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DQ0 - Privacy-Preserving Machine Learning — 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
denizxk.com ↗	70 match 2 shared topics	Deniz Keskin - Lead Machine Learning Engineer	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
berryvilleiml.com ↗	69 match 2 shared topics	Berryville Institute of Machine Learning	en	artificial-intelligence WordPress	robotsllmsaihumans	emailphone	none
natalieisak.com ↗	69 match 2 shared topics	Natalie Isak \| Machine Learning Engineer & AI Safety Researcher	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
swarmnetwork.ai ↗	68 match 2 shared topics	World's 1st Privacy Preserving Oracle Layer Operated by Swarm Intelligence	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
fantasma.ai ↗	66 match 2 shared topics	Fantasma Privacy Guide	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
nborovits.com ↗	66 match 2 shared topics	Nemania Borovits \| Personal Website \| Researcher \| Data Scientist \| Privacy Engineering \| Data Governance \| Machine Learning Engineer \| Data Engineer \| Python \| Machine Learning \| Deep Learning \| NLP	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
zrotrustai.com ↗	66 match 2 shared topics	ZROTrust.AI - Privacy Evidence Layer for GenAI	en	information-and-network-security	robotsllmsaihumans	emailphone	none
1privacy.ai ↗	65 match 2 shared topics	1Privacy.ai — AI-first privacy. One tool for everything you need.	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
avalonprivacy.com ↗	65 match 2 shared topics	Avalon Privacy	en	information-and-network-security Squarespace Magento	robotsllmsaihumans	emailphone	partial · 13
harissmajlovic.com ↗	65 match 2 shared topics	Haris Smajlović — Privacy-Enhancing Computation	en	information-and-network-security	robotsllmsaihumans	emailphone	none
avalear.com ↗	64 match 2 shared topics	Avalear — Private AI for Regulated Work	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
hashmarksecurity.com ↗	64 match 2 shared topics	HashMark Security \| AI-Powered Privacy Compliance for Developers	en	information-and-network-security	robotsllmsaihumans	emailphone	none
lu-zhi.com ↗	64 match 2 shared topics	Zhi Lu \| Cryptography, Privacy Computing, and AI Security	en	information-and-network-security	robotsllmsaihumans	emailphone	none
base64fix.tech ↗	64 match 2 shared topics	Base64Fix.tech — Decode Base64 Safely with AI · Privacy-First Security Decoder	en	information-and-network-security	robotsllmsaihumans	emailphone	none
useintegral.com ↗	64 match 2 shared topics	Integral \| The Independent Privacy Layer for AI \| Integral	en	information-and-network-security	robotsllmsaihumans	emailphone	none
actoriss.com ↗	64 match 2 shared topics	ACTORISS - NHI-first Identity Governance for Humans, Machines & AI Agents	en	information-and-network-security	robotsllmsaihumans	emailphone	none
narpi.ai ↗	64 match 2 shared topics	Narpi Sovereign \| AI Privacy Readiness for regulated Canadian teams	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
csspki.com ↗	63 match 2 shared topics	Trust Infrastructure for AI & Machines - Keyfactor	en	information-and-network-security WordPress	robots llmsaihumans	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.