Meilisearch Launch Week is live 🔥 Day 1: Sharding & Replication - one of our biggest infrastructure releases ever.
Scale beyond a single node. Instant failover. Global routing. And they're fully composable.
Learn more: www.meilisearch.com/blog/shardin...

Meilisearch Launch Week April 13-17th 2026 Meilisearch Launch Week: Bigger scale. Tighter security. Same search you love.

Pre-weekend reminder: Meilisearch Launch Week starts next Monday, April 13.
Multiple features dropping in a row. At least two of them have been a long time coming.
See you Monday 🙌

Three things dropping in Meilisearch Launch Week next week:
– Horizontal scaling
– Enterprise security (SSO + MFA)
– AI chat, straight from your index
...and more. We kick off Monday 👀 www.meilisearch.com/launch-week-...

Meilisearch Launch Week April 13-17th 2026 Meilisearch Launch Week: Bigger scale. Tighter security. Same search you love.

Meilisearch Launch Week starts next Monday April 13

Five features. Three themes: infrastructure scale, enterprise security, developer experience.

First drop Monday - sign up to stay updated 👀 www.meilisearch.com/launch-week-...

RAG-as-a-Service: what it is, use cases, providers & more Learn what RAG-as-a-Service is, why it matters, common use cases, key benefits, and how to evaluate providers to build more accurate AI applications faster.

RAG-as-a-Service keeps coming up in AI conversations – but what does it actually mean?
We wrote a guide covering what it is, how it works, why companies are choosing it, and what to look for before picking a solution.
👉 www.meilisearch.com/blog/rag-as-...

Meilisearch Launch Week is coming next week:

📅 April 13th–18th. Register your interest to get early access and updates:
👉️ share-eu1.hsforms.com/1zljrJkBuTG2...

How Touchless powers instant, scalable vehicle search for large dealer groups Learn how Touchless uses Meilisearch to deliver fast, faceted inventory search across multi-rooftop dealer marketplaces — with real-time filtering, infinite scroll, and 20-minute dealer onboarding.

Automotive inventory search is uniquely hard, and buyers filter across a dozen attributes at once. Here's how Touchless solves it with Meilisearch: www.meilisearch.com/blog/touchle...

Self-RAG explained: how self-reflective retrieval boosts AI outputs Learn what self-RAG is, how it works, and why self-reflective retrieval-augmented generation reduces hallucinations and improves reliability in LLM systems.

You know what's gotten better at checking its own work? 👀 AI.

Self-RAG lets models evaluate their own outputs and decide when to go fetch more context. Our latest article breaks down how it works 👉 meilisearch.com/blog/self-rag

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.

You've asked an AI something - and it confidently got it wrong.

RAG fixes that. It pulls in real data before answering, so your AI stops guessing and starts being useful.

Build better RAG pipelines with Meilisearch 👉 meilisearch.com/blog/rag-in-ai

Meilisearch Meilisearch: A powerful, open-source search engine offering fast and relevant full-text searches. Enhance your search capabilities with features like facet search, semantic search, hybrid search, and…

Samtec inc runs 1.5M monthly searches across a catalog with trillions of part combinations. Engineers don't browse - they search for specifics, and slow or irrelevant results cost sales.
Read the full story on our blog 👇
www.meilisearch.com/blog/samtec-...
#Search #B2B #Ecommerce

kero (@kerollmops.com) Co-founder and Tech Lead at @meilisearch.com. You can find my blog on https://blog.kerollmops.com. I love #rustlang.

Our CTO bsky.app/profile/kero... just dropped another one of his deep-dive posts.
We patched LMDB – the database engine inside Meilisearch – to make our vector store 3x faster. 6 embeddings/sec → 20, on a real customer with 19M vectors.
It's a good one: www.meilisearch.com/blog/3xfaste...

We're heading to KubeCon + CloudNativeCon in Amsterdam (March 23–26)! 🇳🇱

Building search into your cloud native stack? Reach out to set up the time, or come find Chiara from our team at the event.
#KubeCon #CloudNativeCon

Search-as-a-Service explained: how it works, providers, and more 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.

Custom search infra is costly, complex & slow to scale.
More teams are switching to Search-as-a-Service — enterprise-grade search through simple APIs.
✅ Lower costs
✅ AI-powered relevance & personalization
✅ Faster UX
Is it right for you? 👉 meilisearch.com/blog/search-as-a-service

Release v1.39.0 🐳​ · meilisearch/meilisearch What's Changed ✨ Enhancement 🔬 Cross-index document hydration Add a new ForeignKeys setting allowing to hydrate documents with documents coming from other indexes. 📓 Note: This implementation…

Most search indexes end up bloated - you copy the same data everywhere just to get complete results.
Our new 'foreignKeys' links indexes together. Store a reference, get back the full object at search time. Your indexes stay lean. Your results stay rich.
Full release:

Meilisearch March updates Your regular recap of all things Meilisearch. March 2026 edition.

The March Meilisearch update is here!
New ranking rules, replicated sharding in the engine, major embedding performance gains, and a bunch of Cloud UI improvements.

Oh, and we officially joined the Rust Foundation 🦀
Full update:

Release v1.36.0 🐙 · meilisearch/meilisearch Version v1.36.0 introduces an exciting update to the ranking rules to improve the engine's relevance. It's actually the first time we've made such a change since v1.0, and we're really happy about ...

✨ New: new ranking rules!

🔹 attributeRank → prioritizes matches in higher-weighted searchable attributes
🔹 wordPosition → prioritizes matches closer to the start of an attribute

Insert custom rules like price or date exactly where you want 🎯
Thanks @kerollmops.com!
More: github.com/meilisearch/...

Proximity search: Improve relevance & deliver smarter results Learn what proximity search is, how it works across major platforms, and how to use it to improve relevance, ranking, and user search experiences.

Ever searched for something but couldn't find the right words?
Proximity search fixes that by focusing on intent over exact keywords, so results feel relevant even when phrasing isn't perfect.

We broke down how it works in our latest guide 👇

A few weeks ago, our team attended @fosdem.org event in Brussels 🇧🇪

FOSDEM is a free, community-run event for open source developers and projects. We gave a talk on language support in search engines - recording is finally live 👇

🎥 mirrors.dotsrc.org/fosdem/2026/...

Powering the generative AI era: How Scenario scales asset discovery with Meilisearch Meilisearch: A powerful, open-source search engine offering fast and relevant full-text searches. Enhance your search capabilities with features like facet search, semantic search, hybrid search, and…

Scenario.com runs 35M monthly searches across millions of assets.
At that scale, slow or broken search doesn't just frustrate users - it kills the product experience.

Here's how Scenario's team built search infrastructure that keeps up 👇
www.meilisearch.com/blog/scenario
#AI #Search #GenerativeAI

Designing effective typeahead search for faster, smarter UX Learn how to design and optimize typeahead search to improve speed, relevance, and user experience across modern applications.

Bad search = lost business. It's simple.

Autocomplete search (also known as typeahead) fixes this by helping people find what they need before they even finish typing. We broke down exactly how to do it right:

🔗 www.meilisearch.com/blog/typeahe...
#TypeaheadSearch #UXDesign #SmartSearch

Retrieval Augmented Generation (RAG), Search, and Vector Databases How do you get your LLM to speak factually? Using Retrieval Augmented Generation (RAG).Learn all about RAG, search, and vector databases in this video! It complements a series of posts written in…

RAG conversations usually raise more questions than answers.
Luckily, we partnered up with Luis Serrano for this one. Luis is great at explaining complex stuff in simple terms.
If RAG is on your radar, give this a watch 👇

Meilisearch January updates Your monthly recap of everything Meilisearch. January 2026 edition.

The first 2026 edition of Meilisearch Monthly is live on our blog!

🔐 SSO & SCIM for enterprise teams
⚡ 7x faster indexing
📊 Search analytics for all Cloud projects
🧩 Sharding improvements
Plus: Gemini embeddings, FOSDEM 2026, and more.

👉 Read the full blog:

🔍 Just published: Why Elasticsearch pricing confuses 73% of developers

You're calculating CPU + RAM + storage across nodes before knowing your actual costs.

Meilisearch alternative: $30/mo flat, 50k searches included, production-ready in 5 min.

Full breakdown 👉 www.meilisearch.com/blog/elastic...

🔍 New analysis: Why developers are choosing Meilisearch over Elasticsearch in 2025

The reason: simplicity.

Elasticsearch: Distributed clusters, shard management, dedicated DevOps
Meilisearch: Single binary, <50ms search, works out-of-the-box

Full comparison 👉 www.meilisearch.com/blog/elastic...

⚡️ Spent 3 weeks testing Elasticsearch, Qdrant, and Meilisearch for the same search workload.

The results: $99/month + weeks of config vs $30/month + 1 hour setup.

Both delivered <50ms searches. One didn't require a distributed systems PhD.

www.meilisearch.com/blog/elastic...

RAG vs. long-context LLMs: A side-by-side comparison Compare the key differences between RAG and long-context LLMs. See which approach best suits your needs, where to apply them, and more.

And more! But you’ll have to read the article to find out all there is to know about RAG versus long-context LLMs 👉 www.meilisearch.com/blog/rag-vs-...

In the battle between RAG and long-context LLM – which one truly gets your data?

We’ll break down:

When you should use RAG over long-context LLMs
Their respective advantages and disadvantages
How RAG and long-context LLM perform on benchmarks

Retrieve and gain: 3 RAG use cases you can ship today Building real RAG systems isn’t about flashy demos – it’s about shipping features that stay fast, accurate, and reliable as your product grows.

Hot off the press: Our final collaboration with Luis Serrano

“Retrieve and gain: Three RAG use-case patterns you can ship today” – why real-world RAG isn’t demos, but about getting search and AI features reliable, fast, and scalable.

Building a lightning-fast search engine - Clément Renault | EuroRust 2025 *Building a lightning-fast search engine - Clément Renault at EuroRust 2025 🦀* In this talk Clément talks about how Meilisearch has been using Rust to power fast open-source search. *About Clément…

🚀 Our EuroRust 2025 talk is live!

Our CTO, @kerollmops.com, breaks down how we build Meilisearch – a lightning-fast, open-source search engine powered by Rust.

🦀 Real infra lessons
⚡️ Low-latency architecture
🔍 How Rust enables our speed and safety

🎥 Watch: www.youtube.com/watch?v=ULA1...

Spent 40+ hours comparing search infrastructure:

Elasticsearch: $99/mo+, steep learning curve, incredible power
Pinecone: Vector-first, vendor lock-in, $50/mo+
Meilisearch: <50ms hybrid search, MIT license, $30/mo

The differences surprised us: www.meilisearch.com/blog/elastic...