Piperic
similar sites
‹ ProfileAI ReportTools

Sites similar to theodoraxelson.com

Theo Axelson — Power Platform Architect & Data Engineer · ranked by shared content topics & relevance
71match
thepowerplatformnerd.com
The Power Platform Nerd
2 shared topicsartificial-intelligence
70match
sokoslee.com
Sokos Lee — E-commerce Architect & AI Engineer
2 shared topicsartificial-intelligence
70match
arika.dev
Arika — Thoughtful Writing on Architecture, AI & Engineering
2 shared topicstechnology-and-computing
70match
pimentadev.com
JFP | Architecture & AI Engineering
2 shared topicsartificial-intelligence
70match
sonnymonti.com
Sonny Monti — AI Solution Architect
2 shared topicsartificial-intelligence
69match
mattmace.dev
Matt Mace — Platform Engineer & AI Graduate Student
2 shared topicsartificial-intelligence
69match
grulify.com
Grulify — Systems Architect & Data Analyst
2 shared topicsartificial-intelligence
69match
cliffstudios.com
Brady Clifford – AI-First Software Engineer | Architect | Strategist
2 shared topicsartificial-intelligence
69match
dkatsiros.com
Dimitris Katsiros — Data Engineer & ML Engineer
2 shared topicsartificial-intelligence
69match
dominican-resorts.com
AI Systems Architect & Digital Engineer | ProInternet TV
2 shared topicsartificial-intelligence
68match
romankitsela.com
Roman Kitsela — Mathematician & Data Engineer
2 shared topicsartificial-intelligence
68match
fedealmendra.com
Federico Almendra · Backend & Platform Engineer
2 shared topicsartificial-intelligence
68match
iorlas.com
Denis Tomilin — AI Architect
2 shared topicsartificial-intelligence
68match
maximehaegeman.com
Maxime Haegeman | Data Engineer
2 shared topicsartificial-intelligence
68match
dlobaton.com
Daniel Lobaton — Research Engineer
2 shared topicsartificial-intelligence
68match
masondelrio.com
Mason Del Rio — Data & Full-Stack Engineer
2 shared topicsartificial-intelligence
68match
fateless.dev
Aditya Singh | AI Engineer & Backend Architect
2 shared topicsartificial-intelligence
67match
farhancss.com
Syed Farhan Ahmed — Full-Stack Developer · Engineering Manager · Technology Lead · Solution Architect
2 shared topicsartificial-intelligence

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:

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.