meilisearch
Meilisearch is an open-source, developer-focused unified search and AI retrieval platform that provides fast, relevant, and easy-to-integrate search (including full-text, semantic, hybrid, and multimodal capabilities) for websites and applications.
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Best for: Software & Gaming
What it does
AI Agents software for decision-makers comparing workflow fit and alternatives.
Best fit
Software & Gaming
Pricing snapshot
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meilisearch
Meilisearch is presented as a unified search and AI retrieval platform designed for applications and websites, delivering fast, relevant results with minimal configuration. The product emphasizes search-as-you-type performance (returns in less than 50 milliseconds), plug-and-play deployment, and advanced relevancy out of the box. Meilisearch supports a range of retrieval capabilities including full-text search, semantic search, hybrid search, multimodal search (images, video, audio alongside text), vector storage for embeddings and RAG, federated search across multiple data sources, and search analytics to inform product decisions. The offering targets developers and organizations (apps, e-commerce, media, enterprise) and highlights developer ergonomics via self-explanatory APIs and multiple SDKs.
Open-source AI search engine for fast and relevant full-text searches.
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Claim this listing for $29Key Features
Lightning fast search-as-you-type
Search-as-you-type returns answers in less than 50 milliseconds, enabling very low-latency user experiences.
Plug-n-play deployment
Deploy in a matter of minutes with smart presets that let you start searching data with zero configuration.
Full-text search
Reliable and performant full-text search with features like geosearch and faceting to improve relevancy.
Semantic search
Unlock deeper understanding and context in queries for more meaningful results.
Hybrid search
Blend full-text efficiency and semantic embeddings for improved retrieval quality.
Multimodal search
Search across images, video, and audio alongside text using AI-powered embeddings.
Filtering, faceting and sorting
Build complex search interfaces using a toolkit that integrates full-text and semantic search.
Vector storage and embeddings
Store and retrieve vectors for similarity queries, advanced search, or RAG applications.
Federated search
Search across multiple data sources at once to boost relevancy and user experience.
Search analytics
Gain actionable insights with analytics to make data-driven search improvements.
Geosearch
Deliver location-specific results and allow filtering/sorting based on location.
Developer experience & SDKs
Self-explanatory API and SDKs across languages and frameworks to simplify integration and development.
Open source & community
Open-source project with community contributions, GitHub, Discord, and public roadmap.
Pricing
Current pricing details are not available from the vendor source.
Use Cases
App & site search
Provide fast, relevant search experiences in web and mobile apps with out-of-the-box relevancy and search-as-you-type.
E-commerce search
Improve product discovery and ranking with hybrid search, faceting, filtering, and geosearch for location-based sorting.
Media & entertainment catalogs
Search across media metadata and assets (images, video, audio) using multimodal and semantic capabilities for richer discovery.
Enterprise search & knowledge bases
Unify retrieval across private and public data sources, enabling RAG, conversational agents, and improved internal search experiences.
Integrations
JavaScript
Official SDK for JavaScript with code examples shown on the site.
PHP
PHP SDK listed among supported languages.
Python
Python SDK available for integration.
Ruby
Ruby SDK listed as a supported integration.
Java
Java SDK available.
Go
Go SDK listed for server-side integrations.
.NET
.NET SDK available for Microsoft stack integrations.
Dart
Dart SDK listed for integrations (e.g., Flutter).
Rust
Rust SDK available.
Swift
Swift SDK available for iOS/macOS apps.
Frontend frameworks
Instant Meilisearch and integrations for React, Vue, Angular, and server frameworks like Rails and Symfony.
Benefits
Limitations
No verified limitations are available.
Frequently Asked Questions
No verified FAQs are available.
Getting Started
- 1 Step 1: Get started via the Meilisearch website (Get started or Request a demo).
- 2 Step 2: Deploy Meilisearch quickly using plug-n-play presets (deploy in a matter of minutes).
- 3 Step 3: Integrate with your application using the REST API or official SDKs (examples provided for JavaScript and other languages) and add documents to indexes.
Support
Documentation
Official documentation and language SDK guides are listed on the site (JavaScript, PHP, Python, Ruby, Java, Go, .NET, Dart, Rust, Swift).
GitHub
Open source repository for issues, PRs, and contributions.
Discord
Community chat for questions and discussion.
Request a demo
Option to request a custom demo via the website.
API
Documentation and SDKs for JavaScript, PHP, Python, Ruby, Java, Go, .NET, Dart, Rust, Swift are listed on the site.
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