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Sipsjava.com – Projects and blog of Milton Smith — 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
cyx.ai ↗	65 match 2 shared topics	CYX.AI – Empowering Your AI Projects with Security and Privacy	en	artificial-intelligence WordPress	robotsllmsaihumans	emailphone	none
drbunyaminkisacik.com ↗	63 match 2 shared topics	drbunyaminkisacik.com – Transforming smiles with precision.	en	information-and-network-security WordPress WooCommerce	robotsllmsaihumans	emailphone	partial · 8
aidaproject.net ↗	63 match 2 shared topics	AIDA Project – Redefining how AI-driven cyber defence operates	en	artificial-intelligence WordPress WooCommerce	robotsllmsaihumans	emailphone	none
aiconfidence-assessment.com ↗	63 match 2 shared topics	AI Confidence – Privacy Checker	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
ai4it.net ↗	62 match 2 shared topics	AI in IT and Cybersecurity Blog for Enhanced Work \| ai4it	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
trmlabs.com ↗	62 match 2 shared topics	TRM Labs \| Agents and intelligence to fight crime	US~ en	information-and-network-security	robots llmsaihumans	emailphone	none
identity-sentinel.com ↗	62 match 2 shared topics	Identity-Sentinel – Discussing IAM and AI Security	en	information-and-network-security WordPress	robotsllmsaihumans	emailphone	none
mirandus.io ↗	62 match 2 shared topics	Mirandus B.V. - At the nexus of ML, data and security	en	information-and-network-security	robotsllmsaihumans	emailphone	none
1id.com ↗	62 match 2 shared topics	1id.com — Hardware-Backed Identity for AI Agents & Relying Parties	en	information-and-network-security	robots llmsaihumans	emailphone	none
agentfacts.ai ↗	62 match 2 shared topics	AgentFacts — Trust and Verify AI Agents	en	information-and-network-security	robots llms aihumans	emailphone	partial · 8
cleverraccoon.ai ↗	62 match 2 shared topics	Clever Raccoon.ai – Pocket Pen‑Tester	en	information-and-network-security	robotsllmsaihumans	emailphone	none
aaasecure.ai ↗	62 match 2 shared topics	AaaSecure – Compliance at the speed of AI	en	information-and-network-security WordPress	robotsllmsaihumans	emailphone	partial · 8
oxprompt.com ↗	62 match 2 shared topics	Oxprompt - AI and LLM Professional Security Tools	en	information-and-network-security Adobe Experience Manager	robotsllmsaihumans	emailphone	none
triarii.ai ↗	62 match 2 shared topics	Triarii – AI systems for cybersecurity professionals.	en	artificial-intelligence WordPress WooCommerce	robotsllmsaihumans	emailphone	none
miragesecurity.ai ↗	62 match 2 shared topics	Mirage Security - AI Vishing Simulations and Simulator	en	information-and-network-security	robotsllmsaihumans	emailphone	none
miragesecure.com ↗	62 match 2 shared topics	Mirage Security - AI Vishing Simulations and Simulator	en	information-and-network-security	robotsllmsaihumans	emailphone	none
stopahack.com ↗	62 match 2 shared topics	StopAHack.com \| Military-Born AI Security & Cybersecurity	US~ en	information-and-network-security	robots llmsaihumans	emailphone	none
dora-cra-nis2.com ↗	61 match 2 shared topics	Discover DORA, NIS2 and CRA	en	information-and-network-security WordPress	robotsllmsaihumans	email phone	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.