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ICARIT2026 | Applied Research & Information Technologies — 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
agades.tech ↗	70 match 2 shared topics	Agades Technologies — Independent AI Research Initiative	en	information-and-network-security	robotsllmsaihumans	emailphone	none
cryptovoip.tech ↗	68 match 2 shared topics	CryptoVoip Technologies \| AI, Security & Innovation	en	information-and-network-security	robotsllmsaihumans	emailphone	none
cryptovoips.com ↗	68 match 2 shared topics	CryptoVoip Technologies \| AI, Security & Innovation	en	information-and-network-security	robotsllmsaihumans	emailphone	none
ahmed-k.com ↗	66 match 2 shared topics	Ahmed Khan - Applied ML Security Researcher	en	information-and-network-security	robotsllmsaihumans	email phone	none
jaredlog.com ↗	66 match 2 shared topics	Jared Evans — Information Security & AI Practice	en	information-and-network-security	robotsllmsaihumans	emailphone	none
stem-resources.co ↗	66 match 2 shared topics	STEMR Inc. \| AI Cybersecurity & Research Solutions	Colombia en	information-and-network-security	robotsllmsaihumans	emailphone	none
agenthacker.ai ↗	66 match 2 shared topics	AgentHacker \| AI Adversarial Research & Security Engineering	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
jaegerists.com ↗	66 match 2 shared topics	Jaegerists \| AI, Cryptography & Privacy Research	en	information-and-network-security	robotsllmsaihumans	emailphone	partial · 8
skylabus.tech ↗	66 match 2 shared topics	Gianni Perez \| Cyber Threat Analyst & Researcher	en	information-and-network-security	robotsllmsaihumans	emailphone	none
jaesonbooker.com ↗	66 match 2 shared topics	Jaeson Booker – AI Safety Research & Engineering	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
cyberlab.biz ↗	66 match 2 shared topics	CyberLab — AI Security Research Lab	en	information-and-network-security	robotsllmsaihumans	emailphone	none
adriansosa.net ↗	66 match 2 shared topics	Adrian Sosa \| Technology Consultant & Digital Strategist	en	artificial-intelligence	robotsllmsaihumans	emailphone	partial · 8
agomez.info ↗	66 match 2 shared topics	Andrés Gómez Sarmiento \| Technologist & Social Scientist	en	information-and-network-security	robotsllmsaihumans	emailphone	partial · 8
4xfast.com ↗	66 match 2 shared topics	4xfast \| AI-Powered Cybersecurity & Technology Solutions	en	information-and-network-security	robotsllmsaihumans	email phone	none
agenticmachinetech.com ↗	65 match 2 shared topics	Principal-Led Cybersecurity and Security Operations Consulting \| Agentic Machine Technologies	United States~ en	information-and-network-security	robotsllmsaihumans	emailphone	partial · 8
aggicorp.com ↗	65 match 2 shared topics	Aggi Technologies — AI Responsibility for Regulated Industries	en	artificial-intelligence WordPress	robotsllmsaihumans	emailphone	none
medullainstitute.org ↗	65 match 2 shared topics	Medulla AI Security Research Institute	United States~ en	artificial-intelligence	robots llmsaihumans	emailphone	partial · 8
mend.io ↗	65 match 2 shared topics	Mend.io \| Application Security and AI Security, Unified	United States~ en	information-and-network-security WordPress	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.