted up to 54% more relevant paragraphs from correct court opinions.

However, OpenAI emphasized that this is not an "AI lawyer." It primarily serves lawyers and legal software companies, performing several specific tasks: helping distinguish core reasoning from incidental comments in court decisions, actively finding unfavorable precedents, and analyzing how contract clauses allocate risks—focusing on increasing the chances of winning a case in court. In other words, it won't appear in court for you, but it will show you every possible gap in the precedents.