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85match
bogdanielart.com
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2 co-citations4 shared tech2 shared categoryfine-art
85match
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80match
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2 co-citations4 shared tech0 shared categorytheater
75match
aeindel.com
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2 co-citations2 shared tech1 shared categoryfine-art
70match
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2 co-citations2 shared tech2 shared categoryfine-art
70match
ektedemoner.com
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2 co-citations2 shared tech2 shared categoryfine-art
68match
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1 co-citations4 shared tech2 shared categoryfine-art
68match
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68match
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65match
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2 co-citations4 shared tech0 shared categorydance
65match
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2 co-citations4 shared tech0 shared categorydance
62match
kelownasbk.com
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1 co-citations4 shared tech0 shared categorydance
62match
mandykeen.com
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1 co-citations4 shared tech0 shared categorytheater
62match
1whocreates.com
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1 co-citations4 shared tech0 shared categorydesign
62match
afdanceteam.com
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1 co-citations4 shared tech0 shared categorydance
62match
aquamaraboatworks.com
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1 co-citations4 shared tech0 shared categorydesign
62match
cec-me.com
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1 co-citations4 shared tech0 shared categorydesign
62match
elevatedesign.com
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1 co-citations4 shared tech0 shared categorydesign

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.