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Data – Marc – Blogging about everything related to Data and AI based on Microsoft technology — 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
bruce2b.com ↗	69 match 2 shared topics	bruce2b – where Bruce Wilson blogs about business and technology	en	artificial-intelligence WordPress	robotsllmsaihumans	emailphone	partial · 8
hrnjica.net ↗	68 match 2 shared topics	Bahrudin Hrnjica Blog – All about technology: ML, .NET, EA, FEM, Math…	en	technology-and-computing WordPress	robotsllmsaihumans	emailphone	none
365-thoughts.com ↗	68 match 2 shared topics	Scott Roller – This is my home base to discuss all things Microsoft Dynamics 365 and Power Platform.	en	technology-and-computing WordPress	robotsllmsaihumans	emailphone	none
eto.tech ↗	67 match 2 shared topics	Emerging Technology Observatory	en	technology-and-computing	robotsllmsaihumans	emailphone	none
anirudhbhatnagar.com ↗	67 match 2 shared topics	anirudh bhatnagar – Blog to keep me in sync with the evolving technologies.	en	artificial-intelligence WordPress	robotsllmsaihumans	emailphone	none
vividcomm.com ↗	67 match 2 shared topics	Vividcomm – Advanced Technology in Action	en	technology-and-computing WordPress	robotsllmsaihumans	emailphone	none
omgmicrosoft.com ↗	67 match 2 shared topics	OMG! Microsoft — Keeping an ear to the Redmond ground	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
coiffure-chic.ch ↗	67 match 2 shared topics	Codelynx Blog - Be Updated on latest Tech News	Switzerland en	technology-and-computing WordPress WooCommerce	robots llmsaihumans	emailphone	none
everythingaiml.dev ↗	67 match 2 shared topics	Everything AIML	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
eugeniosegala.dev ↗	66 match 2 shared topics	Eugenio Segala - Applied AI lead, technologist, and dreamer.	en	technology-and-computing	robotsllmsaihumans	emailphone	none
antonmaximov.com ↗	66 match 2 shared topics	anton maximov \| Notes on engineering leadership, technology, and adjacent topics by Anton Maximov.	en	technology-and-computing	robotsllmsaihumans	emailphone	none
sprunworld.com ↗	66 match 2 shared topics	SprunWorld - All About Tech and Net	en	technology-and-computing WordPress	robotsllmsaihumans	emailphone	none
ollycox.com ↗	66 match 2 shared topics	Olly Cox – A technology enthusiast trying to be better at sharing	en	artificial-intelligence WordPress	robotsllmsaihumans	emailphone	none
stafera.com ↗	66 match 2 shared topics	Matt Stafrace - Data, Compliance, Technology	en	artificial-intelligence	robotsllmsaihumans	emailphone	partial · 8
brova.com ↗	66 match 2 shared topics	George Brova – Founding CTO @ Migacore Technologies	en	technology-and-computing	robotsllmsaihumans	emailphone	none
datacasquette.com ↗	66 match 2 shared topics	DataCasquette - Data and AI experiments for cybersecurity	en	artificial-intelligence WordPress	robotsllmsaihumans	emailphone	none
ericcrichardson.com ↗	66 match 2 shared topics	Eric C Richardson – Observations in Innovation, technology, and decisions	en	artificial-intelligence WordPress	robotsllmsaihumans	emailphone	none
viraviotech.com ↗	66 match 2 shared topics	ViravioTech – Exploring the Future of AI & Technology	en	technology-and-computing WordPress WooCommerce	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.