SWIRL
by Swirl Search · Federated enterprise search and MCP layer that leaves data in place
BenchRank score
Screenshots of SWIRL
Homepage
Overview
SWIRL is a knowledge layer that runs in your own tenant and queries connected systems live instead of copying them into an index. It federates one search across 150+ sources, ranks and de-duplicates the results, and can produce cited RAG answers using any LLM, including on-prem models. Agents reach the same results through its MCP server or REST API.
- Best for
- Regulated enterprises wanting AI search over existing systems without copying data to a new index
- Pricing
- Annual platform licence: Departmental $24,000/year, Business $72,000/year and Enterprise from $150,000/year, plus a $12,000 60-90 day pilot credited to a first contract; the Semantic Cache add-on and OEM licensing (from $60,000/year plus revenue share) are priced separately.
- Runs on
- macOSSelf-hosted
Strengths and trade-offs
Strengths
- Searches source systems in place - no second index or vector database
- 150+ connectors, including M365, Salesforce, iManage and Snowflake
- First-class MCP server and REST API for agent access
- Runs in your own tenant, with on-prem and air-gapped options
Trade-offs
- Canonical answers and pinning sit in the Semantic Cache add-on, sold apart
- Annual licence only, from $24K/year; no free or self-serve tier
- You supply the LLM and the infrastructure it runs on
- Full connector library and analytics start at the $72K Business edition
How SWIRL markets itself
A structured read of the promise, proof and page design on SWIRL’s captured homepage.
Homepage capture
“The private knowledge layer for enterprise AI.”
- Angle: Category creation
- Hero: Product screenshot
Pricing
Published plans and prices from SWIRL’s own pricing page.
How this score is made up
Each dimension is scored out of 100 and combined into the headline score using fixed weights.
MCP support
Whether an agent can drive the product through the Model Context Protocol, and how much setup that takes.
API quality
Public API surface: machine-readable spec, official SDKs, documented auth, errors, rate limits and versioning.
Documentation
Publicly reachable docs — coverage, freshness, code samples and machine readability.
Agent friendliness
How readable the site is to an automated client: llms.txt, structured data, server-rendered content, crawler access.
Pricing transparency
Whether real prices are published, self-serve signup exists, and usage costs are knowable without a sales call.
Changelog
A public, dated record of what shipped and when — the clearest signal that a product is still alive.
Marketing site structure
Whether the site answers a buyer's questions: clear positioning, the pages that matter, and accessibility.
Page speed
How fast the site loads for real visitors: Chrome UX Report 75th-percentile LCP, INP and CLS, with a Lighthouse mobile run standing in where a site has too little traffic for field data.
Operational trust
Status page and incident history, security disclosure, compliance and data-processing documentation.
Measured, but not part of the score
Useful to know, but not a mark for or against the product — so these do not affect the ranking.
Openness
Source availability, self-hosting, data export and open standards. Scored and shown, but not part of the composite — paid SaaS is not worse for being paid SaaS.
Maintenance
Release cadence and repository activity. Scored and shown, but not part of the composite — it is only measurable for open repositories.
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Where this comes from
The SWIRL pages BenchRank reads when it scores the product — its documentation, release notes, status and security pages, and its repository where there is one.
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