Sinequa

https://www.sinequa.com

Hybrid retrieval combining dense vector + keyword + graph traversal + multimodal. Agentic RAG grounding AI agents in internal knowledge. SOC 2 / ISO 27001 compliant.

At a glance

Type
Hybrid retrieval + agentic RAG
Tier
T1
Created
2024-11
Latest release
not applicable — not OSS
License
not applicable — not OSS
GitHub
not applicable — no GitHub repo
Pricing
Enterprise only
Funding
Acquired by ChapsVision · 2024-11

Taxonomy

storage
vector
retrieval
similarity
persistence
long-term
update
extraction
unit
document
governance
auditable
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

Strong in regulated industries (defense, finance, life sciences) — compliance and security posture is the differentiator.

Cons

Heavyweight enterprise install; smaller developer community; AI features lag pure-play AI search products.

Claims & capabilities

SPARK Matrix Leader Q4 2025; Gartner-cited for powering AI assistants.

Technical surface

API surface
REST, SDK: JS/TS
Backend storage
custom
Deployment
Both
Embedding model
locked
Multi-tenancy
On-premises / private-cloud tenant / fully-managed SaaS — customer choice; Azure-region selectable
MCP
no first-party MCP adapter published as of 2026-05; community connectors may exist.
A2A
no Google A2A (Agent2Agent) integration documented as of 2026-05.
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

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

  • 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.

  • 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.

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