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48match
adverj.com
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0 co-citations4 shared tech1 shared categoryconstruction-industry
47match
hibat-albasrah.com
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46match
bqdcontracting.com
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46match
hitechenvirosolutions.com
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45match
griffonenergyafrica.com
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0 co-citations6 shared tech1 shared categoryconstruction-industry
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aethondevelopers.com
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44match
hogconstructionservices.com
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0 co-citations5 shared tech1 shared categoryconstruction-industry
44match
getcgroup.com
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0 co-citations4 shared tech1 shared categorycivil-engineering-industry
44match
medigroup.net
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43match
hastriter.com
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0 co-citations3 shared tech1 shared categoryconstruction-industry
43match
hoeraufcontracting.com
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43match
guardianutility.com
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43match
coreborein.com
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0 co-citations3 shared tech1 shared categoryconstruction-industry
43match
digginok.com
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0 co-citations3 shared tech1 shared categoryconstruction-industry
43match
ferrofox.com
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0 co-citations3 shared tech1 shared categorymetals-industry
43match
geotech-resources.com
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0 co-citations3 shared tech1 shared categorycivil-engineering-industry
42match
apolohn.com
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0 co-citations3 shared tech1 shared categoryconstruction-industry
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corenet-engineering.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.