Coveo

https://www.coveo.com

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.

Active · Verified 2026-10-27 · fresh as of 2026-10-27 · 43 cited facts, 3 with a third-party source · 1 recorded change · Suggest a correction

At a glance

Tier
T1
Created
2005 third-party fix
Latest release
not applicable — not OSS fix
License
not applicable — not OSS fix
GitHub
not applicable — no GitHub repo fix
Pricing
Enterprise only vendor fix
Freshness
2026-10-27 fix
Layer
agent-infra repo fix
Licensing
commercial vendor fix
Deployment locus
cloud vendor fix
Platform vs product
platform vendor fix

When to use

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

Anti-fit: not for SMB / consumer use cases

Pros & cons

Pros

Mature enterprise search with strong AI ranking and personalization; long-running customer base in commerce + support.

Cons

Closed product; less developer-API-friendly than newer entrants; pricing tied to indexed-asset volume.

Claims & capabilities

Relevance Generative Answering (RGA) models.

Technical surface

API surface
REST, SDK: JS/TS, Atomic
Backend storage
custom
Deployment
Managed-only
Embedding model
locked
Multi-tenancy
Logical multi-tenancy on AWS — dedicated Coveo Index per customer for full data segmentation
MCP
yes — hosted Coveo MCP Server connecting AI agents (ChatGPT, Claude, Copilot) to Coveo retrieval
A2A
no Google A2A (Agent2Agent) integration documented as of 2026-05.
OpenTelemetry
no first-party OpenTelemetry exporter documented; standard logs/metrics typically available.

Compare Coveo with…

Similar systems

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

  • Glean T1

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

  • Clarivate T1

    Bibliographic metadata curation (Web of Science, Derwent, Cortellis). Human editorial governance + journal-deindexing. Memory-adjacent — included as a curated-knowledge baseline.

  • 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.

  • Meilisearch T2

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

  • Mindbreeze InSpire T2

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

  • SearchUnify T1

    Agentic enterprise search with Knowbler — quality checks via the KCS (Knowledge-Centered Service) standard. Most explicit governance features in the segment.

Sources (42 cited facts, 3 third-party)

Each fact links to the page it came from; the badge says who published it (how to read sources).

What changed

Changes to this record's lifecycle, licence, release, pricing and hosting facts, from the catalog's git history. Subscribe (Atom)

  1. 2026-10-27
    • MCP support first recorded as “yes — hosted Coveo MCP Server connecting AI agents (ChatGPT, Claude, Copilot) to Coveo retrieval” source
    #274

Related systems

References (1)

  • Model Context Protocol (MCP spec) depends on at runtime — RAG-as-a-Service for AWS (Dec 2025) via hosted MCP server grounding Amazon Bedrock agents in enterprise knowledge.