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Simonlecomte alternatives & similar sites

Simon Le Comte - — 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
dpia.ai ↗	63 match 2 shared topics	DPIA.ai - Automated GDPR Compliance	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
convosecai.com ↗	63 match 2 shared topics	ConvoSec AI \| Leading AI & Cybersecurity Company	en	information-and-network-security	robotsllmsaihumans	emailphone	none
jamescalhoun.co ↗	63 match 2 shared topics	James Calhoun - CyberSec, AI Systems & Compliance \| Mojave Corp	Colombia en	information-and-network-security	robotsllmsaihumans	emailphone	none
krcrichton.com ↗	63 match 2 shared topics	Kyle Crichton	en	information-and-network-security	robotsllmsaihumans	emailphone	none
heytrustero.com ↗	62 match 2 shared topics	Trustero is Advanced AI for Security and Compliance Teams	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
layr8.io ↗	62 match 2 shared topics	Layr8 — The identity and communication layer for agents	en	information-and-network-security	robots llmsaihumans	emailphone	none
vitruviuscyber.com ↗	62 match 2 shared topics	Vitruvius Cyber Systems \| AI Security and Zero Trust Advisory	en	information-and-network-security	robots llmsaihumans	emailphone	none
sibhi.com ↗	62 match 2 shared topics	Sibhi S \| Machine Learning & Quantum Systems \| VIT Chennai	India~ en	artificial-intelligence	robots llmsaihumans	emailphone	partial · 8
avepoint.com ↗	62 match 2 shared topics	AI-Ready Data Security & Governance for Enterprise \| AvePoint	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
buzzery.ch ↗	62 match 2 shared topics	DQ0 - Privacy-Preserving Machine Learning	Switzerland en	artificial-intelligence	robotsllmsaihumans	emailphone	none
devrand.org ↗	62 match 2 shared topics	Gavin Black, PhD — AI/ML Security	en	information-and-network-security	robotsllmsaihumans	emailphone	none
siemrules.com ↗	62 match 2 shared topics	SIEM Rules \| Threat-intelligence-driven detection engineering	en	information-and-network-security	robotsllmsaihumans	emailphone	none
gravitational.co ↗	62 match 2 shared topics	Teleport: Unified Identity Securing Classic & AI Infrastructure \| Teleport	Colombia en	information-and-network-security	robotsllmsaihumans	emailphone	none
1-pro.net ↗	62 match 2 shared topics	1PRO Solutions - AI-Powered Cybersecurity & Innovation \| Enterprise Security Services	United States~ en	information-and-network-security	robotsllmsaihumans	email phone	none
365architect.com ↗	62 match 2 shared topics	Securing Enterprise Architecture in the AI Era \| 365 Architect	United States~ en	information-and-network-security	robotsllmsaihumans	emailphone	none
alejandroalmeida.org ↗	62 match 2 shared topics	Alejandro Almeida \| Computer Engineer & AI Researcher	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
vitational.com ↗	62 match 2 shared topics	Teleport: Unified Identity Securing Classic & AI Infrastructure \| Teleport	United States~ en	information-and-network-security	robotsllmsaihumans	emailphone	none
1bigthink.com ↗	62 match 2 shared topics	1bigthink \| Secure Your Compliance Today	United States~ en	artificial-intelligence Squarespace Magento	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.