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ООО «Параллакс» | Комплексные информационно-технические системы безопасности — 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
akkamal.kz ↗	77 match 1 shared topics	Ak Kamal Security \| Мы занимаемся информационной безопасностью	ru	information-and-network-security Drupal	robotsllmsaihumans	emailphone	none
belsiem.com ↗	73 match 1 shared topics	BelSIEM – система мониторинга безопасности (SIEM)	ru	information-and-network-security	robotsllmsaihumans	emailphone	none
1-ncils.store ↗	73 match 1 shared topics	152-ФЗ \| Комитет по информационной и правовой безопасности	ru	information-and-network-security	robotsllmsaihumans	emailphone	none
2-ncils.store ↗	73 match 1 shared topics	152-ФЗ \| Комитет по информационной и правовой безопасности	ru	information-and-network-security	robotsllmsaihumans	emailphone	none
24-ncils.store ↗	73 match 1 shared topics	152-ФЗ \| Комитет по информационной и правовой безопасности	ru	information-and-network-security	robotsllmsaihumans	emailphone	none
5-ncils.store ↗	73 match 1 shared topics	152-ФЗ \| Комитет по информационной и правовой безопасности	ru	information-and-network-security	robotsllmsaihumans	emailphone	none
6-ncils.store ↗	73 match 1 shared topics	152-ФЗ \| Комитет по информационной и правовой безопасности	ru	information-and-network-security	robotsllmsaihumans	emailphone	none
7-ncils.store ↗	73 match 1 shared topics	152-ФЗ \| Комитет по информационной и правовой безопасности	ru	information-and-network-security	robotsllmsaihumans	emailphone	none
8-ncils.store ↗	73 match 1 shared topics	152-ФЗ \| Комитет по информационной и правовой безопасности	ru	information-and-network-security	robotsllmsaihumans	emailphone	none
9-ncils.store ↗	73 match 1 shared topics	152-ФЗ \| Комитет по информационной и правовой безопасности	ru	information-and-network-security	robotsllmsaihumans	emailphone	none
a1-kpib.store ↗	73 match 1 shared topics	152-ФЗ \| Комитет по информационной и правовой безопасности	ru	information-and-network-security	robotsllmsaihumans	emailphone	none
a2-kpib.store ↗	73 match 1 shared topics	152-ФЗ \| Комитет по информационной и правовой безопасности	ru	information-and-network-security	robotsllmsaihumans	emailphone	none
m-cib1.store ↗	73 match 1 shared topics	152-ФЗ \| Комитет по информационной и правовой безопасности	ru	information-and-network-security	robotsllmsaihumans	emailphone	none
m-cib2.store ↗	73 match 1 shared topics	152-ФЗ \| Комитет по информационной и правовой безопасности	ru	information-and-network-security	robotsllmsaihumans	emailphone	none
m-cib3.store ↗	73 match 1 shared topics	152-ФЗ \| Комитет по информационной и правовой безопасности	ru	information-and-network-security	robotsllmsaihumans	emailphone	none
m-cib4.store ↗	73 match 1 shared topics	152-ФЗ \| Комитет по информационной и правовой безопасности	ru	information-and-network-security	robotsllmsaihumans	emailphone	none
m-cib5.store ↗	73 match 1 shared topics	152-ФЗ \| Комитет по информационной и правовой безопасности	ru	information-and-network-security	robotsllmsaihumans	emailphone	none
m01mailpost.store ↗	73 match 1 shared topics	152-ФЗ \| Комитет по информационной и правовой безопасности	ru	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.