Fleuret agentic AI pentesting vs Ridge Security RidgeGen and RidgeBot

Quick answer

Fleuret agentic AI pentesting (Émile multi-agent orchestrator for web apps and APIs) (Fleuret (FLEURET AI SAS)) and Ridge Security RidgeGen (agentic AI red teaming) and RidgeBot (Ridge Security (Ridge Security, Inc.)) are both listed in the Security category of Agent Index.

They share no framework tags in our dataset.

This is not a ranking.

Fleuret agentic AI pentesting (Émile multi-agent orchestrator for web apps and APIs) (Fleuret (FLEURET AI SAS)) and Ridge Security RidgeGen (agentic AI red teaming) and RidgeBot (Ridge Security (Ridge Security, Inc.)) are both listed in the Security category of Agent Index. They share no framework tags in our dataset.

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Field Fleuret agentic AI pentesting (Émile multi-agent orchestrator for web apps and APIs)Ridge Security RidgeGen (agentic AI red teaming) and RidgeBot
Vendor Fleuret (FLEURET AI SAS)Ridge Security (Ridge Security, Inc.)
HQ France · EuropeUnited States · North America
Primary category SecuritySecurity
Also listed in SecuritySecurity
Summary Paris-based agentic pentesting platform in which the Émile orchestrator coordinates 12-60 specialist attack agents (auth bypass, IDOR, injection chains, business logic, privilege escalation) against web apps and APIs, reports only findings proven with a replayable proof of concept, and re-tests fixes, with EU-sovereign hosting.Offensive-security vendor from Milpitas, California. Its on-premises, model-agnostic RidgeGen agent does agentic AI red teaming: it reasons through multi-step attack chains to find business-logic and non-CVE risks, verifies every finding with reproducible exploit evidence, gives fix guidance and re-runs to confirm fixes. It sits alongside RidgeBot automated pentesting.
Frameworks (vendor-stated) ——
Frameworks (vendor-claimed) ——
Capabilities / tasks pen test management, attack surface, vulnerability management, exposure managementpen test management, attack surface, vulnerability management, exposure management
Pricing (as published) Published on fleuret.ai: free organisation plan (scanners only, 2 users, 10 repositories); one-off pentest EUR 4,000 per web app; contract covering every app on quote.Not published
Pricing model published-tiersquote
Primary source https://fleuret.ai/platformhttps://ridgesecurity.ai/ridgegen/
Last checked 2026-10-202026-10-19
Official site https://fleuret.ai/https://ridgesecurity.ai/ridgegen/

FAQ (from this dataset)

What is the difference between Fleuret agentic AI pentesting and Ridge Security RidgeGen and RidgeBot?

Both are listed under Security. Shared tasks: pen-test-management, attack-surface, vulnerability-management, exposure-management. Differences are from stored category and task tags, not a ranking.

Which one publishes pricing?

Fleuret agentic AI pentesting (Émile multi-agent orchestrator for web apps and APIs): Published on fleuret.ai: free organisation plan (scanners only, 2 users, 10 repositories); one-off pentest EUR 4,000 per web app; contract covering every app on quote. Ridge Security RidgeGen (agentic AI red teaming) and RidgeBot: Not published

Where are Fleuret agentic AI pentesting and Ridge Security RidgeGen and RidgeBot headquartered?

Fleuret agentic AI pentesting (Émile multi-agent orchestrator for web apps and APIs) publishes HQ in France. Ridge Security RidgeGen (agentic AI red teaming) and RidgeBot publishes HQ in United States.

Side-by-side data is generated from the open dataset. “Vendor-claimed” frameworks are as marketed by each vendor and not verified by Agent Index; framework tags indicate relevance, not certification. Request current quotes from each vendor before buying. This page does not rank or score vendors. Sponsored comparisons, if any, will be labelled.

Also in this use case

Other verified listings that share a task tag or use-case group with Fleuret agentic AI pentesting (Émile multi-agent orchestrator for web apps and APIs) or Ridge Security RidgeGen (agentic AI red teaming) and RidgeBot. Open a pair page or the use-case table — this is not a ranking.

Use-case comparisons

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