Piperic
similar sites
‹ ProfileAI ReportTools

Sites similar to abdullahghaffar.dev

Abdullah Ghaffar - Backend Engineer & AI Systems · ranked by shared content topics & relevance
75match
abhinavgoyal.dev
Abhinav Goyal - Backend Engineer & AI Systems Architect
1 shared topicsartificial-intelligence
70match
rohianon.com
Rohi Anon Ogula - Backend & AI Engineer
1 shared topicsartificial-intelligence
70match
abaay.tech
Abhay Srivastava | SDE - Backend & AI Systems
1 shared topicsartificial-intelligence
70match
aditya-raj09.tech
Aditya Raj — Software Engineer & AI Systems Builder
1 shared topicsartificial-intelligence
70match
achyuthreddyi.com
Achyuth Reddy — Backend & Systems Engineer
1 shared topicsartificial-intelligence
70match
0xpriyanshujha.dev
Priyanshu Jha - LLM & AI Systems Engineer
1 shared topicsartificial-intelligence
70match
alexnechyporenko.dev
Alex Nechyporenko | AI Backend & LLM Systems Engineer
1 shared topicsartificial-intelligence
70match
neverdecel.com
Neverdecel | AI Systems Engineer
1 shared topicsartificial-intelligence
69match
abhiram-adab.tech
Abhiram Adabala | Backend & AI Engineer
1 shared topicsartificial-intelligence
69match
alexschar.dev
Alex Schar — AI Systems Engineer
1 shared topicsartificial-intelligence
69match
fedemejia.com
Federico Mejia — Systems Engineer & AI Developer
1 shared topicsartificial-intelligence
69match
pieper.ai
Pieper AI — Backend & AI Systems That Scale
1 shared topicsartificial-intelligence
69match
aayushmishra.dev
Aayush Mishra | AI Systems Engineer
1 shared topicsartificial-intelligence
69match
abhi-shek.dev
Abhishek Kumar | AI Systems Engineer
1 shared topicsartificial-intelligence
69match
ahmedachour.tech
Ahmed Achour — AI Systems Engineer
1 shared topicsartificial-intelligence
69match
fernandofauth.com
Fernando Fauth | AI Systems Engineer
1 shared topicsartificial-intelligence
69match
matlababbaszada.com
Matlab Abbaszada — Backend Developer & AI Engineer
1 shared topicsartificial-intelligence
69match
arkanislabs.com
Arkanis Labs | AI Systems Engineering
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.