Meilisearch

Meilisearch

Fast, AI-powered search engine for developers

Overview

Meilisearch provides a fast and easy-to-integrate search engine for websites and applications. It focuses on helping developers and tech teams create search experiences that return relevant results quickly. Its product blends traditional full-text search with AI-powered semantic search in a hybrid mode, improving accuracy for user queries. The engine can be embedded directly into apps or used as a cloud service, and it offers a freemium model—a free basic version with paid plans for advanced features and higher-scale needs. This cloud option includes a 14-day free trial. Meilisearch differentiates itself by offering a lightweight, developer-friendly search solution with built-in AI capabilities and flexible deployment (on-premises or cloud) to fit growing projects. Its goal is to help online platforms deliver fast, meaningful search experiences at scale.

About Meilisearch

Simplify's Rating
Why Meilisearch is rated
B
Rated B on Competitive Edge
Rated B on Growth Potential
Rated B on Differentiation

Industries

Enterprise Software

AI & Machine Learning

Company Size

11-50

Company Stage

Series A

Total Funding

$20.5M

Headquarters

Paris, France

Founded

2018

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Simplify's Take

What believers are saying

  • January 2026 analytics GA and 7x indexing gains improve Cloud adoption and retention.
  • April 2026 launch week delivered SAML, MFA, sharding, and replication for larger buyers.
  • Q3 2026 serverless indexes target new workloads and expand recurring Cloud revenue.

What critics are saying

  • Elastic shipped GPU-accelerated vector search in April 2026, pressuring Meilisearch on enterprise AI.
  • Enterprise features now gate sharding, replication, and SSO, risking open-source user conversion.
  • If cloud growth stalls, Meilisearch becomes a commodity API against Elasticsearch and Algolia.

What makes Meilisearch unique

  • Rust-native architecture underpins Meilisearch’s speed, safety, and open-source credibility.
  • March 2026 added distributed search, foreignKeys joins, and Chat UI across Cloud.
  • v1.38 stabilized HNSW vector storage, strengthening hybrid search for AI workflows.

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Funding

Total Funding

$20.5M

Below

Industry Average

Funded Over

2 Rounds

Series A funding typically happens when a startup has a product and some customers, and now needs funding to scale. This money is usually used to grow the team, expand marketing, and improve the product. Venture capital firms are frequently the main investors here.
Series A Funding Comparison
Meet Average

Industry standards

$15M
$8.2M
Discord
$15M
Canva
$15M
Meilisearch
$30M
Kalshi

Benefits

4 day work week

Equipment

Remote friendly

PTO

Parental leave

Health insurance

Team gatherings

Mental health support

Stock options

Career development

Growth & Insights and Company News

Headcount

6 month growth

0%

1 year growth

4%

2 year growth

4%
Neomoti
Jul 24th, 2026
Introducing Hojiinet: A next-gen full-stack job search engine.

Introducing Hojiinet: A next-gen full-stack job search engine. * blog * introducing Hojiinet: A next-gen full-stack job search engine. Fragmented data and basic keyword searches are major challenges in regional job markets. Job seekers frequently run into irrelevant search results, while crawling and indexing systems often face scale issues. To address this, NeoMoti developed Hojiinet: a modern, end-to-end full-stack platform built from the ground up to redefine job matching. The architecture consists of a highly responsive Next.js frontend, styled with shadcn/ui and TailwindCSS, combined with a robust FastAPI backend. Under the hood, Hojiinet utilizes a custom, Tor-proxy-rotated crawling framework that aggregates vacancies from multiple portals securely and reliably without trigger-blocking issues. Data ingestion triggers instant synchronization events. Leveraging RabbitMQ as an event broker, the system processes updates in real time. NeoMoti integrated a 384-dimensional vector embedding model (all-MiniLM-L6-v2) alongside Meilisearch's hybrid search engine, matching candidates to job opportunities based on both precise keyword lookups and semantic intent. By combining modern frontend patterns with asynchronous event-driven pipelines, Hojiinet delivers an exceptionally fast, fully localized, and responsive job-finding experience. It serves as a flagship demonstration of NeoMoti's capabilities in building real-world, scalable AI & full-stack applications.

Meilisearch
Jul 21st, 2026
Meilisearch vs. Manticore: Use cases, features, pricing, & more.

Meilisearch vs. Manticore: Use cases, features, pricing, & more. Compare Meilisearch and Manticore across performance, scalability, features, and ease of use. Learn the strengths of each platform and choose the right search engine for your needs. Meilisearch and Manticore Search are among the best full-text search engines around, great for your high-performance, scalable needs. However, chances are that only one of these solutions will be the right one for you. Choosing between the two is about finding the search engine that fits your needs, team, and growth plans. This means comparing their use cases, features, pricing, and more to help you make a confident choice. In this guide, Meilisearch'll introduce both tools, highlight their key features, and discuss real-world use cases that show what makes each stand out. You'll also get a clear look at pricing and weighing the pros and cons of both. What is Meilisearch? Meilisearch is an open-source search engine built for flexibility and speed, outperforming Elasticsearch in many cases. It delivers fast, typo-tolerant results in less than 50 milliseconds, making it appealing for web and mobile applications. With minimal configuration, developers can get up and running faster while still benefiting from features such as relevance tuning, filtering, and multilingual support. Best for: Startups, small- to medium-sized projects, and teams prioritizing rapid implementation and user-friendly search experiences. Meilisearch: pros and cons. Before choosing a search solution, it helps to look beyond feature lists and see how a tool performs in the real world. Here's how Meilisearch performs, based on real user feedback from platforms like G2. Meilisearch pros. * Easy to use: Users often comment that Meilisearch is easy to use, and the setup process is pretty straightforward, saving them a lot of time. * Responsive customer support: Support is very responsive, and users generally have a good experience with the team, noting they're quick to respond and helpful. * Seamless integrations: Reviewers value Meilisearch's integrations, which positively impact the developer experience. Meilisearch cons. * Limited advanced features: Some users noted that Meilisearch could be more sophisticated, with additional features such as index management. * Cost issues: Recent pricing changes have users concerned, saying it might not feel cost-effective for those with large indexes but lower usage. * Limited number of query words: A search query must involve no more than ten words; any more will be ignored. What is Manticore Search? Manticore Search is an open-source search engine built as a continuation of Sphinx, improving its functionality with full-text search and real-time analytics. Combining traditional SQL-like querying with powerful search, it's a flexible option for developers who need more control over indexing and ranking algorithms. Best for: Large-scale projects and teams that need advanced customization, SQL familiarity, and high-performance querying at scale. Manticore Search: pros and cons. Manticore is a powerful and flexible solution but it does come with a few disadvantages. Manticore pros. * Advanced customization: Offers deep control over ranking, filtering, and search behavior. * SQL-like querying: Familiar syntax for developers with database experience, simplifying adoption and complex queries. * Real-time indexing: Enables fast data updates without significant delays. Manticore cons. * Steep learning curve: Manticore Search is more challenging for beginners compared to other tools. * Complex setup: Initial configuration and tuning can be time-consuming. * Documentation gaps: Some users find resources harder to navigate and less beginner-friendly. What are the use cases of Meilisearch and Manticore Search? Meilisearch is used for fast, user-facing search experiences where simplicity, typo tolerance, and quick implementation matter most. Meanwhile, Manticore is primarily used for complex, large-scale search and analytics workloads that require high performance and deep customization. This table will clarify the differences between the two: This breakdown highlights the distinction between the two tools. Meilisearch prioritizes simplicity and efficient search, while Manticore focuses on power and scale for more demanding systems. What are the key features of Meilisearch and Manticore Search? When comparing Meilisearch and Manticore Search, the difference comes down to the features they provide. Both offer robust search capabilities, but they prioritize very different developer and product needs. Meilisearch features. Meilisearch focuses on delivering an out-of-the-box user search experience, making it attractive for teams that want fast results with minimal setup: * Instant, typo-tolerant search: Offers a highly relevant search functionality that scales with your needs. Delivers relevant search results quickly, even with misspelled words. * Vector and hybrid search: Meilisearch's AI-powered hybrid search combines best-in-class full-text and semantic search features to create a top-notch search experience. Meanwhile, Meilisearch's vector search helps you enhance applications for image, video, and audio search, product recommendations for e-commerce platforms, and intuitive Q&A interactions. Vector search improves relevance in search results, provides more personalized user experiences, and handles all unstructured data. * Zero-config relevance tuning: Smart defaults mean you get high-quality search results without too much manual tweaking. Beyond these, Meilisearch offers built-in features like synonyms, faceted search, and ranking rules that are easy to configure. Its lightweight architecture and quick deployment make it ideal for rapid prototyping and production use alike. Manticore Search features. Manticore is mostly designed for advanced use cases where flexibility and performance at scale are critical: * SQL-like query language: Enables complex queries using familiar syntax. * Real-time indexing: Supports fast ingestion and querying of continuously updating data. * Distributed architecture: Handles large datasets and scales across multiple nodes. In addition, Manticore offers advanced full-text search capabilities, granular control over ranking, and support for complex filtering and aggregations, making it a strong choice for data-heavy environments. Overall, Meilisearch wins over Manticore in ease of use, onboarding speed, and delivering a polished search experience without requiring deep expertise. How much do Meilisearch and Manticore Search cost? While both tools are open-source at their core, their cost structures diverge when you consider hosting, scalability, and managed services. Meilisearch pricing. Meilisearch follows a freemium plus managed cloud model, giving teams the flexibility they need to meet their goals: * Open-source (self-hosted): Free to use, with full core features. Ideal for developers who want complete control. * Cloud (usage-based): Starts at $30/month; useful for teams that want simple pricing to launch fast. * Cloud (resource-based plans): For apps that need dedicated performance at any scale, this plan starts at $23/month. * Enterprise: Custom pricing with dedicated infrastructure, SLA, and compliance features. Manticore pricing. Manticore takes a more traditional approach, with fewer built-in paid tiers: * Open-source: Completely free to use and self-host, with no licensing fees. * Managed/cloud options: Available via third-party providers or custom setups, so costs vary by infrastructure. * Enterprise support: Optional paid support or consulting, depending on the vendor and deployment. Manticore's costs are mostly tied to infrastructure (servers, storage, DevOps time) rather than per-query pricing, whereas Meilisearch is typically driven by search volume, stored documents, and infrastructure usage. What kind of API client libraries do Meilisearch and Manticore Search have? When it comes to integrations, both Meilisearch and Manticore offer a solid range of SDKs and APIs. In short, Meilisearch provides official SDKs and REST APIs designed for quick integration, while Manticore offers a wide range of clients, making it versatile for optimizing complex systems. Meilisearch stands out with its modern SDK ecosystem and ease of integration. Manticore, however, excels in backend flexibility, offering more language coverage for enterprise environments. Meilisearch vs Manticore: How to make the right choice? If you're building a user-facing application, then Meilisearch is a better starting point. Its ease of implementation, instant search capabilities, and minimal configuration let teams ship quickly without deep search expertise. On the other hand, Manticore is better suited to applications that handle large datasets or analytics-heavy workloads. Why Meilisearch stands out for teams that need fast, flexible search. Meilisearch allows teams to launch quickly without deep expertise, thanks to its instant, typo-tolerant search and zero-config setup. Its clear APIs, fast performance, and built-in relevance tuning make it ideal for delivering polished search experiences with minimal effort. Maya shin. Head of Marketing @ Meilisearch

Meilisearch
Oct 30th, 2023
Introducing Teams - Meilisearch Cloud

Meilisearch Cloud introduces the all-new Teams feature.

Meilisearch
Jul 5th, 2023
Vector storage is coming to Meilisearch to empower search through AI

Meilisearch is thrilled to release vector storage for Meilisearch to bring fast, relevant search to AI-powered applications.

Meilisearch
Mar 20th, 2023
Minoru Osuka: POV of a main language contributor

This year, Meilisearch has launched Meilisearch's very first contributors program: the Meilistars.

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