Meilisearch

https://www.meilisearch.com

Semantic + hybrid search GA (2025). Automatic embedding generation + caching via OpenAI / HuggingFace / Ollama. Multi-modal (text + images); hybrid rank fusion; conversational RAG built in.

At a glance

Type
Open-source semantic + hybrid search
Tier
T2
Created
2018
Latest release
not applicable — not OSS
License
not applicable — not OSS
GitHub
not applicable — no GitHub repo
Pricing
Free + paid
Funding
Series A · 2022-10

Taxonomy

storage
vector
retrieval
similarity
persistence
long-term
update
overwrite
unit
document
governance
inspectable
conflict
n/a

When to use

Optimised for: enterprise connectors + entitlements + governance + RAG-grounding

Anti-fit: not for SMB / consumer use cases

Pros & cons

Pros

Open-source typo-tolerant search; vector layer added without losing keyword speed; lightweight ops.

Cons

Smaller corpus scale ceiling than Elastic; AI / ranking features less mature.

Claims & capabilities

Open source (MIT) + Meilisearch Cloud.

Technical surface

API surface
REST, SDK: JS, Python, PHP, Go, Ruby, Java, .NET, Swift, Rust
Backend storage
custom (LMDB-backed engine, Rust)
Deployment
Both
Embedding model
multiple supported
Multi-tenancy
namespace
MCP
via community port
A2A
not supported
OpenTelemetry
no first-party OpenTelemetry exporter documented; standard logs/metrics typically available.

Similar systems

Other enterprise-search adjacencies in the catalog, ranked by inbound references.

  • Algolia (NeuralSearch) T1

    NeuralSearch combines vector + keyword via neural hashing — compresses to 1/10th size while retaining 99% info. AI-powered personalisation + recommendations.

  • Clarivate T1

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  • Coveo T1

    RAG-as-a-Service for AWS (Dec 2025) via hosted MCP server grounding Amazon Bedrock agents in enterprise knowledge. Passage retrieval + answer generation + ranked search + fetch in one API.

  • Glean T1

    Enterprise search with 100+ connectors. Personalised per-user knowledge graph. No governance layer.

  • Lucidworks Conversational Q&A AI Agent T1

    Enterprise Q&A agent powered by Luci patent-pending ultra-precise RAG. Embeds on product detail pages; consumes technical PDFs, spec sheets, images, tables, charts, graphs and product manuals. Maintains session history for multi-turn follow-ups; refuses out-of-scope queries via prompt-injection guard.

  • Mindbreeze InSpire T2

    Hybrid keyword + vector retrieval with entitlement-aware filtering. Unified enterprise knowledge graph linking documents, tickets, records. RAG prompt orchestration built in.

Related systems

References (1)

Row last verified 2026-05-14. Catalog data is CC-BY-4.0 — see how to read this.