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42match
greenuxglobal.com
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0 co-citations1 shared tech1 shared categoryconstruction-industry
42match
fencerentalservice.com
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41match
corazon-marketing.com
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40match
jiniv.com
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40match
hbxiaotian.com
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0 co-citations2 shared tech1 shared categorycivil-engineering-industry
40match
bowlandbeam.com
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0 co-citations2 shared tech1 shared categoryconstruction-industry
40match
genialcontractors.com
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0 co-citations1 shared tech1 shared categoryconstruction-industry
35match
jengapro.com
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0 co-citations0 shared tech1 shared categoryconstruction-industry
35match
kejugegroup.com
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0 co-citations0 shared tech1 shared categoryconstruction-industry
35match
kemetals.com
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0 co-citations0 shared tech1 shared categoryconstruction-industry
35match
kempa-llc.com
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0 co-citations0 shared tech1 shared categorymechanical-and-industrial-engineering-industry
35match
kenyabitumen.com
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0 co-citations0 shared tech1 shared categoryconstruction-industry
35match
kjfabrications.com
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0 co-citations0 shared tech1 shared categoryconstruction-industry
35match
kjfearless.com
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0 co-citations0 shared tech1 shared categoryconstruction-industry
35match
kjtimur.com
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0 co-citations0 shared tech1 shared categoryconstruction-industry
35match
kkcontech.com
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0 co-citations0 shared tech1 shared categorycivil-engineering-industry
35match
kyrodevelopment.com
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0 co-citations0 shared tech1 shared categoryreal-estate-industry
35match
makhersstudio.com
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0 co-citations0 shared tech1 shared categoryconstruction-industry

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.