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90match
maivax.com
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90match
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72match
bakesonic.com
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58match
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58match
adrianocabrera.com
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58match
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57match
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55match
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1 co-citations3 shared tech0 shared categorydesserts-and-baking
55match
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55match
bombaycurries.com
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54match
gudtolli.com
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1 co-citations3 shared tech1 shared categoryfood-and-drink
54match
balbademcafe.com
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1 co-citations3 shared tech1 shared categoryfood-and-drink
50match
joeschmocoffeeco.com
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50match
elaratea.com
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48match
kengenfoods.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.