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AuditML — Verifiable Trust Layer for AI Transparency — 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
integrous-evidence.com ↗	71 match 2 shared topics	Verifiable Trust for Digital Evidence	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
prufoldlabs.ai ↗	70 match 2 shared topics	Prufold Labs - The Trust Layer for the Autonomous Economy	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
vorim.ai ↗	70 match 2 shared topics	Vorim AI — Agent Identity and Trust Layer for AI Systems	en	information-and-network-security	robots llmsaihumans	emailphone	none
mygentic.ai ↗	70 match 2 shared topics	CELLO — The Trust Layer for Agent-to-Agent Communication	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
vortalis.ai ↗	69 match 2 shared topics	Vortalis \| The trust layer for AI agents in regulated industries	United Kingdom~ en	information-and-network-security	robotsllmsaihumans	emailphone	none
intinuous.com ↗	69 match 2 shared topics	Intinuous \| The verifiable identity layer for a generative world	en	information-and-network-security	robotsllmsaihumans	emailphone	none
livic.ai ↗	68 match 2 shared topics	Livic AI – Autonomous Trust & Security Layer for AI Agents	en	information-and-network-security	robotsllmsaihumans	emailphone	none
athenyx.ai ↗	68 match 2 shared topics	Athenyx — The Safety Layer for Autonomous AI Agents	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
protopia.ai ↗	68 match 2 shared topics	Protopia AI — The Inference Privacy Layer for AI Factories - Protopia	en	artificial-intelligence WordPress	robotsllmsaihumans	emailphone	none
six-sov.com ↗	67 match 2 shared topics	SIX — Sovereign Inference Exchange \| Verifiable AI Infrastructure	en	artificial-intelligence Spree Commerce	robotsllmsaihumans	emailphone	none
protegolayers.com ↗	67 match 2 shared topics	Agent Safety Layer — On-chain Policy Enforcement for AI Agents	en	information-and-network-security	robotsllmsaihumans	emailphone	none
provenlog.com ↗	67 match 2 shared topics	ProvenLog — Tamper-evident audit trails for AI agents	en	information-and-network-security	robotsllmsaihumans	emailphone	none
protostars.ai ↗	67 match 2 shared topics	Protostars.ai — AI Trust Infrastructure for EU Cyber Resilience Act	en	information-and-network-security	robotsllmsaihumans	emailphone	none
nectotech.com ↗	66 match 2 shared topics	Necto — Secure Infrastructure for AI Agents	Sweden~ en	information-and-network-security	robotsllmsaihumans	emailphone	partial · 8
cryptonqr.com ↗	66 match 2 shared topics	CryptonQR — Trust Infrastructure for the AI Era	en	information-and-network-security Paddle	robotsllmsaihumans	emailphone	none
attestlog.org ↗	66 match 2 shared topics	AttestLog \| Digital Provenance, File Integrity, and Transparency Log Proofs	en	information-and-network-security	robots llmsaihumans	emailphone	none
interposesecurity.com ↗	66 match 2 shared topics	Interpose Security — A control layer for enterprise AI	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
attestmcp.com ↗	66 match 2 shared topics	AttestMCP — Compliance Evidence for AI Agent Memory	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.