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Security Systems for the Modern Enterprise | Verkada — 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
onescopesecurity.tech ↗	100 match 2 shared topics	Security Systems for the Modern Enterprise \| Verkada	en	information-and-network-security	robotsllmsaihumans	emailphone	partial · 8
seyonis.com ↗	76 match 2 shared topics	Seyonis — Next-Generation Security for the Modern Enterprise	en	information-and-network-security	robotsllmsaihumans	emailphone	none
one-worxs.org ↗	73 match 2 shared topics	AI-Powered Security Systems for Modern Businesses \| OneWorxs	United States~ en	information-and-network-security WordPress	robotsllmsaihumans	email phone	none
gruve.ai ↗	72 match 2 shared topics	AI Security & Infrastructure for Enterprise \| Gruve	en	information-and-network-security WordPress	robots llmsaihumans	emailphone	none
gruveusa.com ↗	72 match 2 shared topics	AI Security & Infrastructure for Enterprise \| Gruve	en	information-and-network-security WordPress	robotsllmsaihumans	emailphone	none
seqrite.com ↗	71 match 2 shared topics	Seqrite: AI-Driven Enterprise Cybersecurity Solutions Company	en	information-and-network-security WordPress WooCommerce	robots llmsaihumans	emailphone	none
carterchurch.com ↗	71 match 2 shared topics	Carter Church - AI Systems for Security Operations	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
avepoint.com ↗	71 match 2 shared topics	AI-Ready Data Security & Governance for Enterprise \| AvePoint	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
mindfulaitech.com ↗	70 match 2 shared topics	Mindful Technologies — AI Security for the Agentic Enterprise	en	information-and-network-security	robotsllmsaihumans	emailphone	none
hp7.io ↗	70 match 2 shared topics	HP7 Security - AI-Powered Enterprise Cybersecurity	en	information-and-network-security	robotsllmsaihumans	email phone	none
sessera.ai ↗	70 match 2 shared topics	Sessera — Open-Source Enterprise Browser Security & AI Governance	en	information-and-network-security	robotsllmsaihumans	emailphone	partial · 8
nyedis.ai ↗	70 match 2 shared topics	Nyedis AI \| Enterprise AI Security & Governance Solutions	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
3sixtyai.com ↗	70 match 2 shared topics	3SixtyAI \| Intelligent Mobile Security Systems	en	artificial-intelligence WordPress	robotsllmsaihumans	emailphone	none
numyra-research.org ↗	69 match 2 shared topics	Numyra Security — The Security Layer for AI‑Driven Enterprises	en	information-and-network-security	robotsllmsaihumans	emailphone	none
certifiedaiaccess.ai ↗	69 match 2 shared topics	Certified AI Access - Enterprise AI Security	en	information-and-network-security	robotsllmsaihumans	email phone	none
kavryl.com ↗	69 match 2 shared topics	Kavryl Security \| Safe, Visible Enterprise AI Agents	en	information-and-network-security	robotsllmsaihumans	emailphone	partial · 8
1pw.ai ↗	69 match 2 shared topics	1PW.AI \| Enterprise Password Security & Bitcoin Solutions	en	information-and-network-security	robotsllmsaihumans	emailphone	partial · 8
qshield.app ↗	69 match 2 shared topics	QShield — Enterprise AI Agent Security Control Plane	en	information-and-network-security	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.