Skip to main content

Mistral's Agentic Search: Multi-Step Retrieval Boosts Complex Document Accuracy to 86%

For companies building AI systems, there's a familiar headache: the most valuable knowledge is locked away in dense, confidential documents—financial reports, legal contracts, government filings. Traditional retrieval-augmented generation (RAG) often stumbles here, because it grabs fixed chunks of text without the ability to reason or dig deeper. That's exactly the problem Mistral AI set out to solve with its new Agentic Search.

From Mechanical Retrieval to Active Reasoning

The old way of doing things is like sending a librarian to fetch a book and then asking them to answer questions without ever opening it. The model gets a snippet, and that's it. Agentic Search changes the game by giving the model a set of tools that mimic how a human would actually work through a document:

  • search: Scans the entire corpus for relevant documents.
  • open: Opens a specific document.
  • navigate: Jumps to a particular page or section.
  • read: Pulls the content at that spot.
  • grep: Finds specific patterns within the open document.

With these tools, the model can check what it's retrieved, refine its search, follow leads into the underlying data, and even cross-reference multiple documents. It's no longer a one-shot retrieval; it's an active investigation.

Real-World Results That Speak Volumes

The proof is in the numbers. On FinanceBench, a test involving 368 complex SEC filings averaging 147 pages each, simply adding the search loop tripled accuracy. When the full navigation toolkit was deployed, accuracy soared to 86%. And it wasn't just about accuracy—latency dropped significantly, and token usage fell by up to a third.

But it's not just financial documents. On OfficeQA Pro, a benchmark packed with 696 scanned, table-heavy government PDFs, the agentic approach delivered a breakthrough in accuracy, showing it can handle deep tables and structured numerical queries with ease.

Flexible Deployment for Real-World Needs

What's more, Agentic Search fits into existing setups without a fuss. Whether you're working in the cloud or on-premises, it can be embedded in Libraries within Studio and Vibe, or integrated into custom workflows via the Mistral Search Toolkit. That flexibility means enterprises can finally unlock the value of their sensitive data and build high-precision retrieval systems that actually work.

Key Points

  • Traditional RAG limitations: Fixed text chunks, no reasoning or iteration.
  • Agentic Search tools: search, open, navigate, read, grep—enabling multi-step retrieval.
  • Performance gains: Accuracy up to 86% on FinanceBench; significant latency and token reductions.
  • Versatility: Handles complex documents like financial filings and government PDFs.
  • Deployment options: Cloud and on-premises, with integration via Studio, Vibe, or the Search Toolkit.