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Salish Systems LLC - Enterprise Technology & Security Consulting — 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
am2pm.net.au ↗	69 match 2 shared topics	Cyber Security \| Technology	AU en	cloud-computing Wix	robotsllmsaihumans	emailphone	none
abc3services.com ↗	68 match 2 shared topics	abc3 – Cloud Cybersecurity Consulting	en	information-and-network-security WordPress WooCommerce	robotsllmsaihumans	emailphone	none
zscaler.com ↗	67 match 2 shared topics	Leading Cloud Enterprise Security Provider for Zero Trust	US~ en	information-and-network-security Drupal	robots llmsaihumans	emailphone	none
zscalercloud.com ↗	67 match 2 shared topics	Leading Cloud Enterprise Security Provider for Zero Trust	US~ en	information-and-network-security Drupal	robots llmsaihumans	emailphone	none
zscalerinc.com ↗	67 match 2 shared topics	Leading Cloud Enterprise Security Provider for Zero Trust	US~ en	information-and-network-security Drupal	robots llmsaihumans	emailphone	none
zskaler.com ↗	67 match 2 shared topics	Leading Cloud Enterprise Security Provider for Zero Trust	US~ en	information-and-network-security Drupal	robotsllmsaihumans	emailphone	none
avinteli.com ↗	67 match 2 shared topics	Cloud Security Consulting & AWS Architecture Services \| Avinteli	US~ en	information-and-network-security	robots llmsaihumans	emailphone	none
scalesecureconsulting.com ↗	67 match 2 shared topics	ScaleSecure Consulting \| Cloud Infrastructure & Security Experts	en	information-and-network-security	robotsllmsaihumans	emailphone	none
johndorion.com ↗	66 match 2 shared topics	John Dorion - Consulting Engineer & Cybersecurity Enthusiast	en	information-and-network-security	robotsllmsaihumans	emailphone	partial · 8
mtechsystems.co.uk ↗	66 match 2 shared topics	M-Tech Systems — Technology solutions for ambitious organisations	GB en	information-and-network-security	robotsllmsaihumans	email phone	none
mtechnologygroup.co.uk ↗	66 match 2 shared topics	M-Tech Systems — Technology solutions for ambitious organisations	GB en	information-and-network-security	robotsllmsaihumans	email phone	none
digitalcrest.co.uk ↗	66 match 2 shared topics	Digital Crest Consulting \| Cyber Security, GRC and Cloud	GB en	information-and-network-security	robotsllmsaihumans	emailphone	none
samaysystems.com ↗	66 match 2 shared topics	Samay Systems LLC	en	information-and-network-security	robotsllmsaihumans	emailphone	none
sameli.io ↗	66 match 2 shared topics	Adrian Sameli \| Public Cloud Security Systems Engineer	en	information-and-network-security	robots llmsaihumans	emailphone	partial · 8
hashersystems.com ↗	66 match 2 shared topics	Hasher Systems – IT Infrastructure, Security & Cloud Solutions	en	cloud-computing WordPress WooCommerce	robotsllmsaihumans	emailphone	none
depositit.com ↗	65 match 2 shared topics	Cyber Security Solutions for Business in the Insurance and Technology sectors \| Depositit	en	information-and-network-security	robotsllmsaihumans	emailphone	none
saltuum.com ↗	65 match 2 shared topics	Saltuum Consulting	en	information-and-network-security	robotsllmsaihumans	emailphone	none
cybersecuritycloud.ie ↗	65 match 2 shared topics	Cyber Security Cloud	IE 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.