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GDDNA | Global Anti-Fraud Verification & AI Provenance Network — 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
aiproof.top ↗	68 match 2 shared topics	AI Security & Verification News - AI Proof	en	information-and-network-security	robotsllmsaihumans	emailphone	none
deeptrack.io ↗	66 match 2 shared topics	Deeptrack \| Enterprise Deepfake Detection & AI Content Verification	KE~ en	artificial-intelligence	robotsllmsaihumans	emailphone	none
getquyn.com ↗	66 match 2 shared topics	QYN — The Verification Layer	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
zoryxsolutionsllc.com ↗	66 match 2 shared topics	Zoryx Solutions LLC — Deterministic AI Verification & Validation	en	artificial-intelligence	robotsllmsaihumans	email phone	none
aashthaseva.info ↗	66 match 2 shared topics	Bharat Web Solution - Document Verification	en	information-and-network-security	robotsllmsaihumans	emailphone	none
docverify.app ↗	66 match 2 shared topics	AI Document Verification for Agents & APIs \| DocVerify	en	artificial-intelligence	robots llmsaihumans	emailphone	none
agenticprovenanceprotocol.com ↗	65 match 2 shared topics	Agentic Provenance Protocol	en	information-and-network-security	robots llmsaihumans	emailphone	none
gidaverify.com ↗	65 match 2 shared topics	GidaVerify — Trustless Verification	en	information-and-network-security	robotsllmsaihumans	emailphone	partial · 8
smsguard.ai ↗	65 match 2 shared topics	SMSGuard - Stop SMS Pumping Fraud \| Save Money on SMS Verification	en	artificial-intelligence	robotsllmsaihumans	emailphone	partial · 8
globeia.ai ↗	65 match 2 shared topics	Trustworthy Identity Verification Platform Enhanced Background Verification	en	information-and-network-security	robotsllmsaihumans	emailphone	none
fraudprotect.ai ↗	65 match 2 shared topics	AI Fraud Protect - Detect & Prevent Certification Fraud	en	information-and-network-security	robotsllmsaihumans	emailphone	none
zignsec.com ↗	65 match 2 shared topics	IDV solutions: Identity Verification - G2 Risk Solutions	en	information-and-network-security WordPress	robotsllmsaihumans	emailphone	none
advanced-consulting.london ↗	65 match 2 shared topics	ZKAP \| Cryptographic Verification of Formalized Rules for AI Systems	en	information-and-network-security	robots llmsaihumans	email phone	none
cyber-kyc.store ↗	65 match 2 shared topics	GPT / Claude KYC Verification — Pass in 5 Minutes \| KYCPass	en	information-and-network-security	robotsllmsaihumans	emailphone	partial · 8
agent-trust.org ↗	64 match 2 shared topics	Agent Trust — Trust Resolution and Verification Infrastructure for Autonomous Agents	en	artificial-intelligence	robots llmsaihumans	emailphone	none
getvouch.io ↗	64 match 2 shared topics	Vouch \| Identity, Employment & Social Verification Without Document Uploads	en	artificial-intelligence	robots llmsaihumans	emailphone	none
requestguard.com ↗	64 match 2 shared topics	RequestGuard — AI Bot Detection & Fraud Protection	en	information-and-network-security	robotsllmsaihumans	emailphone	none
sourceiq.info ↗	64 match 2 shared topics	SourceIQ — Content Provenance & Threat Intelligence	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.