similar sites

Browse

Pricing AI Report

Tools

🚀Submit Your Site to AIPush your URL to AI search engines 🤖AI Crawler CheckerSee which AI bots your site blocks 🎯AI Readiness CheckerScore your site 0–100 for AI 🔗Backlink CheckerWho links to any site — free All tools →

Browse free →

Sites similar to samuelnellessen.com

Samuelnellessen alternatives & similar sites

Samuel Nellessen | AI Safety Research Engineer — 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
copeuccino.com ↗	72 match 2 shared topics	Dex-Xavier Copeland \| GRC Engineer & AI Safety Researcher	en	information-and-network-security	robotsllmsaihumans	emailphone	none
luongnv.com ↗	69 match 2 shared topics	Luong Nguyen \| AI & Cybersecurity Engineer	France~ en	information-and-network-security	robots llmsaihumans	emailphone	none
0xdkay.me ↗	69 match 2 shared topics	Dongkwan Kim \| Security Researcher	en	information-and-network-security	robotsllmsaihumans	emailphone	none
lampsec.dev ↗	68 match 2 shared topics	LAMPSEC — Autonomous AI Security Research	en	information-and-network-security	robotsllmsaihumans	emailphone	none
splunksurge.com ↗	68 match 2 shared topics	SURGe Security Research Team \| Splunk	en	information-and-network-security Adobe Experience Manager	robotsllmsaihumans	emailphone	none
0ximu.dev ↗	67 match 2 shared topics	0ximu \| Security Researcher	en	information-and-network-security	robotsllmsaihumans	emailphone	none
corgi-corp.com ↗	67 match 2 shared topics	Corgi Corp - Adversarial AI Research	en	artificial-intelligence Ghost	robotsllmsaihumans	emailphone	none
sprk3.com ↗	67 match 2 shared topics	SPR{K3 — ML Security Research	en	information-and-network-security	robotsllmsaihumans	emailphone	none
cooties.io ↗	66 match 2 shared topics	Cooties@Blog \| Cybersecurity & AI Research Insights	en	information-and-network-security	robotsllmsaihumans	emailphone	none
samilafrance.com ↗	66 match 2 shared topics	Sami Lafrance — Founding Engineer @ Ctrl+G	en	information-and-network-security	robotsllmsaihumans	emailphone	none
abai.wtf ↗	66 match 2 shared topics	Tom Abai \| Security Researcher	en	information-and-network-security	robotsllmsaihumans	emailphone	none
imsre.dev ↗	65 match 2 shared topics	Nate Crisler \| Principal AI Security Architect \| Platform Engineering & AI Infrastructure	en	artificial-intelligence	robots llmsaihumans	emailphone	partial · 8
samogunti.com ↗	65 match 2 shared topics	Samuel Ogunti, MBA \| AI & Cloud Security Architect	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
coreyalejandro.com ↗	64 match 2 shared topics	Corey Alejandro — AI Safety + Societal Impact Portfolio	en	artificial-intelligence	robotsllmsaihumans	emailphone	partial · 8
onlinecloudsec.com ↗	64 match 2 shared topics	Moshe Ferber \| Cloud Security Evangelist & AI Safety Expert	en	information-and-network-security	robotsllmsaihumans	emailphone	none
thiagogoncalves.com ↗	64 match 2 shared topics	Thiago Goncalves — Senior Engineer · AI Platform & Security · Builder-Operator	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
cooperraterink.com ↗	64 match 2 shared topics	Cooper Raterink	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
spotem.ai ↗	64 match 2 shared topics	AI Security Cameras & Surveillance \| AI CCTV Monitoring Solutions	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.