How to build and optimize RAG in AI for reliable answers
Learn how RAG in AI works in practice, how to improve retrieval relevance, evaluate quality, secure data, and keep results up to date in production.
Maya Shin
Tutorials, product updates, and insights from the Meilisearch team
Learn how RAG in AI works in practice, how to improve retrieval relevance, evaluate quality, secure data, and keep results up to date in production.
How this global electronics manufacturer elevates product discovery with faster, more relevant search at scale
We patched LMDB to support nested read transactions on uncommitted writes - eliminating full database scans and making Meilisearch's vector store 3× faster
Find out what Search-as-a-Service is, how it works, key pros and cons, top providers, how to choose the right one, and more.
Learn what an index file is, how it works, where it’s used, and why it’s essential for fast data retrieval in systems like databases and search engines.
Learn what specialty search engines are, how they work, and why they offer more relevant, focused results for specific industries, tasks, and user needs.
Learn what proximity search is, how it works across major platforms, and how to use it to improve relevance, ranking, and user search experiences.
Intent understanding is where most conversational search implementations quietly fail. Here's why the translation layer between natural language and structured queries is where the real differentiation lives.
The transition to Meilisearch transformed Scenario’s search into a core product advantage
Learn how to design and optimize typeahead search to improve speed, relevance, and user experience across modern applications.
Learn what document indexing is, how it works, and why it’s key to fast, accurate information retrieval and efficient document management across industries.