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50match
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eldecusa.com
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50match
eldec-china.com
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50match
emag-world.com
EMAG Machine Tools: Turning Lathes and Grinding Machines
0 co-citations1 shared tech1 shared categorymechanical-and-industrial-engineering-industry
50match
emag.com
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0 co-citations1 shared tech1 shared categorymechanical-and-industrial-engineering-industry
41match
grisar-bt.com
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0 co-citations1 shared tech1 shared categorymechanical-and-industrial-engineering-industry
35match
aljac.com
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35match
cfturbo.com
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0 co-citations1 shared tech1 shared categorymechanical-and-industrial-engineering-industry
35match
elgo-electronic.com
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0 co-citations1 shared tech1 shared categorymechanical-and-industrial-engineering-industry
35match
femfat.com
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0 co-citations1 shared tech1 shared categorymechanical-and-industrial-engineering-industry
35match
femfat-software.com
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0 co-citations1 shared tech1 shared categorymechanical-and-industrial-engineering-industry
35match
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31match
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30match
kanam-grund-group.com
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30match
map7.com
MAP7: map7 Consulting e. U.
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30match
mapa-pro.com
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0 co-citations1 shared tech1 shared categorymechanical-and-industrial-engineering-industry
30match
jacob-group.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.