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Verifyhuman alternatives & similar sites

VerifyHuman — The trust layer for the internet — 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
accessopenorigins.com ↗	76 match 1 shared topics	OpenOrigins - Digital Media Verification and Trust Layer for the Internet	en	information-and-network-security	robots llmsaihumans	emailphone	none
qrauth.io ↗	75 match 1 shared topics	QRAuth — The trust layer for QR-based identity	en	information-and-network-security	robotsllmsaihumans	emailphone	partial · 8
tunnelmind.ai ↗	71 match 1 shared topics	TunnelMind — Trust Attestation for the Agentic Internet	en	information-and-network-security	robots llmsaihumans	emailphone	none
acalna.com ↗	70 match 1 shared topics	Taeste: Proof of Life for the Internet	Canada~ en	information-and-network-security	robots llmsaihumans	emailphone	partial · 8
blockchaintrustcollective.com ↗	69 match 1 shared topics	The Blockchain Trust Collective - The Trust Layer of Web3	en	information-and-network-security	robotsllmsaihumans	emailphone	none
blockcontentseal.com ↗	68 match 1 shared topics	BlockContentSeal — The Authenticity Layer for Digital Publishing	en	information-and-network-security	robotsllmsaihumans	emailphone	none
pzxmtoken.com ↗	68 match 1 shared topics	PZXM Network — The Cryptographic Foundation for Human Longevity	en	information-and-network-security	robotsllmsaihumans	emailphone	partial · 8
anonyx.network ↗	67 match 1 shared topics	Anonyx Network — Institutional Privacy Layer for Canton	en	information-and-network-security	robotsllmsaihumans	emailphone	none
venation.digital ↗	67 match 1 shared topics	Venation - The evidence layer for security and compliance teams	en	information-and-network-security	robots llmsaihumans	emailphone	none
verifyone.org ↗	67 match 1 shared topics	VerifyOne.org - Trusted Verification for Any Product	en	information-and-network-security	robotsllmsaihumans	emailphone	none
kycilo.com ↗	67 match 1 shared topics	Kycilo — International KYC verification	en	information-and-network-security	robotsllmsaihumans	emailphone	partial · 8
rjonetworks.com ↗	67 match 1 shared topics	RJO Networks \| Modern Defense for the Age of Intelligence	en	information-and-network-security	robotsllmsaihumans	emailphone	none
mcptrust.dev ↗	66 match 1 shared topics	MCPTrust — Lockfile for MCP servers	en	information-and-network-security	robotsllmsaihumans	emailphone	none
veri-fi.org ↗	66 match 1 shared topics	veri-fi — Trust has a half-life. We do the math.	en	information-and-network-security	robotsllmsaihumans	emailphone	partial · 8
cryptostorm.com ↗	66 match 1 shared topics	cryptostorm - The VPN service provider for the truly paranoid	en	information-and-network-security	robotsllmsaihumans	emailphone	none
5bsd.org ↗	66 match 1 shared topics	5BSD — Private Compute With Verifiable Integrity	en	information-and-network-security	robotsllmsaihumans	emailphone	none
4signature.com ↗	66 match 1 shared topics	Creating Trust In A Digital World	en	information-and-network-security WordPress	robotsllmsaihumans	email phone	none
veritrustglobal.com ↗	66 match 1 shared topics	VeriTrust Global - Trusted Verification for Modern Records	Singapore~ 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.