The real enemy of building a search pipeline is "stitching together disparate tools" 🔍 Here's an open-source framework that unifies ingestion, retrieval, and evaluation. Title: Introducing Search Toolkit URL: 🔍 Overview The Mistral Search Toolkit is a composable, open-source framework that streamlines production search pipelines for AI applications. It integrates ingestion, retrieval, and evaluation into one unified system. ❓ Challenges Solved Building a production-grade search pipeline is harder than it looks. ・Organizations spend enormous time integrating disparate tools ・As a result, they can't focus on actually improving search quality 💡 Methodology & Features It's built from three components. ・Ingestion: process multiple data sources with configurable pipelines handling parsing, chunking, and embedding generation ・Retrieval: offers BM25 sparse search, dense embedding-based search, and hybrid configurations ・Evaluation: built-in metrics including recall, precision, MRR, and NDCG to measure each configuration You can run the whole ingestion → retrieval → evaluation flow in one framework. 🌍 Use Cases ・Enterprise search across wikis, repositories, and file storage ・RAG systems that want to measure retrieval quality in isolation ・Domain-specific retrieval for legal or medical content ・Agentic systems needing reliable indexed search alongside live data It's production-ready and already deployed across financial services, manufacturing, public sector, and media. #Search# #RAG#