Tutorials, product updates, and insights from the Meilisearch team
Indexer edition 2024 revolutionizes search performance with parallel processing, optimized RAM usage, and enhanced observability. See what's new in our latest release.
Learn how LSI works under the hood, see a practical Python implementation, and discover why this foundational technique remains relevant in today's AI-driven search landscape.
We've built a bridge between Meilisearch and AI assistants using the Model Context Protocol (MCP), enabling developers to manage search infrastructure through natural language.
Meilisearch 1.13 stabilizes AI-powered search, introduces remote federated search – laying the groundwork for sharding – and makes version upgrades easier.
Your monthly recap of everything Meilisearch. January 2025 edition.
Learn how enterprise search transforms data access and boosts productivity. Get expert insights on implementation, providers, and ROI in this guide.
Learn how to cache semantic search to slash API costs and response times. Discover practical strategies for implementing caching.
Discover best practices for building a RAG system, with tips on optimizing documents, integrating AI, and why effective retrieval is key to success.
Learn to boost search efficiency with personalization and recommendation strategies with case studies and tips.
Your monthly recap of everything Meilisearch. December 2024 edition.
Meilisearch 1.12 brings significant indexing speed improvement and introduces new APIs disable prefix search and facet search, and retrieve task batches.
![Fuzzy search: a comprehensive guide to implementation [2026]](/_next/image?url=https%3A%2F%2Fres.cloudinary.com%2Fmeilisearch%2Fimage%2Fupload%2Fv1766418783%2Fblog%2Fcovers%2Ffuzzy-search-feature.avif&w=3840&q=75)
Learn how to implement fuzzy search in 2026 to handle typos and misspellings, with practical code examples and best practices for better UX.
