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Polygraph and Security Technologies in The Woodlands | PAST — 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
krontech.com ↗	75 match 1 shared topics	Telecom and Cybersecurity Technologies \| Kron	en	information-and-network-security	robotsllmsaihumans	emailphone	none
curvace.org ↗	71 match 1 shared topics	Curvace \| Optical Sensing & Security Technology	United States~ en	information-and-network-security	robotsllmsaihumans	emailphone	none
5qglobal.net ↗	70 match 1 shared topics	5Q \| CRE Technology and Cyber Security Experts	United States~ en	information-and-network-security	robotsllmsaihumans	emailphone	none
cser.tech ↗	70 match 1 shared topics	cser.tech \| Discreet Technology & Security	en	information-and-network-security	robotsllmsaihumans	emailphone	none
cyfendry.com ↗	70 match 1 shared topics	Cyfendry \| Government Technology and Security Solutions	en	information-and-network-security	robotsllmsaihumans	emailphone	none
cybrawn.tech ↗	70 match 1 shared topics	CYBRAWN Technologies — Digital Investigations & Enterprise-Grade Security	en	information-and-network-security	robotsllmsaihumans	emailphone	none
larches.io ↗	70 match 1 shared topics	Larches Technologies - Cybersecurity & IT Services	en	information-and-network-security	robotsllmsaihumans	emailphone	none
larches.net ↗	70 match 1 shared topics	Larches Technologies - Cybersecurity & IT Services	en	information-and-network-security	robotsllmsaihumans	emailphone	none
devost.net ↗	70 match 1 shared topics	Matt Devost – Technologist \| Entrepreneur \| Security Expert	en	information-and-network-security WordPress	robotsllmsaihumans	emailphone	none
cycomtechnologies.tech ↗	69 match 1 shared topics	Advanced Cycom Technologies - Cybersecurity & IT Solutions	en	information-and-network-security	robotsllmsaihumans	emailphone	none
shrijishah.com ↗	69 match 1 shared topics	Shriji Shah - Security and Information Technology Specialist	en	information-and-network-security	robotsllmsaihumans	emailphone	none
conklintechsec.com ↗	69 match 1 shared topics	Cybersecurity \| Conklin Technology Security Assessment	en	information-and-network-security Wix	robots llmsaihumans	emailphone	none
alberto.bz ↗	69 match 1 shared topics	Alberto J. Matus – Cybersecurity \| Technology \| Belize	en	information-and-network-security WordPress WooCommerce	robotsllmsaihumans	emailphone	none
nozominetworks.ch ↗	69 match 1 shared topics	The Leader in OT Cybersecurity Technology \| Nozomi Networks	Switzerland en	information-and-network-security	robotsllmsaihumans	emailphone	none
p3tm.com ↗	69 match 1 shared topics	P3 Technologies \| Enterprise Cybersecurity	en	information-and-network-security	robotsllmsaihumans	emailphone	none
crystaltech.co.ke ↗	69 match 1 shared topics	Home - Your Partner in Technology & Security	en	information-and-network-security WordPress WooCommerce	robotsllmsaihumans	emailphone	none
dizard.tech ↗	69 match 1 shared topics	Home \| Dizard Technologies	en	information-and-network-security	robotsllmsaihumans	emailphone	partial · 8
1sourcedigital.com ↗	69 match 1 shared topics	Home - One Source Digital Technologies	en	information-and-network-security WordPress	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.