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Alphametics Inc. – AI-Enabled Engineering for Secure Enterprises — 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
privateaifactory.com ↗	70 match 2 shared topics	Private AI Factory \| Secure On-Prem LLM Deployment for Enterprises & Defense	en	artificial-intelligence	robotsllmsaihumans	email phone	none
siegepal.com ↗	70 match 2 shared topics	SiegePal - Cybersecurity & AI Engineering for B2B	en	information-and-network-security	robots llmsaihumans	emailphone	none
privateaiglobal.com ↗	69 match 2 shared topics	Private AI Global \| Secure Enterprise AI Solutions	en	information-and-network-security	robotsllmsaihumans	emailphone	none
briangreunke.com ↗	68 match 2 shared topics	Brian Greunke — AI Security & Engineering	en	artificial-intelligence	robots llmsaihumans	emailphone	none
privaro.ai ↗	68 match 2 shared topics	Privaro — Privacy Infrastructure for Enterprise AI	en	artificial-intelligence	robots llmsaihumans	emailphone	none
mybigid.com ↗	68 match 2 shared topics	BigID: Enterprise Data Security Platform for DSPM & AI	Israel~ en	information-and-network-security WordPress	robotsllmsaihumans	emailphone	none
1-pro.net ↗	68 match 2 shared topics	1PRO Solutions - AI-Powered Cybersecurity & Innovation \| Enterprise Security Services	United States~ en	information-and-network-security	robotsllmsaihumans	email phone	none
alphabytez.dev ↗	68 match 2 shared topics	AlphaBytez - Private AI. Secure Systems. Built for the Real World.	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
progralink.com ↗	68 match 2 shared topics	Progralink — Cybersecurity Engineering & Post-Quantum Cryptography	en	information-and-network-security	robotsllmsaihumans	emailphone	none
leonchu.com ↗	68 match 2 shared topics	Leon Chu \| AI Engineer	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
keygraphlcl.com ↗	68 match 2 shared topics	Keygraph \| Continuous Agentic Pentesting for the Enterprise	en	information-and-network-security	robots llmsaihumans	emailphone	none
keygraph.net ↗	68 match 2 shared topics	Keygraph \| Continuous Agentic Pentesting for the Enterprise	en	information-and-network-security	robots llmsaihumans	emailphone	none
keygraph.io ↗	68 match 2 shared topics	Keygraph \| Continuous Agentic Pentesting for the Enterprise	en	information-and-network-security	robots llmsaihumans	emailphone	none
proactcyber.com ↗	68 match 2 shared topics	ProAct Cyber - AI Cybersecurity & Managed Compliance Solutions \| Enterprise Security Services	United States~ en	information-and-network-security	robotsllmsaihumans	emailphone	partial · 8
avepoint.com ↗	67 match 2 shared topics	AI-Ready Data Security & Governance for Enterprise \| AvePoint	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
cybrcon.com ↗	67 match 2 shared topics	Cybrcon — AI Governance & Cybersecurity Compliance Engineering	en	information-and-network-security	robotsllmsaihumans	emailphone	none
kawshik.dev ↗	67 match 2 shared topics	Kawshik Ahmed Ornob — Security, AI & Full-Stack Engineer	en	information-and-network-security	robotsllmsaihumans	emailphone	none
precize.io ↗	67 match 2 shared topics	Trusted Agentic Automation for Enterprises	en	information-and-network-security	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.