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Sentricus | Enterprise Cybersecurity & Risk Management — 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
blackswantechnologies.com ↗	76 match 2 shared topics	AI, Cybersecurity & Risk Management Consulting \| Black Swan Technologies%	en	artificial-intelligence WordPress	robotsllmsaihumans	email phone	none
1-pro.net ↗	73 match 2 shared topics	1PRO Solutions - AI-Powered Cybersecurity & Innovation \| Enterprise Security Services	United States~ en	information-and-network-security	robotsllmsaihumans	email phone	none
blacknode.cloud ↗	72 match 2 shared topics	Black Node — AI Cybersecurity & Automation	en	information-and-network-security	robotsllmsaihumans	email phone	none
blackmatterdefense.com ↗	72 match 2 shared topics	Black Matter Defense — Enterprise AI Security Consultancy	en	information-and-network-security	robotsllmsaihumans	emailphone	none
corecyber.io ↗	72 match 2 shared topics	CoreCyber - Your DIY for AI Cyber Risk Management	en	information-and-network-security	robotsllmsaihumans	emailphone	none
avepoint.com ↗	71 match 2 shared topics	AI-Ready Data Security & Governance for Enterprise \| AvePoint	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
blackkitesec.com ↗	71 match 2 shared topics	Black Kite \| Standards-Based Third-Party Cyber Risk Management	United States~ en	information-and-network-security	robots llmsaihumans	emailphone	none
blackkiteinc.com ↗	71 match 2 shared topics	Black Kite \| Standards-Based Third-Party Cyber Risk Management	United States~ en	information-and-network-security	robots llmsaihumans	emailphone	none
blackkitehq.com ↗	71 match 2 shared topics	Black Kite \| Standards-Based Third-Party Cyber Risk Management	United States~ en	information-and-network-security	robots llmsaihumans	emailphone	none
thinktech.ai ↗	71 match 2 shared topics	Wisr AI \| Autonomous Risk Management at Machine Speed	en	information-and-network-security	robotsllmsaihumans	emailphone	none
1pw.ai ↗	70 match 2 shared topics	1PW.AI \| Enterprise Password Security & Bitcoin Solutions	en	information-and-network-security	robotsllmsaihumans	emailphone	partial · 8
spirko.net ↗	70 match 2 shared topics	Spirko Enterprises, LLC \| Digital Products, Automation & Cybersecurity	en	information-and-network-security	robotsllmsaihumans	emailphone	none
mchugh.ai ↗	70 match 2 shared topics	Jeremy McHugh, D.Sc. — Cybersecurity & AI	United States~ en	artificial-intelligence	robotsllmsaihumans	emailphone	none
cooties.io ↗	70 match 2 shared topics	Cooties@Blog \| Cybersecurity & AI Research Insights	en	information-and-network-security	robotsllmsaihumans	emailphone	none
abstract.engineering ↗	70 match 2 shared topics	Seif.ai - Continuous cybersecurity across all assets	en	information-and-network-security	robotsllmsaihumans	emailphone	none
luongnv.com ↗	69 match 2 shared topics	Luong Nguyen \| AI & Cybersecurity Engineer	France~ en	information-and-network-security	robots llmsaihumans	emailphone	none
onezania.com ↗	69 match 2 shared topics	AI Compliance Agents for Security & Risk \| Zania	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
thezaraai.com ↗	69 match 2 shared topics	TheZaraAI — AI · Cybersecurity · Automation	en	artificial-intelligence Spree Commerce	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.