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AI Data Loss Prevention | Blacksight AI — 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
blackfog.cloud ↗	67 match 2 shared topics	BlackFog AI Security for Data Exfiltration, Shadow AI and Ransomware Prevention	en	information-and-network-security WordPress WooCommerce	robotsllmsaihumans	emailphone	none
fense.ai ↗	66 match 2 shared topics	Fense.ai - Advanced E-commerce Fraud Detection and Prevention	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
blindinsight.com ↗	65 match 2 shared topics	Encrypted data analytics & AI — Blind Insight	en	artificial-intelligence	robots llmsaihumans	emailphone	none
incountry.com ↗	65 match 2 shared topics	Data residency and AI data protection - InCountry AgentCloak	en	artificial-intelligence WordPress	robotsllmsaihumans	emailphone	none
blockchainaifoundation.com ↗	65 match 2 shared topics	Blockchain AI Foundation — Data Sovereignty Through AI + Blockchain	en	information-and-network-security	robotsllmsaihumans	emailphone	none
mdnt.ai ↗	64 match 2 shared topics	Midnight Labs	en	information-and-network-security	robotsllmsaihumans	emailphone	none
dataofficer.eu ↗	64 match 2 shared topics	Dataofficer.eu: all-in-on data oversight for EU data regulations	European Union en	information-and-network-security WordPress	robotsllmsaihumans	email phone	none
blackwalltier.com ↗	64 match 2 shared topics	Black_Wall // Pre-action outcome API for AI agents	en	artificial-intelligence	robots llmsaihumans	emailphone	none
incode.com ↗	64 match 2 shared topics	AI-powered Identity Verification \| Incode	en	information-and-network-security	robots llmsaihumans	emailphone	none
blinkops.org ↗	64 match 2 shared topics	Agentic Security Operations Platform \| BlinkOps	United States~ en	artificial-intelligence Webflow	robotsllmsaihumans	emailphone	none
blackunicorn.tech ↗	64 match 2 shared topics	LLM Security Testing & EU AI Compliance \| Black Unicorn Security	en	information-and-network-security	robots llmsaihumans	emailphone	none
data-privacy-office.eu ↗	63 match 2 shared topics	Data Privacy Office Europe - DPO Europe	European Union en	artificial-intelligence WordPress	robotsllmsaihumans	emailphone	partial · 8
backslash.security ↗	63 match 2 shared topics	Backslash \| Agentic AI Endpoint Security Platform	en	information-and-network-security Webflow	robotsllmsaihumans	emailphone	none
ambient.ai ↗	63 match 2 shared topics	Prevent security incidents with computer vision intelligence \| Ambient.ai	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
lasso.security ↗	63 match 2 shared topics	Secure AI Adoption at Enterprise Scale \| Lasso	en	information-and-network-security Webflow	robots llmsaihumans	emailphone	none
thinkerlabs.ai ↗	63 match 2 shared topics	Thinker Labs: Cybersecurity, AI & Innovation Integration \| Thinker Laboratories	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
avepoint.com ↗	63 match 2 shared topics	AI-Ready Data Security & Governance for Enterprise \| AvePoint	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
blackswantechnologies.com ↗	63 match 2 shared topics	AI, Cybersecurity & Risk Management Consulting \| Black Swan Technologies%	en	artificial-intelligence 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.