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Learning Templates alternatives & similar sites

Learning Templates – Learning management by design — 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
champions-lms.com ↗	70 match 2 shared topics	Champions LMS - Learning Management System	en	education-industry	robotsllmsaihumans	emailphone	none
daylearningdesign.com ↗	68 match 2 shared topics	Day Learning Design – Building scalable Agile learning programs.	en	education-industry WordPress	robotsllmsaihumans	emailphone	none
learnscape.io ↗	68 match 2 shared topics	Learnscape – Digital Learning Design and Development	en	education-industry WordPress	robotsllmsaihumans	emailphone	none
disruptlearning.org.uk ↗	68 match 2 shared topics	Disrupt Learning & Education \| Innovative eLearning Design UK	United Kingdom en	education-industry WordPress	robotsllmsaihumans	emailphone	none
learningdesignsmith.com ↗	68 match 2 shared topics	Learning DesignSmith \| Learning and Development Instructional Designer and LMS	en	education-industry Wix	robots llmsaihumans	emailphone	none
learningdesignlabs.com ↗	68 match 2 shared topics	Learning Design Labs	United States~ en	education-industry Spree Commerce	robotsllmsaihumans	emailphone	none
leanneglasser.com ↗	67 match 2 shared topics	leanne glasser – Learning Experience Designer (LXD) \| 15+ Years in education & learning design	en	education-industry WordPress	robotsllmsaihumans	emailphone	none
learningdesignbyhl.com ↗	67 match 2 shared topics	Learning Design by HL – Instructional Learning design, curriculum curation & eLearning consultancy	en	education-industry WordPress	robotsllmsaihumans	emailphone	none
briarang.com ↗	67 match 2 shared topics	Home \| Briar Ang \| Learning Designer	en	education-industry Wix	robots llmsaihumans	emailphone	none
simondaniele.com ↗	66 match 2 shared topics	Simon Daniele – Transmedia Learning that Drives Engagement and Growth	en	education-industry WordPress WooCommerce	robotsllmsaihumans	emailphone	none
cssdemo.net ↗	66 match 2 shared topics	Anspear \| Learning Design & LMS Technology	en	education-industry	robotsllmsaihumans	email phone	none
hanford.co.uk ↗	66 match 2 shared topics	Anspear \| Learning Design & LMS Technology	United Kingdom en	education-industry	robotsllmsaihumans	email phone	none
aaronjura.com ↗	66 match 2 shared topics	Aaron Jura – Education Leader & Learning Experience Designer	en	education-industry	robotsllmsaihumans	emailphone	none
kckingsbury.com ↗	66 match 2 shared topics	Kiely Kingsbury – Instructional Designer \| Learning Specialist	en	education-industry WordPress	robotsllmsaihumans	emailphone	none
ceslimited.biz ↗	66 match 2 shared topics	E Learning Software \| Blended Learning \| Learning Platform - ceslimited.biz	en	education-industry WordPress	robotsllmsaihumans	emailphone	none
glintlearning.co.uk ↗	66 match 2 shared topics	Glint Learning \|	United Kingdom en	education-industry WordPress	robotsllmsaihumans	emailphone	none
skoolix.app ↗	66 match 2 shared topics	Skoolix - Leading LMS for Efficient School Management	Egypt~ en	education-industry WordPress Gambio	robotsllmsaihumans	emailphone	none
skullee.com ↗	66 match 2 shared topics	Skullee Learning Solutions SL — Empowering learning through digital innovation	en	education-industry	robotsllmsaihumans	email phone	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.