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45match
automaten-meinken.com
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0 co-citations5 shared tech0 shared categoryweb-development
45match
breitler-pharma.com
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0 co-citations5 shared tech0 shared categoryweb-development
45match
aobtrading.com
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0 co-citations5 shared tech0 shared categoryweb-development
45match
getatech.de 🇩🇪
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0 co-citations5 shared tech0 shared categoryweb-development
45match
globalpix.de 🇩🇪
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0 co-citations5 shared tech0 shared categoryweb-development
45match
it-professional-services.de 🇩🇪
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0 co-citations5 shared tech0 shared categoryweb-development
45match
maria-und-markus.de 🇩🇪
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0 co-citations5 shared tech0 shared categoryweb-development
45match
openhouse-netzwerk.de 🇩🇪
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0 co-citations5 shared tech0 shared categorycomputer-networking
45match
projektrockengel.de 🇩🇪
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0 co-citations5 shared tech0 shared categoryweb-development
45match
trustworks.de 🇩🇪
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0 co-citations5 shared tech0 shared categoryit-and-internet-support
41match
3dlogo.com
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0 co-citations1 shared tech1 shared category3-d-graphics
40match
homemade-studios.de 🇩🇪
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40match
itc-project.de 🇩🇪
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38match
filaso.com
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0 co-citations1 shared tech1 shared category3-d-graphics
38match
filaso3d.com
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0 co-citations1 shared tech1 shared category3-d-graphics
38match
produkterotik.de 🇩🇪
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38match
project-dio.de 🇩🇪
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35match
haxurd.com
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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.