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Unclassified · 17 Sep 2026 · 02:00 CEST

Introducing Astra for Law

OpenAI · 17 Sep 2026 · 02:00 CESTRead original at OpenAI ↗
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Our most powerful model, configured into a new AI foundation for law.

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 ChatGPT 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. Together, they amplify Astra’s capabilities across the legal practice, while giving firms and legal technology companies the freedom to build their own applications and workflows.

Our new legal search index is one of the tools Astra for Law can use. Legal research often begins with finding the exact right authority, locating the relevant passages, and understanding how relevant and binding they are to the situation at hand. The index helps Astra for Law do that work, and complements the licensed content and specialist products firms rely on 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, the nonprofit behind CourtListener, 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. This benchmark measures how well the model can find relevant sources and passages, and how well its research answers meet the evaluation criteria.

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.

Astra for Law and GPT‑6 Astra’s performance on the Vals AI Legal Research Bench validation set, across reasoning effort settings.

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. That can mean distinguishing a court’s holding from its other observations, addressing cases that weaken an argument, or explaining how a contract exception shifts risk between the parties.

For example, when

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OpenAI · 17 Sep 2026 · 02:00 CEST

Open the original at OpenAI ↗