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Above AI Agents for Proactive Insider 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
corecyber.io ↗	71 match 2 shared topics	CoreCyber - Your DIY for AI Cyber Risk Management	en	information-and-network-security	robotsllmsaihumans	emailphone	none
balbix.com ↗	70 match 2 shared topics	Autonomous Cyber Risk Management \| SAFE	en	information-and-network-security WordPress	robotsllmsaihumans	emailphone	partial · 8
cortexprotect.com ↗	69 match 2 shared topics	Cortex Protect — XDR & SIEM for AI Agents	en	information-and-network-security	robotsllmsaihumans	emailphone	none
threatvec.com ↗	69 match 2 shared topics	ThreatVec — AI Agent Security Posture Management	en	information-and-network-security	robotsllmsaihumans	emailphone	none
blackkitehq.com ↗	69 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 ↗	69 match 2 shared topics	Black Kite \| Standards-Based Third-Party Cyber Risk Management	United States~ en	information-and-network-security	robots llmsaihumans	emailphone	none
blackkitesec.com ↗	69 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 ↗	69 match 2 shared topics	Wisr AI \| Autonomous Risk Management at Machine Speed	en	information-and-network-security	robotsllmsaihumans	emailphone	none
onezania.com ↗	68 match 2 shared topics	AI Compliance Agents for Security & Risk \| Zania	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
openscopeai.com ↗	68 match 2 shared topics	Safety controls for AI agents	en	artificial-intelligence	robots llmsaihumans	emailphone	none
ferentin.ai ↗	67 match 2 shared topics	Ferentin \| The Trust Layer for AI Agents	en	information-and-network-security	robotsllmsaihumans	emailphone	none
ferentin.com ↗	67 match 2 shared topics	Ferentin \| The Trust Layer for AI Agents	en	information-and-network-security	robots llmsaihumans	emailphone	none
aam.wtf ↗	67 match 2 shared topics	AAM - Safe AI Agents You Can Trust	en	information-and-network-security	robotsllmsaihumans	emailphone	none
astrix.security ↗	67 match 2 shared topics	Identity Security for AI Agents & NHIs \| Astrix Security	en	information-and-network-security WordPress	robots llmsaihumans	emailphone	none
openape.ai ↗	67 match 2 shared topics	OpenApe — Human Security for AI Agents	en	information-and-network-security	robotsllmsaihumans	emailphone	none
blackswantechnologies.com ↗	67 match 2 shared topics	AI, Cybersecurity & Risk Management Consulting \| Black Swan Technologies%	en	artificial-intelligence WordPress	robotsllmsaihumans	email phone	none
accurics.website ↗	66 match 2 shared topics	Vulnerability and exposure management \| Cloud and AI security \| Tenable®	en	artificial-intelligence Drupal	robotsllmsaihumans	emailphone	none
accurics.site ↗	66 match 2 shared topics	Vulnerability and exposure management \| Cloud and AI security \| Tenable®	en	artificial-intelligence Drupal	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.