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Lucid Computing - Provable trust infrastructure for frontier AI — 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
cryptonqr.com ↗	73 match 2 shared topics	CryptonQR — Trust Infrastructure for the AI Era	en	information-and-network-security Paddle	robotsllmsaihumans	emailphone	none
mcpverify.net ↗	72 match 2 shared topics	MCPVerify — Trust Infrastructure for AI Tools	en	information-and-network-security	robotsllmsaihumans	emailphone	none
trusera.dev ↗	72 match 2 shared topics	Trusera — Trust Infrastructure for the Agentic Era	en	information-and-network-security	robotsllmsaihumans	emailphone	none
csspki.com ↗	72 match 2 shared topics	Trust Infrastructure for AI & Machines - Keyfactor	en	information-and-network-security WordPress	robots llmsaihumans	emailphone	none
l6verify.com ↗	70 match 2 shared topics	Bits & Blocks — Privacy Infrastructure for the AI Era	en	information-and-network-security	robotsllmsaihumans	emailphone	none
qryptix.dev ↗	70 match 2 shared topics	Qryptix - Privacy & AI Infrastructure	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
trygruve.com ↗	70 match 2 shared topics	AI Security & Infrastructure for Enterprise \| Gruve	en	information-and-network-security WordPress	robotsllmsaihumans	emailphone	none
gruveusa.com ↗	70 match 2 shared topics	AI Security & Infrastructure for Enterprise \| Gruve	en	information-and-network-security WordPress	robotsllmsaihumans	emailphone	none
gruve.ai ↗	70 match 2 shared topics	AI Security & Infrastructure for Enterprise \| Gruve	en	information-and-network-security WordPress	robots llmsaihumans	emailphone	none
netsim.dev ↗	70 match 2 shared topics	NetSim Labs \| Secure Infrastructure for AI Agents	en	information-and-network-security	robotsllmsaihumans	emailphone	none
trusthouse.ai ↗	69 match 2 shared topics	TrustHouse — Enterprise AI Trust Infrastructure	en	information-and-network-security	robotsllmsaihumans	emailphone	none
brainworkflow.com ↗	69 match 2 shared topics	BrainWorkflow \| Zero-Trust AI Infrastructure	en	artificial-intelligence	robotsllmsaihumans	emailphone	partial · 8
qsecorp.org ↗	68 match 2 shared topics	Quantum Resilience Infrastructure for the AI Era — QSE	en	information-and-network-security	robots llmsaihumans	emailphone	none
black-diamond.tech ↗	68 match 2 shared topics	Black Diamond Labs — Runtime Safety Infrastructure for AI Agents	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
8peaks.io ↗	67 match 2 shared topics	8peaks \| Sovereign AI Infrastructure & Zero Trust AI Platform \| EU AI Act Compliance	Belgium~ en	artificial-intelligence	robotsllmsaihumans	emailphone	none
tryarhasi.com ↗	67 match 2 shared topics	Arhasi \| The AI Trust Infrastructure\| Intelligence Security \| Decision Provenance \| AI Decision Infrastructure	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
robostai.com ↗	67 match 2 shared topics	Robost - Secure Your Enterprise AI Infrastructure	en	information-and-network-security	robotsllmsaihumans	emailphone	none
thevelocityroom.com ↗	67 match 2 shared topics	The Velocity Room \| AI Infrastructure & Security Community	en	artificial-intelligence HubSpot	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.