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65match
link-be.com
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0 co-citations5 shared tech1 shared categorycivil-engineering-industry
65match
janurteknik.com
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0 co-citations5 shared tech1 shared categorymechanical-and-industrial-engineering-industry
65match
adscenso.com
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0 co-citations5 shared tech1 shared categoryconstruction-industry
65match
afferoenterprises.com
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0 co-citations5 shared tech1 shared categorycivil-engineering-industry
65match
ccincorporated.com
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0 co-citations5 shared tech1 shared categoryconstruction-industry
59match
handymanexpedited.com
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59match
hasolhormigones.com
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0 co-citations4 shared tech1 shared categoryconstruction-industry
59match
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0 co-citations4 shared tech1 shared categorycivil-engineering-industry
59match
campsasac.com
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0 co-citations4 shared tech1 shared categoryconstruction-industry
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grayrockae.com
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0 co-citations4 shared tech1 shared categorylogistics-and-transportation-industry
59match
4pointplans.com
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0 co-citations4 shared tech1 shared categoryconstruction-industry
59match
a1-constructiongroup.com
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0 co-citations4 shared tech1 shared categoryconstruction-industry
59match
anuskaengineering.com
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0 co-citations4 shared tech1 shared categorycivil-engineering-industry
59match
apexiacts.com
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0 co-citations4 shared tech1 shared categoryconstruction-industry
59match
aqdiw.com
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0 co-citations4 shared tech1 shared categoryconstruction-industry
59match
aramegypt.com
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0 co-citations4 shared tech1 shared categoryconstruction-industry
59match
bamakohome.com
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bamboo2trade.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.