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Reclaim Protocol - Cryptographic Verification for Identity, Education, Employment & Travel — 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
tryreclaimdemo.com ↗	100 match 1 shared topics	Reclaim Protocol - Cryptographic Verification for Identity, Education, Employment & Travel	en	information-and-network-security	robotsllmsaihumans	emailphone	none
leronetwork.app ↗	74 match 1 shared topics	Lero Network \| Cryptographic Verification Protocol	en	information-and-network-security	robotsllmsaihumans	emailphone	none
truedatalabs.com ↗	70 match 1 shared topics	Universal data verification protocol – True Data Labs	en	information-and-network-security	robotsllmsaihumans	emailphone	none
truztcube.com ↗	70 match 1 shared topics	Truztcube – Identity Verification, eKYC & Authentication-as-a-Service for Africa	en	information-and-network-security	robotsllmsaihumans	emailphone	none
idverix.com ↗	70 match 1 shared topics	ID Verifx — Identity Verification On-Chain	en	information-and-network-security	robotsllmsaihumans	emailphone	none
idchecker.com ↗	70 match 1 shared topics	Identity Verification - Mitek	en	information-and-network-security Drupal	robotsllmsaihumans	emailphone	none
mccidentity.com ↗	69 match 1 shared topics	MCC IDENTITY – Biometric Identity Verification for Government & Enterprises	en	information-and-network-security	robotsllmsaihumans	emailphone	none
allveratad.com ↗	69 match 1 shared topics	Veratad: Age Verification \| Identity Verification \| Fraud Prevention	en	information-and-network-security	robotsllmsaihumans	emailphone	none
idverificationhub.com ↗	69 match 1 shared topics	idVerificationHub - Enterprise Identity Verification Platform	en	information-and-network-security	robotsllmsaihumans	emailphone	none
ledgerprove.com ↗	69 match 1 shared topics	LedgerProve — Cryptographic SBOM Verification	en	information-and-network-security	robotsllmsaihumans	emailphone	partial · 4
identt.com ↗	69 match 1 shared topics	Identity proofing and age verification – IDENTT	en	information-and-network-security WordPress	robotsllmsaihumans	emailphone	none
heylia.com.br ↗	69 match 1 shared topics	Identity Verification — GlobalID Systems	Brazil en	information-and-network-security	robotsllmsaihumans	emailphone	none
focusverify.com ↗	69 match 1 shared topics	Focus Verify - Identity Verification Solutions	en	information-and-network-security	robotsllmsaihumans	emailphone	none
id3technologies.com ↗	68 match 1 shared topics	id3 Technologies – Secure Identity & Document Verification	France~ en	information-and-network-security	robotsllmsaihumans	emailphone	none
truesthuman.com ↗	68 match 1 shared topics	Truest Human — Identity Verification with DKBA	en	information-and-network-security	robotsllmsaihumans	emailphone	none
btobbes.com ↗	68 match 1 shared topics	Btobbes - Identity Verification & Fraud Systems	en	information-and-network-security	robotsllmsaihumans	emailphone	none
idanalyzer.com ↗	68 match 1 shared topics	ID Analyzer - Identity Verification API & KYC Solutions \| Document OCR, Biometric & AML	en	information-and-network-security	robotsllmsaihumans	emailphone	none
idrabbit.com ↗	68 match 1 shared topics	idrabbit \| Next-Gen Identity Verification	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.