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65match
2nd-chanceinvestments.com
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60match
hangmenpdx.com
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60match
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60match
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59match
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59match
j3am.com
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59match
greyclyde.com
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0 co-citations4 shared tech1 shared categoryreal-estate-industry
59match
bostonrealestatepartners.com
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55match
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55match
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54match
kenleeconsulting.com
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53match
makproperties.com
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52match
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0 co-citations5 shared tech1 shared categoryreal-estate-industry
52match
apprazrapp.com
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52match
jmscoping.com
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0 co-citations5 shared tech1 shared categoryreal-estate-industry
52match
elemex-canada.com
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0 co-citations5 shared tech1 shared categoryreal-estate-industry
51match
jfsullivaninvestments.com
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0 co-citations5 shared tech1 shared categoryreal-estate-industry
51match
greatestatesusa.com
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0 co-citations5 shared tech1 shared categoryreal-estate-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.