Introducing Search Toolkit | Mistral AI

What this post added

This post introduces the Search Toolkit, a new framework for building AI search pipelines. It details the components of the toolkit: Ingestion (document parsing, chunking, embedding generation with adapter interfaces), Retrieval (BM25, dense embedding, hybrid configurations), and Evaluation (recall, precision, MRR, NDCG). It highlights the benefits of a unified framework for reducing integration overhead and improving search quality. The post also provides a starter app template with Docker and Vespa for quick setup and demonstrates its use with sample data. It mentions battle-tested use cases in financial services, manufacturing, public sector, and media & entertainment, including an example with CMA CGM and Voxtral for fake news detection.