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DeepTeam - The LLM Red Teaming Framework — 18 websites ranked by shared content topics, category and on-page relevance.

Each result shows its full tech stack, contacts and AI-policy — not just a name · Browse all sites in Artificial Intelligence →

Domain	Match	Title	Country/Lang	Category	AI files	Contact	AI-protection
mind-gard.com ↗	69 match 2 shared topics	Mindgard - Automated AI Red Teaming & Security Testing	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
mindgard.ai ↗	69 match 2 shared topics	Mindgard - Automated AI Red Teaming & Security Testing	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
cytadel.ai ↗	69 match 2 shared topics	Cytadel \| AI-Driven Autonomous Red Teaming Platform	United Kingdom~ en	artificial-intelligence	robotsllmsaihumans	emailphone	none
agentictrustframework.ai ↗	67 match 2 shared topics	Agentic Trust Framework \| AI Agent Governance Standard	en	information-and-network-security	robots llmsaihumans	emailphone	none
chimaukachukwu.com ↗	67 match 2 shared topics	Chima Ukachukwu \| AI Security Analyst & Red Teamer	United States~ en	information-and-network-security	robotsllmsaihumans	emailphone	none
agentreef.net ↗	66 match 2 shared topics	AgentReef - The Living Network for AI Agents	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
agentidentityregistry.org ↗	66 match 2 shared topics	AIR — Open Identity & Trust Framework for AI Agents	en	information-and-network-security	robotsllmsaihumans	emailphone	none
agentidentityregistry.com ↗	66 match 2 shared topics	AIR — Open Identity & Trust Framework for AI Agents	en	information-and-network-security	robotsllmsaihumans	emailphone	none
pakistanredteam.com ↗	66 match 2 shared topics	Pakistan Red Team \| AI-Powered Cyber Security Agency in Pakistan	en	information-and-network-security	robotsllmsaihumans	emailphone	none
p-sep.com ↗	66 match 2 shared topics	P-SEP: Framework for Responsible AI, Cybersecurity & Trust	en	information-and-network-security WordPress WooCommerce	robotsllmsaihumans	emailphone	none
chatsaif.com ↗	66 match 2 shared topics	ChatSAIF - Secure AI Framework	en	information-and-network-security	robotsllmsaihumans	emailphone	none
aicm.app ↗	65 match 2 shared topics	AI Controls Matrix (AICM v1.0.2) - Cloud Security Alliance AI Governance Framework	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
clawpatrol.dev ↗	65 match 2 shared topics	Claw Patrol - The security firewall for agents	en	information-and-network-security	robots llmsaihumans	emailphone	partial · 8
trampolyneai.com ↗	65 match 2 shared topics	AI Red-Teaming & Runtime Security Platform \| Trampolyne AI	en	information-and-network-security	robotsllmsaihumans	emailphone	none
hiline-motorsports.com ↗	65 match 2 shared topics	MDLabCA — Offensive Security, Red Team, Threat Intelligence & AI-Powered Detection	en	information-and-network-security	robotsllmsaihumans	emailphone	partial · 8
eaglesfield.ai ↗	65 match 2 shared topics	Eaglesfield Adversarial AI \| LLM Security & AI Safety Testing	United Kingdom~ en	artificial-intelligence	robotsllmsaihumans	email phone	none
advisedly.ai ↗	64 match 2 shared topics	Advisedly — Tear Down the Cyber and Compliance Paywall	en	information-and-network-security	robotsllmsaihumans	emailphone	none
0xclaw.dev ↗	64 match 2 shared topics	Local AI pentesting for security teams	en	information-and-network-security	robots llmsaihumans	emailphone	partial · 7

How the match score works

Each match is a 0–100 similarity score — the higher it is, the more two sites resemble one another. It’s computed automatically from our own crawl data (never from what a site says about itself) by combining several independent signals, so a high score means several of them point the same way:

shared topics how many of the same fine‑grained content topics (IAB sub‑categories) both sites cover — the main signal.
same category whether they sit in the same business / industry category.
content & title how closely their titles and page descriptions line up in wording and meaning.

No single signal decides the result — they’re blended together. Treat the score as a way to rank candidates rather than an absolute percentage; the chips on each result show which signals contributed.