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Empowering Excellence and Innovation in Education and Technology | Data Dynamics — 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 Education Industry →

Domain	Match	Title	Country/Lang	Category	AI files	Contact	AI-protection
cue.org ↗	73 match 1 shared topics	Leading Innovation in Education - CALIE	en	education-industry WordPress	robotsllmsaihumans	email phone	partial · 8
carinaconsulting.co.uk ↗	72 match 1 shared topics	Carina Consulting - excellence in education and skills	United Kingdom en	education-industry	robotsllmsaihumans	email phone	none
bridgingtechsolutions.com ↗	71 match 1 shared topics	Tech Bridge Solutions: Connecting Education and Technology \| Tech Bridge Solutions	en	education-industry	robotsllmsaihumans	emailphone	none
srausche.com ↗	71 match 1 shared topics	Sam Rauschenfels \| Higher Education \| Innovation \| Advocacy \| Technology	en	education-industry WordPress	robotsllmsaihumans	emailphone	none
data.org.uk ↗	71 match 1 shared topics	We support and champion design and technology education in schools - D&T Association	United Kingdom en	education-industry	robotsllmsaihumans	emailphone	none
baronsedtechconsulting.com ↗	71 match 1 shared topics	Home – Educational technology consulting for higher education and K-12	en	education-industry WordPress	robotsllmsaihumans	emailphone	none
developmentwisdom.org ↗	71 match 1 shared topics	Innovative Education and Entrepreneurial Solutions\| Development Wisdom	en	education-industry Weebly	robotsllmsaihumans	emailphone	none
erifoundry.org ↗	71 match 1 shared topics	ERI Foundry - Education Research and Innovation	en	education-industry	robotsllmsaihumans	emailphone	partial · 8
anydstem.com ↗	70 match 1 shared topics	AnyD Materials - STEM Education Excellence \| IIT Bombay	en	education-industry	robotsllmsaihumans	emailphone	none
mcglaysia.com ↗	70 match 1 shared topics	Learning2.1 – technology and education and all that goes in the mix	en	education-industry WordPress	robotsllmsaihumans	emailphone	none
cscollaborative.org ↗	70 match 1 shared topics	Jason Innes \| Educational Technology Consulting	en	education-industry	robotsllmsaihumans	emailphone	none
danieldowns.com ↗	70 match 1 shared topics	Daniel Downs: Educational Leader and Technology Strategist \| Daniel Downs	en	education-industry	robotsllmsaihumans	emailphone	none
csajapan.org ↗	70 match 1 shared topics	CSA Japan - Empowering Education Across the Pacific	en	education-industry WordPress WooCommerce	robotsllmsaihumans	emailphone	none
education.gov.mw ↗	70 match 1 shared topics	Ministry of Education - Science and Technology	en	education-industry	robotsllmsaihumans	emailphone	none
ei.study ↗	70 match 1 shared topics	Educational Initiatives \| Transforming Education Through Technology	en	education-industry	robotsllmsaihumans	emailphone	none
one98edusolutions.com ↗	70 match 1 shared topics	One98 Edusolutions: Pioneering Education Excellence	en	education-industry WordPress	robotsllmsaihumans	emailphone	none
howardpharmily.com ↗	70 match 1 shared topics	Higher Education Admissions & Enrollment Technology \| Liaison	en	education-industry	robotsllmsaihumans	emailphone	none
edtechmagazine.com ↗	70 match 1 shared topics	K12 and Higher Education Technology News \| EdTech Magazine	United States~ en	education-industry Drupal	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.