Piperic
similar sites
‹ ProfileAI ReportTools

Sites similar to thepiyushkumar.com

Piyush Kumar | Lead Product Manager · ranked by shared content topics & relevance
74match
kunle.ai
Product Manager
1 shared topicstechnology-and-computing
70match
arnauddeklerk.com
Arnaud de Klerk | Product Manager
1 shared topicstechnology-and-computing
70match
boborchard.com
Bob Orchard | Senior Product Manager
1 shared topicstechnology-and-computing
70match
theserhiibo.com
Serhii Bohachenko — Product Manager
1 shared topicstechnology-and-computing
70match
alekforgrowth.com
Alek Darr — Product Manager & Builder
1 shared topicstechnology-and-computing
69match
andynguyen.digital
Andy Nguyen — Product Manager Portfolio
1 shared topicstechnology-and-computing
69match
mattliveshere.com
Matt Jarosz, Product Manager in Los Angeles
1 shared topicstechnology-and-computing
69match
arseniia-khoriushina.com
Arseniia Khoriushina – Product Manager
1 shared topicstechnology-and-computing
68match
adamjturnbull.com
Adam Turnbull | Digital Product Management
1 shared topicstechnology-and-computing
68match
feras.com
Feras - Platform Product Manager & API Strategist
1 shared topicstechnology-and-computing
68match
kumarpeeyush.com
Peeyush Kumar | Software Engineer
1 shared topicstechnology-and-computing
67match
bobblake.com
Bob Blake | Product Manager, Hardware Engineer, Grill Master
1 shared topicstechnology-and-computing
67match
dj21techstack.com
Dj21TechStack | apigee developer ; product manager; software engineer;
1 shared topicstechnology-and-computing
66match
arpanaprajapati.com
Arpana Prajapati | Product Leader
1 shared topicstechnology-and-computing
66match
kukulinski.com
Ross Kukulinski: Technology Product Management, Strategy, and Startups
1 shared topicstechnology-and-computing
66match
kukulinski.dev
Ross Kukulinski: Technology Product Management, Strategy, and Startups
1 shared topicstechnology-and-computing
66match
kumarsomesh.com
Somesh Kumar
1 shared topicstechnology-and-computing
66match
feedrou.com
Feedrou — Fast, customisable product feed management
1 shared topicstechnology-and-computing

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.