Search Engine Optimisation & Intelligence · B2B SaaS Provider
Meilisearch
Open-source search engine with managed cloud search infrastructure.
Available information varies by company and source.
Profile record updated:
Company facts
- Official name
- Meili
- Entity type
- COMPANY
- Founded
- 2018
- Headquarters
- 52, boulevard de Sebastopol 75003 Paris, France
- Company size
- 10–49
- Market cluster / sector
- Search Engine Optimisation & Intelligence
- Market role
- B2B SaaS Provider
- Official website
- meilisearch.com
What Meilisearch does
Meilisearch uses an open-core style distribution model centred on free adoption of its open-source search engine and monetisation through a managed cloud service. The free self-hosted product lowers adoption friction for developers and product teams, while the hosted offer captures recurring revenue from customers that want production-grade infrastructure, scaling, observability, support, and advanced capabilities without operational overhead.
Category differentiation
Meilisearch is not a consumer search engine or an ad measurement platform. It is developer-facing search infrastructure used by businesses to power search inside their own products.
Strategic context
AI-supported assessment from the existing company research; distinguish interpretation from sourced facts.
Meilisearch is a French software company that develops an API-first search engine for websites and applications. Its core product is distributed as open-source software for self-hosted deployments, while Meilisearch Cloud provides a managed version with hosted infrastructure, scaling, monitoring, analytics, and enterprise support. The platform is used to build on-site search and discovery features across web and mobile products, including full-text, semantic, vector, hybrid, and conversational retrieval use cases. The company makes money by converting open-source adoption into paid cloud usage and enterprise-grade service plans. Its direct customers are developers, engineering teams, product teams, startups, and larger enterprises that need search infrastructure without building and maintaining it internally. Relative to broader search infrastructure competitors, Meilisearch positions itself around deployment control, developer usability, and a simplified implementation model.
Company news briefing
Briefing updated:
Following its expansion into medical-specific RAG applications to minimise AI hallucinations, Meilisearch is further embedding its hybrid search capabilities within developer ecosystems. The introduction of tools like Larameili allows for the direct management of document chunks and vector embeddings within the Laravel framework, reinforcing the company's role in decentralised search infrastructure. These developments solidify Meilisearch’s strategy of providing specialised, self-hostable alternatives for grounding generative AI models in trusted clinical and proprietary datasets.
Business model & monetisation
Meilisearch operates a dual monetisation model: free open-source self-hosting for adoption and paid managed cloud services for production use. Commercial revenue comes from Meilisearch Cloud through subscription and resource or usage-based pricing tied to infrastructure consumption such as CPU, RAM, storage, and search volume, with higher-tier enterprise plans adding custom pricing, SLAs, support, and advanced features.
- Managed cloud search platform
- SaaS subscription and resource-based pricing
- Enterprise cloud plans
- Custom contracts with SLA and support
- Open-source self-hosted engine
- Free adoption funnel
Products & capabilities
No products with linked sources are available in this view.
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Enterprise search, observability and security software built on Elasticsearch.
Hosted search and discovery infrastructure for digital products.
AI search platform with enterprise web search and research APIs.
Enterprise software for search, discovery, and AI-powered knowledge experiences.
Open-source vector database and managed cloud for AI retrieval.
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Recent recorded signals
Dates refer to the source publication. Older entries are historical context, not evidence of a new event.
Larameili: Laravel models for Meilisearch chunked search
Infrastructure · Recorded impact score: 1/5
A technical tutorial introduces Larameili, a PHP package that maps Meilisearch indexes to Active Record–style models in Laravel so developers can store and query document chunks (including vector embeddings) directly in Meilisearch. The article covers installation via Composer, index/model configuration (searchable, filterable fields, and embedders), syncing settings, bulk import and update methods, hybrid keyword+vector search with a semantic weighting parameter, pagination returning Laravel paginator objects, and resolving related Eloquent records from hits.
- The Larameili package can be installed via Composer: composer require edulazaro/larameili.
- Larameili gives a Meilisearch index an Active Record model so chunks can be queried like Eloquent models without being stored in the database.
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Questions about Meilisearch
What is Meilisearch?
Meilisearch is a developer-focused search platform offering an open-source search engine and a managed cloud version for embedding fast, relevant search into websites and applications.
Who uses Meilisearch?
It is used by developers, engineering teams, product teams, startups, and enterprises that need search and discovery features inside digital products.
How does Meilisearch make money?
It makes money through Meilisearch Cloud via subscription and usage or resource-based pricing, plus enterprise plans with support and SLA commitments.
Sources & coverage
This profile uses public, official and technically observable information. Missing information does not prove that a product or relationship does not exist. The list below does not imply that every profile statement has been verified.
15 publicly documented primary sources and citations linked across the market graph.
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