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100match
makina-us.com
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1 co-citations2 shared tech2 shared categorycivil-engineering-industry
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cira-international.co.id 🇮🇩
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1 co-citations2 shared tech2 shared categoryconstruction-industry
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1 co-citations2 shared tech1 shared categorycivil-engineering-industry
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1 co-citations2 shared tech1 shared categorymanufacturing-industry
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bbpondengineering.com
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1 co-citations2 shared tech1 shared categorycivil-engineering-industry
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1 co-citations2 shared tech1 shared categoryconstruction-industry
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boulanteng.com
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1 co-citations2 shared tech1 shared categoryconstruction-industry
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1 co-citations2 shared tech1 shared categorycivil-engineering-industry
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1 co-citations2 shared tech1 shared categorycivil-engineering-industry
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geometrastorani.com
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1 co-citations2 shared tech1 shared categoryconstruction-industry
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geotist.com
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1 co-citations2 shared tech1 shared categorycivil-engineering-industry
90match
gigaframeworks.com
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1 co-citations2 shared tech1 shared categoryconstruction-industry
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appliedsc.co.uk 🇬🇧
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1 co-citations2 shared tech1 shared categorycivil-engineering-industry
85match
jilcom.com
Página principal
1 co-citations2 shared tech2 shared categorycivil-engineering-industry
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hdec-sico.com
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hhhbinfra.com
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85match
aonerailtech.com
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appliedinfrastructure.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.