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Ricardo Conceição - VP Engineering | rnuno.com — 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 Computer Networking →

Domain	Match	Title	Country/Lang	Category	AI files	Contact	AI-protection
gieittechs.com ↗	68 match 2 shared topics	Home - Global Infrastructure Engineering	en	computer-networking	robotsllmsaihumans	emailphone	none
aptient.com.au ↗	66 match 2 shared topics	Network Engineering, Security & Managed Infrastructure — Aptient	Australia en	computer-networking	robotsllmsaihumans	emailphone	none
maruf.engineer ↗	66 match 2 shared topics	Maruf Ahmed \| Network Engineer \| Cisco & MikroTik Specialist	en	computer-networking	robotsllmsaihumans	emailphone	none
kennethnnorom.com ↗	65 match 2 shared topics	Kenneth Nnorom \| Network Security Engineer	en	information-and-network-security WordPress	robots llmsaihumans	emailphone	none
aldar.tech ↗	64 match 2 shared topics	Aldar Ali - System Engineer and Cybersecurity enthusiast	en	information-and-network-security	robotsllmsaihumans	emailphone	none
allcable.net ↗	63 match 2 shared topics	All Cable Consulting \| Structured Cabling & Security Systems	en	information-and-network-security WordPress WooCommerce	robotsllmsaihumans	email phone	none
benno-sawitzki.com ↗	63 match 2 shared topics	Network Scanning \| InternetData	en	computer-networking	robotsllmsaihumans	emailphone	none
theapiwire.com ↗	63 match 2 shared topics	The API Wire \| The Integration Network	en	computer-networking	robotsllmsaihumans	emailphone	none
zypercore.com ↗	63 match 2 shared topics	Zypercore - Leading IT Reseller for Network and Security \| zypercore.com	en	information-and-network-security	robotsllmsaihumans	emailphone	none
kenlexan.com ↗	62 match 2 shared topics	Kenlexan – Powering Secure Connections	en	information-and-network-security WordPress	robotsllmsaihumans	emailphone	none
kdg-neteng.com ↗	62 match 2 shared topics	KDG NetEng \| KDG NetEng	en	computer-networking WordPress	robotsllmsaihumans	email phone	none
startkentik.com ↗	62 match 2 shared topics	Network Intelligence and Observability \| Network Monitoring & DDoS Detection \| Kentik	en	computer-networking	robots llmsaihumans	emailphone	none
demokentik.com ↗	62 match 2 shared topics	Network Intelligence and Observability \| Network Monitoring & DDoS Detection \| Kentik	en	computer-networking	robots llmsaihumans	emailphone	none
kentikteam.com ↗	62 match 2 shared topics	Network Intelligence and Observability \| Network Monitoring & DDoS Detection \| Kentik	en	computer-networking	robots llmsaihumans	emailphone	none
kentikpro.com ↗	62 match 2 shared topics	Network Intelligence and Observability \| Network Monitoring & DDoS Detection \| Kentik	en	computer-networking	robots llmsaihumans	emailphone	none
kentikapp.com ↗	62 match 2 shared topics	Network Intelligence and Observability \| Network Monitoring & DDoS Detection \| Kentik	en	computer-networking	robots llmsaihumans	emailphone	none
kentikaitech.com ↗	62 match 2 shared topics	Network Intelligence and Observability \| Network Monitoring & DDoS Detection \| Kentik	en	computer-networking	robots llmsaihumans	emailphone	none
kentikaiteam.com ↗	62 match 2 shared topics	Network Intelligence and Observability \| Network Monitoring & DDoS Detection \| Kentik	en	computer-networking	robots llmsaihumans	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.