Piperic
similar sites
‹ ProfileAI ReportTools

Sites similar to mrami.dev

Mohamed Rami | Full-Stack Developer & AI Solutions Architect · ranked by shared content topics & relevance
74match
aadesh.me
Aadesh Gavhane | Agentic AI & Full-Stack Developer
1 shared topicsartificial-intelligence
74match
luanjie.dev
Luanjie — AI & Full-Stack Developer
1 shared topicsartificial-intelligence
74match
siibaalhassan.com
Siiba Alhassan | Full-Stack Developer
1 shared topicsartificial-intelligence
74match
lordsonobire.com
Lordson Obire | AI Full-Stack Developer
1 shared topicsartificial-intelligence
74match
aksy.dev
Akshay - AI Engineer & Full-Stack Developer
1 shared topicsartificial-intelligence
74match
abbos.me
Abbosbek Arabboev — AI Full-Stack Developer
1 shared topicsartificial-intelligence
74match
byhemant.tech
Hemant - Full-Stack Developer & Robotics Engineer | Portfolio
1 shared topicsartificial-intelligence
74match
mreidy.com
Michael Reidy | CS Researcher & Full-Stack Developer
1 shared topicsartificial-intelligence
74match
hmzadev.com
Hamza — AI Agent & Full-Stack Developer
1 shared topicsartificial-intelligence
74match
eddy-kim.com
Eddy Kim - AI Engineer & Full Stack Developer
1 shared topicsartificial-intelligence
73match
andrewbaxter.dev
Andrew Baxter | AI Specialist & Full-Stack Developer
1 shared topicsartificial-intelligence
73match
ahmedseddik.dev
Ahmed Seddik — AI/ML Engineer & Full-Stack Developer
1 shared topicsartificial-intelligence
73match
julhas.com
Mohammad Julhas Sujan | AI Solutions Architect, Health Informatics & AMR Expert
1 shared topicsartificial-intelligence
73match
rek0de.com
Ben Hughes // rek0de | AI Solutions Architect
1 shared topicsartificial-intelligence
73match
fromhomecoffee.com
Nick Losee — AI Solutions Architect
1 shared topicsartificial-intelligence
73match
agenticcore.tech
Daniyal — AI Solutions Architect
1 shared topicsartificial-intelligence
73match
fullfran.com
FullFran - AI Solutions Architect & Physicist
1 shared topicsartificial-intelligence
73match
build-with-brandon.com
Brandon Tate — AI Engineer & Full-Stack Developer
1 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.