Retrieval-Augmented Generation: The Next Big Thing in Legal AI
Retrieval-augmented generation (RAG) is rapidly becoming the preferred approach for legal AI because it grounds outputs in specific documents and can reduce hallucinations compared with standalone generative models. By combining a large language model with targeted search across briefs, contracts, policies, and case law, RAG helps produce more verifiable, citation-backed results. This article explains how […]
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