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Nexguards alternatives & similar sites

NexGuards | AI Social Engineering and Cybersecurity Awareness Platform — 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
jungleriver.xyz ↗	75 match 2 shared topics	Gamified Cybersecurity Awareness Training Platform \| Drip⁷	en	information-and-network-security	robotsllmsaihumans	emailphone	none
godrip7.com ↗	75 match 2 shared topics	Cybersecurity Awareness Training Platform \| Drip⁷	en	information-and-network-security	robotsllmsaihumans	emailphone	none
vishin.ai ↗	73 match 2 shared topics	Vishin.ai - Vishing Security Awareness Platform	en	information-and-network-security	robotsllmsaihumans	emailphone	none
cybr.ai ↗	73 match 2 shared topics	CYBR \| Security Awareness Training For The Next Generation	en	information-and-network-security Wix	robots llmsaihumans	emailphone	none
ctrlsec.io ↗	72 match 2 shared topics	CtrlSec — AI-Powered Cybersecurity Platform	India~ en	information-and-network-security	robotsllmsaihumans	emailphone	none
rhymtech.com ↗	71 match 2 shared topics	AI-Powered Cybersecurity Platform \| RHYM Technologies	en	information-and-network-security	robotsllmsaihumans	email phone	none
gneiss-group.com ↗	71 match 2 shared topics	Gneiss Group \| AI Security Awareness Training	en	information-and-network-security	robotsllmsaihumans	emailphone	none
kindssecurity.com ↗	71 match 2 shared topics	Kinds Security \| AI-Powered Security Awareness Training	en	information-and-network-security	robots llmsaihumans	emailphone	none
deltapinglabs.com ↗	71 match 2 shared topics	DeltaPingLabs \| AI Protocol and Security Engineering	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
cybrcon.com ↗	70 match 2 shared topics	Cybrcon — AI Governance & Cybersecurity Compliance Engineering	en	information-and-network-security	robotsllmsaihumans	emailphone	none
natecrisler.com ↗	70 match 2 shared topics	Nate Crisler \| Principal AI Security Architect \| Platform Engineering & AI Infrastructure	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
vraust.ai ↗	70 match 2 shared topics	Vraust · AI Fraud Detection & Social Engineering Defense	en	information-and-network-security	robots llmsaihumans	emailphone	none
agenthacker.ai ↗	70 match 2 shared topics	AgentHacker \| AI Adversarial Research & Security Engineering	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
ai-cs.tech ↗	70 match 2 shared topics	ai-cs.tech - AI-Powered Cybersecurity Automation Platform	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
ricardgardella.com ↗	70 match 2 shared topics	Ricard Gardella — Senior AI Engineer & Cybersecurity Specialist	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
beginwithendor.com ↗	70 match 2 shared topics	Endor Labs \| AI-Native Application Security Platform	United States~ en	information-and-network-security	robotsllmsaihumans	emailphone	none
demoendor.com ↗	70 match 2 shared topics	Endor Labs \| AI-Native Application Security Platform	United States~ en	information-and-network-security	robotsllmsaihumans	emailphone	none
defagent.io ↗	70 match 2 shared topics	DefAgent \| Military-Grade AI Cybersecurity Platform	United States~ en	artificial-intelligence	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.