Mistral launches Agentic Search, multi-step retrieval pushes enterprise doc-Q&A accuracy to 86%
On Aug 20 Mistral AI launched the upgraded Agentic Search with multi-step retrieval loops, replacing single-shot RAG. Five filesystem-like tools let agents inspect, refine, drill into underlying evidence and cross-reference across docs, lifting complex document QA accuracy to 86 percent.
On August 20, Mistral AI officially launched the upgraded Agentic Search, aimed at the enterprise retrieval-augmented generation space. The core idea is to evolve single-shot RAG — where the model answers only from the initial retrieved chunks — into a multi-step retrieval loop, so the model is no longer constrained by the quality of its first retrieval pass when answering complex document queries.
Built on top of Mistral's existing enterprise search indexes, Agentic Search exposes five filesystem-like operations to the model so it can actively inspect retrieved content, refine the search strategy, drill into underlying evidence, and cross-reference across multiple documents. In industry benchmarks Agentic Search pushes complex document QA accuracy to 86 percent.
The offering fits both cloud and on-prem deployments: it can be embedded in Mistral's Studio and Vibe Libraries or integrated into customer-built workflows via the Mistral Search Toolkit. Mistral officially positions Agentic Search as infrastructure for unlocking sensitive enterprise data and building high-precision retrieval systems. It has shown practical utility on the complex document query scenarios Mistral emphasizes — contracts, technical manuals, cross-document reports, compliance text, and policy/legal material where traditional search typically falls short.