🔍 Just published: The real cost of "enterprise search" Algolia review reveals why teams pay $10k+/year for features they never use. Meilisearch alternative: Open-source, sub-50ms results, $30/mo cloud (or self-host free forever). Full breakdown 👉 www.meilisearch.com/blog/algolia...

🚨 It's billion with a B! We're very happy to announce that Meilisearch now processes over 10 billion searches each month spread across 10 million databases. Do you want to see the magic for yourself? Get started on our website → www.meilisearch.com

Who wins in the battle between semantic search and RAG? Discover the answer in our new guide! In it, you’ll learn: ✔️ How both of them work ✔️ The difference between them ✔️ Their limitations ✔️ The latest trends in semantic search and RAG Read all about it here 👉 www.meilisearch.com/blog/semanti...

⚡️ Under 50ms search response times aren't reserved for enterprise budgets anymore Meilisearch delivers Algolia-level AI features (hybrid search, semantic understanding, automated embeddings) with Typesense-level simplicity Check the full comparison:

There is a common misconception that RAG and prompt engineering are one and the same. But that couldn’t be farther from the truth. In this guide, we will shed light on these two concepts so you can make the right decision for your system. Read it here 👉🏻 buff.ly/3QMjxZU

🚀 The future of generative AI is here 😬 But only if you tackle hallucinations and context-limits head-on In our latest blog post, we explore how RAG + hybrid search (full-text + semantic) can dramatically boost your LLM’s accuracy and relevance 👉 Check it out: www.meilisearch.com/blog/masteri...

You can now experience Meilisearch AI in one click ⚡ No need to upload data – we’ve added a mock dataset and progress feedback so you can instantly see how it works. Fast. Intuitive. Powerful. Try it here → www.meilisearch.com

🔍 Most devs choose between: • Algolia ($500+/mo, premium pricing) • Elasticsearch (free* but needs dedicated DevOps) There's a third option delivering <50ms response times in a single-node architecture. Rust-based. Typo-tolerant by default. Hybrid AI search. www.meilisearch.com/blog/algolia...

Exciting news: Meilisearch is featured in the latest Fireship video covering OpenAI’s new browser, Atlas! It just dropped – and if you haven’t played with Meilisearch yet, here’s your sign. 👀 There’s a little code surprise in the announcement! www.youtube.com/watch?v=5uSb...

Guess who made it into the Product Hunt featured list 👀 Meilisearch Chat – our conversational AI layer for your data – was featured in front of 1M+ readers! Proud moment for the crew behind it 💜 www.producthunt.com/posts/meilis...

In the battle of retrieval-augmented generation, who will win: GraphRAG or vector RAG? We broke down both side by side to see which one’s better and help you make the decision easier. Dive into the ultimate showdown 👉: www.meilisearch.com/blog/graph-r...

That’s a wrap on Launch Week 🚀 Highlights: • Conversational AI (/chat endpoint) • GeoJSON + polygon-aware queries • Multi-modal (image + text + embedding) search • Personalization via Cohere 3.5 embeddings • Fair, predictable resource-based pricing Full recap →

Day 5: Resource-based Pricing 💸 Fair, usage-based pricing for Meilisearch Cloud. Transparent. Predictable. Developer-friendly. See the announcement →

Day 4: Personalization API Cohere 3.5-powered embeddings → tailored search results per user. Fast, private, no reindexing. Demo → personalization.meilisearch.com Docs → www.meilisearch.com/docs/learn/p...

Day 3: Multi-modal Search 🧠 Blend text, images, and embeddings for hybrid retrieval and recommendations. Built-in vector support – no extra setup. Demo → multi-modal.meilisearch.com Docs → www.meilisearch.com/docs/learn/a...

Day 2 → Advanced GeoSearch 🗺️ Search by polygons, multi-points, or custom shapes – with Meilisearch speed. See the demo: chantiers-paris.vercel.app And docs: www.meilisearch.com/docs/learn/f...

We’re live on Product Hunt today with Meilisearch Chat! 🎉 Support us here: www.producthunt.com/products/mei...

Launch week Day 1: Meilisearch Chat Conversational AI for your Meilisearch data – powered by RAG + precision search. Chat with docs, products, or private datasets. Try it → supportbot.meilisearch.com

✨ Launch Week starts next week! Big updates, new features, and fresh ways to connect search + AI. Don’t miss a thing — subscribe to stay informed 👉 dub.sh/3raK2mt

RAG isn’t just the buzzword of the month. It’s the secret sauce to building smarter apps using Ruby. In this step-by-step developer’s guide, learn: Why use RAG with Ruby What tools are needed How to build RAG apps using Ruby Dive in 👉 www.meilisearch.com/blog/build-r...

🚀 Launch Week is coming! Next week, we’re unveiling what’s next for Meilisearch – faster, smarter, and more human search. Be the first to know what’s launching 👇 👉 www.meilisearch.com/launch-week-...

We are now live on the AWS Marketplace 😎 AWS has been a great partner to us and we're super happy to now serve customers directly via their marketplace! Learn more on our blog: www.meilisearch.com/blog/aws-mar...

Are you ready to supercharge your Rails app with AI? Our step-by-step guide to building RAG applications on Rails will shed light on this topic, including: How Retrieval-Augmented Generation works The common pitfalls when building RAG in Rails How to build a RAG app in Rails

Have you seen our new Geosearch functionality? This database contains 1M+ documents and still queries in <3ms on a CUSTOM POLYGON. That means you can now draw any shape over any area and the geosearch experience will be instantaneous, even over large datasets

Building an effective Retrieval-Augmented Generation (RAG) system is only half the battle. Knowing if it actually works is where the real magic happens. In this guide, learn: • What is RAG evaluation • Why is it important • What are the key metrics 👉 www.meilisearch.com/blog/rag-eva...

Building with LLMs? You’ll need RAG. But you don’t need to overcomplicate it. Luis Serrano explains how to keep it fast, flexible, and open-source with Meilisearch. Full blog 👉

Think of modular RAG like LEGO. 🧱 You build Retrieval-Augmented Generation systems smarter and faster, as modular RAG treats each part of the process as separate but connected modules. All you have to do is snap them together into place. But how do you do that?

Check out this tutorial from our community! Sevalla shows how to simple integrate full-text search into a Flask app www.youtube.com/watch?v=Xw-3...

Traditional Retrieval-Augmented Generation (RAG) is a powerful tool. However, it often misses the connections between entities that lend answers depth. Enter GraphRAG, a game changer for connecting information, combining knowledge graphs with LLMs to produce more accurate responses.

We love seeing community contributors share their expertise 💜 This time, Luis Serrano walks you through how to build RAG pipelines with Meilisearch – a simple, fast, and open-source solution. Read here 👉

Ever wondered how to get RAG working without complex infra? 🤔 In a new blog, Luis Serrano shows how Meilisearch unifies full-text + vector search for fast, open-source RAG. Check it out 👉

Ever heard of adaptive RAG? It’s Retrieval-Augmented Generation’s smarter cousin. 🤭 For every query, adaptive RAG decides when and how to retrieve based on the complexity of the question. We break it down in plain English, discover everything about it here 👉 www.meilisearch.com/blog/adaptiv...

Curious about corrective RAG? We will demystify it for you. In our latest guide, we explain how CRAG works, why it matters, and where it fits into your workflow. Whether you’re managing projects or optimizing processes, this is your go-to resource for CRAG 👉 www.meilisearch.com/blog/correct...

Still waiting around for your traditional RAG to finish? ⌛ There’s a better, faster way to retrieve information from knowledge bases and generate responses: speculative RAG. But what exactly is it?

Automate your workflows with webhooks 🔌 Meilisearch can automatically send an HTTP POST payload to a URL you specify whenever a task’s status changes. Now, you won’t have to constantly poll the tasks API endpoint to know when dataset is done indexing. 👇

Here's everything we shipped in August 👇 www.meilisearch.com/blog/august-...

Not all RAG is created equal. In fact, it comes in 14 different flavors, from agentic RAG to module RAG to advanced RAG, each with its own set of advantages and disadvantages. We’ve broken them down in this article 👉 www.meilisearch.com/blog/rag-types #Meilisearch #RAG #RAGTypes

What if your users could just speak directly to your website? voice.meilisearch.com

Meilisearch v1.19.0 brings experimental sharding support: github.com/meilisearch/...

Announcing Meilisearch 1.18 🕷️ ◆ Return `queryVector` in the search response when using `retrieveVectors` ◆ Allow retrieving documents with vectors from specific embedders ◆ Support renaming indexes using the API github.com/meilisearch/...

Learn to build full-text search with Laravel Scout www.meilisearch.com/docs/guides/...

⚡ Check out this demo of song search against a >40GB dataset github.com/meilisearch/...

Announcing Meilisearch 1.16 🦚 ◆ Multi-modal search and embeddings ◆ Transfer data between instances ◆ Improved documents API www.meilisearch.com/blog/meilise...

Leverage hybrid search to boost the retrieval accuracy of your RAG pipeline www.meilisearch.com/blog/masteri...

Here's the recap of everything we shipped this month 💫 www.meilisearch.com/blog/july-20...

🤝 @firebase.com

Same Meilisearch, new flexible pricing ⚡ www.meilisearch.com/pricing/plat...

Build semantic search using any open-source LLM with Hugging Face www.meilisearch.com/docs/guides/...

what's 1 thing that search analytics could do better?

Build conversational search with the chat API www.meilisearch.com/docs/learn/a...