🥳 Join our launch event

Meilisearch product update: AI-powered hybrid search, monitoring, and more. Thursday, March 7th 4PM CET | 3PM GMT | 10AM EST

Join us on March 7th to discuss our recent releases and get a sneak peak of what’s coming on Meilisearch Cloud. Spoilers—hybrid search, new embedding models, GPU support, and more. 🤫

🤔 Vector embeddings, explained

Vector embeddings

Wondering what are vector embeddings? What is the semantic space? How is it relevant for search? Our very own @CarolainFG dug deep into the matter to create this high-level educational piece.

🚀 Upgrade to 1.6

Meilisearch 1.6 release notes

We released Meilisearch 1.6 in January. Upgrade to benefit from hybrid search, indexing speed improvements, and further customization of proximity ranking rule. It’s time to upgrade. 👇

💡 Indexing best practices

All our tips to index data efficiently and speed up the indexing process.

🔄 Syncing with your Postgres database

Learn how to keep your Meilisearch in sync with a Postgres database.

🐬 Add search to your Appwrite application

Learn how to add a search function to your Appwrite application.

🐇 Meilisearch v1.7 release candidate

Get a preview of what’s coming next (and give your feedback!)

🟧 Laravel Scout guide

Learn how to use Meilisearch in your Laravel 10 application.

🥰 Made with Meilisearch

Rerun.io added a search bar to allow users to search through all their documentation and SDKs API references. The site is built with React and uses Analytics to allow them to improve the docs content.

rerun.io search interface

We’re always looking to promote new projects from the community. Post yours in the #built-with-meilisearch Discord channel!

🤓 Life at Meili

Our engineer @dureuill wrote about how dynamic management of virtual memory enabled us to remove limitations in Meilisearch indexing policy. Attention, this one is technical.

Squeezing millions of documents in only 128 TB of virtual memory

🦸 We're hiring!

See our open positions: