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Pureml alternatives & similar sites

SuperAlign — AI Security for the Enterprise — 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
llmguardpro.com ↗	74 match 2 shared topics	LLMGuard Pro — Enterprise AI Security Platform	en	information-and-network-security	robotsllmsaihumans	emailphone	none
llmdatasecurity.com ↗	74 match 2 shared topics	Redactive \| Enterprise AI Security Platform	en	information-and-network-security Storyblok	robotsllmsaihumans	emailphone	none
gateforge.io ↗	74 match 2 shared topics	Gateforge — AI security questionnaires for enterprise deals	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
interposesecurity.com ↗	73 match 2 shared topics	Interpose Security — A control layer for enterprise AI	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
protegrity.ai ↗	72 match 2 shared topics	Protegrity \| AI Security and Data Protection for Enterprises	en	information-and-network-security WordPress	robotsllmsaihumans	emailphone	partial · 8
protegrity.com ↗	72 match 2 shared topics	Protegrity \| AI Security and Data Protection for Enterprises	en	information-and-network-security WordPress	robots llmsaihumans	emailphone	none
avepoint.com ↗	71 match 2 shared topics	AI-Ready Data Security & Governance for Enterprise \| AvePoint	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
cavexia.ai ↗	71 match 2 shared topics	Cavexia — Security for the agentic stack	United States~ en	information-and-network-security	robots llms ai humans	emailphone	none
cavexia.com ↗	71 match 2 shared topics	Cavexia — Security for the agentic stack	United States~ en	information-and-network-security	robots llmsaihumans	emailphone	none
llmagentsecurity.com ↗	71 match 2 shared topics	LLM Agent Guard \| Enterprise AI Security & Prompt Shield	en	information-and-network-security	robots llmsaihumans	emailphone	none
neoncyber.com ↗	71 match 2 shared topics	Neon Cyber \| Browser Security for the AI Workforce	en	information-and-network-security	robots llmsaihumans	emailphone	none
protegritydata.com ↗	71 match 2 shared topics	AI Data Security Platform for Secure Enterprise AI \| Protegrity	en	information-and-network-security	robotsllmsaihumans	emailphone	none
hp7.io ↗	70 match 2 shared topics	HP7 Security - AI-Powered Enterprise Cybersecurity	en	information-and-network-security	robotsllmsaihumans	email phone	none
neogriffin.dev ↗	70 match 2 shared topics	NeoGriffin — Security Proxy for AI Agents	en	information-and-network-security	robotsllmsaihumans	emailphone	none
protisec.com ↗	70 match 2 shared topics	PROTISEC — AI-Powered Enterprise Cybersecurity \| PROTISEC	Spain~ en	information-and-network-security Spree Commerce	robots llms aihumans	email phone	full · 11
1pw.ai ↗	70 match 2 shared topics	1PW.AI \| Enterprise Password Security & Bitcoin Solutions	en	information-and-network-security	robotsllmsaihumans	emailphone	partial · 8
intercis.io ↗	70 match 2 shared topics	Intercis — AI Agent Governance for Security Teams	en	information-and-network-security	robotsllmsaihumans	emailphone	none
vortexzen.com ↗	70 match 2 shared topics	VortexZen — AI-Powered Cybersecurity for Real People	en	information-and-network-security Gumroad	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.