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HackWednesday | AI Security Analysis for Cybersecurity Teams — 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 Information And Network Security →

Domain	Match	Title	Country/Lang	Category	AI files	Contact	AI-protection
heyekai.com ↗	73 match 2 shared topics	Ekai CoWork — Secure AI Co-Workers for Cybersecurity Teams	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
ai-security-consultant.ch ↗	73 match 2 shared topics	AI Security Consultant — Automated Cybersecurity for SMEs	Switzerland en	artificial-intelligence	robotsllmsaihumans	emailphone	none
360sec.com ↗	71 match 2 shared topics	AI-Powered Cybersecurity Services — MDR, Red Teaming & AI Security Testing \| 360 Security Group	United States~ en	information-and-network-security	robotsllmsaihumans	emailphone	none
vizazigroup.com ↗	71 match 2 shared topics	Vizazi Group Cybersecurity and AI Solutions \| Vizazi Group	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
vivesecurity.com ↗	71 match 2 shared topics	ViveSecurity - AI-Powered Cybersecurity Solutions	en	information-and-network-security	robotsllmsaihumans	emailphone	none
0xclaw.dev ↗	71 match 2 shared topics	Local AI pentesting for security teams	en	information-and-network-security	robots llmsaihumans	emailphone	partial · 7
vitruviuscyber.com ↗	70 match 2 shared topics	Vitruvius Cyber Systems \| AI Security and Zero Trust Advisory	en	information-and-network-security	robots llmsaihumans	emailphone	none
krishnac.com ↗	70 match 2 shared topics	Krishna C - Director, Cybersecurity x Agentic AI	United States~ en	artificial-intelligence	robotsllmsaihumans	emailphone	none
diem360.com ↗	70 match 2 shared topics	Diem360 \| AI-Powered Cybersecurity Intelligence	en	information-and-network-security	robotsllmsaihumans	emailphone	none
composedsecurity.com ↗	70 match 2 shared topics	Composed Security — Verified product security for AI engineering teams	en	information-and-network-security	robots llmsaihumans	emailphone	none
astrix.security ↗	70 match 2 shared topics	Identity Security for AI Agents & NHIs \| Astrix Security	en	information-and-network-security WordPress	robots llmsaihumans	emailphone	none
hexascan.app ↗	70 match 2 shared topics	HexaScan - AI based security analysis platform - Web & Server Security Audit Platform by BlazeHexa	en	information-and-network-security	robotsllmsaihumans	emailphone	none
1-pro.net ↗	69 match 2 shared topics	1PRO Solutions - AI-Powered Cybersecurity & Innovation \| Enterprise Security Services	United States~ en	information-and-network-security	robotsllmsaihumans	email phone	none
2thrivellc.com ↗	69 match 2 shared topics	Cyber Security and AI Consulting	en	information-and-network-security	robotsllmsaihumans	emailphone	none
kotelab.com ↗	69 match 2 shared topics	Kotelab — Turn Your CCTV Into an AI Security Analyst	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
compsimple.com ↗	69 match 2 shared topics	Compsimple — Federal Cybersecurity and AI Governance	en	information-and-network-security	robotsllmsaihumans	emailphone	none
hermesecurity.com ↗	69 match 2 shared topics	Hermes Security Solutions - Cybersecurity Offensive	en	information-and-network-security Webflow	robotsllmsaihumans	emailphone	none
connectwithsweetsecurity.com ↗	69 match 2 shared topics	Sweet Security: Cloud Security Built for Today's AI Era	en	information-and-network-security Webflow	robotsllmsaihumans	emailphone	none

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.