Piperic
similar sites
‹ ProfileAI ReportTools

Sites similar to repolense.ai

RepoLens | Codebase understanding for PMs and engineers · ranked by shared content topics & relevance
100match
repolens.ai
RepoLens | Codebase understanding for PMs and engineers
2 shared topicstechnology-and-computing
68match
eventsourcingbook.com
Understanding Eventsourcing
2 shared topicssoftware-and-applications
67match
paulgradie.com
Paul Gradie - Software Engineer and Builder
2 shared topicstechnology-and-computing
67match
iklabs.dev
IK Labs - Engineering studio for long-lived software systems
2 shared topicssoftware-and-applications
67match
importflow.dev
Onboarding imports for Supabase SaaS founders | ImportFlow
2 shared topicstechnology-and-computing
67match
andernet.dev
Matthew Anderson | Software Engineer
2 shared topicstechnology-and-computing
67match
ternki.com
Ternki - Building tools for DevOps and Platform Engineers
2 shared topicstechnology-and-computing
66match
evansagge.com
Evan Sagge - Software Engineering Leader
2 shared topicstechnology-and-computing
66match
alexflores.cloud
Alex Flores | Software Engineer
2 shared topicstechnology-and-computing
66match
abahnj.dev
Josemaria Abah - Senior Android Engineer
2 shared topicstechnology-and-computing
66match
denisantonov.com
Denis Antonov - Software Engineer
2 shared topicssoftware-and-applications
66match
deniroholding.com
DeNiRo Holding — Engineering Team
2 shared topicstechnology-and-computing
66match
deploytitan.com
DeployTitan | Coordinated safe releases for distributed engineering teams
2 shared topicstechnology-and-computing
66match
devdo.com
devdo - understanding your development process
2 shared topicstechnology-and-computing
66match
mapnix.com
Mapnix | Integration Engineering Workspace
2 shared topicssoftware-and-applications
66match
andrewmclachlan.com
Andrew McLachlan - Engineering Manager
2 shared topicstechnology-and-computing
66match
arifurrahman.dev
Arifur Rahman | Founder & Software Engineer
2 shared topicssoftware-and-applications
66match
eviraj.dev
Viraj Ehelepola | QA Engineer
2 shared topicssoftware-and-applications

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.