Fleuret agentic AI pentesting vs Hoxhunt Respond

Quick answer

Fleuret agentic AI pentesting (Émile multi-agent orchestrator for web apps and APIs) (Fleuret (FLEURET AI SAS)) and Hoxhunt Respond (automated phishing incident response) (Hoxhunt) 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 Hoxhunt Respond (automated phishing incident response) (Hoxhunt) 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)Hoxhunt Respond (automated phishing incident response)
Vendor Fleuret (FLEURET AI SAS)Hoxhunt
HQ France · EuropeFinland · Europe
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.Finnish human-risk platform whose Respond module automatically investigates every employee-reported email, groups related reports into one campaign incident, suppresses safe and duplicate reports, and removes confirmed malicious messages from all affected inboxes without waiting for an analyst.
Frameworks (vendor-stated) ——
Frameworks (vendor-claimed) ——
Capabilities / tasks pen test management, attack surface, vulnerability management, exposure managementphishing triage, email security, incident response, remediation
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 (per-employee quote after a scoping call)
Pricing model published-tiersquote
Primary source https://fleuret.ai/platformhttps://hoxhunt.com/product/phishing-email-incident-response-automation
Last checked 2026-10-202026-10-18
Official site https://fleuret.ai/https://hoxhunt.com/product/phishing-email-incident-response-automation

FAQ (from this dataset)

What is the difference between Fleuret agentic AI pentesting and Hoxhunt Respond?

Both are listed under Security. They share no task tags in this dataset. Fleuret agentic AI pentesting-only tasks: pen-test-management, attack-surface, vulnerability-management, exposure-management. Hoxhunt Respond-only tasks: phishing-triage, email-security, incident-response, remediation. 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. Hoxhunt Respond (automated phishing incident response): Not published (per-employee quote after a scoping call)

Where are Fleuret agentic AI pentesting and Hoxhunt Respond headquartered?

Fleuret agentic AI pentesting (Émile multi-agent orchestrator for web apps and APIs) publishes HQ in France. Hoxhunt Respond (automated phishing incident response) publishes HQ in Finland.

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 Hoxhunt Respond (automated phishing incident response). Open a pair page or the use-case table — this is not a ranking.

Use-case comparisons

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