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35match
golden-developer.de 🇩🇪
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project-development-site.de 🇩🇪
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forenberg.de 🇩🇪
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28match
fotosaal.de 🇩🇪
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0 co-citations1 shared tech1 shared categorytechnology-and-computing
28match
forum-hessen-it.de 🇩🇪
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28match
genetik-web.de 🇩🇪
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28match
hessen-software.de 🇩🇪
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28match
hessen-produkte.de 🇩🇪
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28match
major-data.de 🇩🇪
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0 co-citations1 shared tech1 shared categorytechnology-and-computing
28match
kunst-und-druck.de 🇩🇪
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0 co-citations1 shared tech1 shared categorytechnology-and-computing
28match
mobile-health-forum.de 🇩🇪
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28match
plasticworldsolutions.de 🇩🇪
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0 co-citations1 shared tech1 shared categorytechnology-and-computing
28match
my-webanalytics.de 🇩🇪
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0 co-citations1 shared tech1 shared categorytechnology-and-computing
28match
procare-holding.de 🇩🇪
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0 co-citations1 shared tech1 shared categorytechnology-and-computing
28match
procare-west.de 🇩🇪
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0 co-citations1 shared tech1 shared categorytechnology-and-computing
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procare-ost.de 🇩🇪
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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.