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SEALISON · Cryptographic proof layer for AI logs — 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
agentreceipts.ai ↗	72 match 2 shared topics	Agent Receipts — cryptographic audit trails for AI agents \| Agent Receipts	en	information-and-network-security	robots llmsaihumans	emailphone	none
agentmark.dev ↗	72 match 2 shared topics	agentmark — cryptographic provenance for AI-generated code	en	artificial-intelligence	robotsllmsaihumans	emailphone	partial · 8
agentoath.ai ↗	71 match 2 shared topics	AgentOath — Cryptographic Trust for AI Agents	en	information-and-network-security	robotsllmsaihumans	emailphone	none
agent-provenance.org ↗	70 match 2 shared topics	Agent Provenance \| Proof Layer for Agent-Readable Systems	en	information-and-network-security	robots llmsaihumans	emailphone	none
agentpki.dev ↗	70 match 2 shared topics	AgentPKI — cryptographic identity for AI agents on the public internet	en	information-and-network-security	robotsllmsaihumans	emailphone	none
agenticrypt.com ↗	70 match 2 shared topics	Agenticrypt — Proof of Intent Gateway for AI Agents	en	information-and-network-security	robotsllmsaihumans	emailphone	none
advanced-consulting.london ↗	70 match 2 shared topics	ZKAP \| Cryptographic Verification of Formalized Rules for AI Systems	en	information-and-network-security	robots llmsaihumans	email phone	none
agentpin.org ↗	69 match 2 shared topics	AgentPin — Domain-anchored cryptographic identity for AI agents	en	information-and-network-security	robotsllmsaihumans	emailphone	none
agentpin.net ↗	69 match 2 shared topics	AgentPin — Domain-anchored cryptographic identity for AI agents	en	information-and-network-security	robotsllmsaihumans	emailphone	none
agentpin.dev ↗	69 match 2 shared topics	AgentPin — Domain-anchored cryptographic identity for AI agents	en	information-and-network-security	robotsllmsaihumans	emailphone	none
agentlookup.ai ↗	68 match 2 shared topics	AgentLookup — The Identity Layer for AI Agents	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
schemapin.com ↗	68 match 2 shared topics	SchemaPin — Cryptographic Tool Verification for AI Agents & MCP Servers	en	information-and-network-security	robotsllmsaihumans	emailphone	none
agentseal.ai ↗	68 match 2 shared topics	AgentSeal — The Trust Layer for AI Agents	en	information-and-network-security Spree Commerce	robotsllmsaihumans	emailphone	none
agentidp.dev ↗	68 match 2 shared topics	AgentIDP — The Identity Layer for AI Agents	en	information-and-network-security	robotsllmsaihumans	emailphone	partial · 8
agentrux.com ↗	68 match 2 shared topics	AgenTrux — The Secure Communication Layer for AI Agents	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
0byte.tech ↗	67 match 2 shared topics	0byte - The Origin Protocol for AI Content	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
mcpverify.net ↗	67 match 2 shared topics	MCPVerify — Trust Infrastructure for AI Tools	en	information-and-network-security	robotsllmsaihumans	emailphone	none
agentscan.tech ↗	66 match 2 shared topics	AgentScan — The trust layer for autonomous agents	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.