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Digital Fraud Prevention & Risk-Based Authentication | Sift — 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
sift.com ↗	100 match 2 shared topics	Digital Fraud Prevention & Risk-Based Authentication \| Sift	en	information-and-network-security WordPress WooCommerce	robots llmsaihumans	emailphone	partial · 8
siftscience.com ↗	100 match 2 shared topics	Digital Fraud Prevention & Risk-Based Authentication \| Sift	en	information-and-network-security WordPress WooCommerce	robots llmsaihumans	emailphone	partial · 8
americanverification.com ↗	67 match 2 shared topics	American Verification — Autograph Authentication	en	information-and-network-security	robotsllmsaihumans	emailphone	none
idtsoa.com ↗	66 match 2 shared topics	Data Breach Prevention \| Data Breach Resolution	en	information-and-network-security WordPress	robotsllmsaihumans	emailphone	none
idmerit.com ↗	66 match 2 shared topics	Global Identity Verification Solutions Provider via API \| IDMERIT	United States~ en	information-and-network-security WordPress	robotsllmsaihumans	email phone	none
proffid.com ↗	64 match 2 shared topics	Proffid - Secure Digital Identity Platform for Business & Employee Management \| Proffid	en	information-and-network-security	robotsllmsaihumans	emailphone	none
3ilion.com ↗	64 match 2 shared topics	3ilion - Register, Establish and Protect Your Digital Identity.	en	information-and-network-security WordPress WooCommerce	robotsllmsaihumans	emailphone	none
trivexplatform.com ↗	64 match 2 shared topics	Trivex \| Sealed Validation & Compliance Records	en	information-and-network-security	robotsllmsaihumans	emailphone	none
identitydot.com ↗	64 match 2 shared topics	IdentityDot \| Brand Protection & Monitoring	en	information-and-network-security	robotsllmsaihumans	emailphone	none
identityillustrated.com ↗	64 match 2 shared topics	Identity Illustrated by Smile ID	en	information-and-network-security	robotsllmsaihumans	emailphone	partial · 1
brustview.com ↗	63 match 2 shared topics	BrustView \| Digital Compliance & Transparency	en	information-and-network-security	robotsllmsaihumans	emailphone	none
formentor.co.uk ↗	63 match 2 shared topics	Navigating Governance, Risk & Compliance with Confidence	United Kingdom en	information-and-network-security WordPress	robotsllmsaihumans	email phone	none
simplifiedid.com ↗	63 match 2 shared topics	Home - Simplified.ID	en	information-and-network-security WordPress	robotsllmsaihumans	email phone	none
simplified-id.com ↗	63 match 2 shared topics	Home - Simplified.ID	en	information-and-network-security WordPress	robotsllmsaihumans	email phone	none
k2grc.com ↗	62 match 2 shared topics	K2 GRC \| Governance, Risk & Compliance Platform	en	information-and-network-security	robotsllmsaihumans	email phone	none
truvern.com ↗	62 match 2 shared topics	Truvern – Board-defensible third-party risk governance \| Truvern	en	information-and-network-security	robotsllmsaihumans	emailphone	none
trustcredo.com ↗	62 match 2 shared topics	Credo Screening — AML & Sanctions Screening Platform	en	information-and-network-security	robotsllmsaihumans	emailphone	none
igatheater.com ↗	62 match 2 shared topics	Hydden Playbill \| End Identity Governance Theatre - Make User Access Reviews Real	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.