Piperic Business Intelligence

similar sites

Sites similar to markuslehtola.com

Markus Lehtola — Blog & Projects · ranked by category · tech stack · backlink co-citation

Jacky Huang's Blog

2 co-citations2 shared tech1 shared categorytechnology-and-computing

2 co-citations2 shared tech1 shared categorytechnology-and-computing

2 co-citations2 shared tech1 shared categorytechnology-and-computing

ivanaguilar.com

Ivan Aguilar | Site Reliability Engineer / Platform Engineer

2 co-citations2 shared tech1 shared categorytechnology-and-computing

Vladimir Ivakin

2 co-citations2 shared tech1 shared categorytechnology-and-computing

Jared Hagen · Principal Software Engineer

2 co-citations2 shared tech1 shared categorytechnology-and-computing

jasmeetbrar.com

Jasmeet Brar | Full Stack Engineer

2 co-citations2 shared tech1 shared categoryweb-development

Home | Adnane MIRI

2 co-citations2 shared tech1 shared categoryartificial-intelligence

Thinking Emoji 🤔 | Adriel Martinez

2 co-citations2 shared tech1 shared categorytechnology-and-computing

Thinking Emoji 🤔 | Adriel Martinez

2 co-citations2 shared tech1 shared categorytechnology-and-computing

Home • Balssh

2 co-citations2 shared tech1 shared categoryweb-design-and-html

Celeriant: enforce your invariants at write time

2 co-citations2 shared tech1 shared categoryprogramming-languages

2 co-citations2 shared tech1 shared categoryprogramming-languages

2maro.io — The Backlog

2 co-citations2 shared tech1 shared categoryweb-development

.0wav — Media with a memory

2 co-citations2 shared tech0 shared categorydigital-audio

Jeff Hidalgo — Security Engineer

2 co-citations2 shared tech0 shared categoryinformation-and-network-security

Aleksandar Pavlov — Software Engineer

2 co-citations2 shared tech1 shared categoryartificial-intelligence

András Hatvani — Senior Software Architect & AI Transformation Consultant

2 co-citations2 shared tech0 shared categoryartificial-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:

co-citations how often the same third-party websites link out to both — sites referenced together tend to serve the same world.
shared tech how much of their technology stack (CMS, e‑commerce, analytics, frameworks…) overlaps.
shared category whether they sit in the same business / industry category.
positioning how closely their titles and on‑page wording line up.

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.