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76match
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3 co-citations7 shared tech1 shared categorybusiness
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consultantagency.co.uk 🇬🇧
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3 co-citations7 shared tech1 shared categorybusiness
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3 co-citations7 shared tech0 shared categorylegal-services-industry
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atconsultantservices.co.uk 🇬🇧
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3 co-citations7 shared tech0 shared categorymanagement-consulting-industry
66match
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3 co-citations7 shared tech1 shared categorybusiness
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cbbaws.com
CBBAWS - COMMUNITY BUSINESS BUILDERS OF ALBUQUERQUE WEST SIDE
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3 co-citations7 shared tech0 shared categorymechanical-and-industrial-engineering-industry
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balmoralsolutions.com
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3 co-citations7 shared tech0 shared categorymanagement-consulting-industry
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bowmorefinance.com
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apecelectricalservices.com
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2 co-citations7 shared tech1 shared categorybusiness
65match
botslogic.com
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2 co-citations7 shared tech1 shared categorybusiness
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corgiregistered.com
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2 co-citations7 shared tech1 shared categorymanagement-consulting-industry
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appblinds.co.uk 🇬🇧
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2 co-citations7 shared tech1 shared categorybusiness
62match
abielrecruitment.co.uk 🇬🇧
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2 co-citations7 shared tech0 shared categoryhealthcare-industry
62match
calabashlogistics.co.uk 🇬🇧
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2 co-citations7 shared tech0 shared categorylogistics-and-transportation-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.