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85match
kenximedicalcourier.com
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2 co-citations3 shared tech2 shared categorylogistics-and-transportation-industry
85match
africaroadfreight.com
Castle Transport| Road Freight into Africa| Logistics| Supply Chain Management| Bonded Warehousing|
2 co-citations3 shared tech2 shared categorylogistics
77match
gemslogisticsinc.com
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2 co-citations3 shared tech2 shared categorylogistics
72match
centerlinefreightservicesinc.com
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72match
greenwoodpallet.com
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1 co-citations3 shared tech2 shared categorylogistics
70match
hastekpro.com
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2 co-citations3 shared tech0 shared categorymechanical-and-industrial-engineering-industry
70match
greentechnologysolution.com
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2 co-citations3 shared tech0 shared categorygreen-solutions
70match
3dnetwork.uk 🇬🇧
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2 co-citations3 shared tech0 shared categorytechnology-industry
70match
aegispayfi.com
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2 co-citations3 shared tech0 shared categoryfinancial-industry
70match
acedigitalmarketing.co.uk 🇬🇧
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70match
kanddsolutions.com
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2 co-citations3 shared tech0 shared categorybusiness
69match
greenforrogers.com
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2 co-citations3 shared tech0 shared categorygreen-solutions
69match
devham.com
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69match
fdimarketplace.com
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69match
cotugnoconstruction.com
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2 co-citations3 shared tech0 shared categoryconstruction-industry
69match
grevch.com
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2 co-citations3 shared tech0 shared categoryreal-estate-industry
69match
apartnerinlearning.com
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2 co-citations3 shared tech0 shared categoryeducation-industry
68match
hlmarketingservices.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.