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The Keitner Group | Keller Williams Referred Urban | PLACE — 18 websites ranked by shared content topics, category and on-page relevance.

Each result shows its full tech stack, contacts and AI-policy — not just a name · Browse all sites in Real Estate Buying And Selling →

DomainMatchTitleCountry/LangCategoryAI filesContactAI-protection
rentzteam.com 84 match
2 shared topics
The Rentz Team | Keller Williams Realty Preferred | PLACE en real-estate-buying-and-selling robotsllmsaihumans emailphone none
darwaldenteam.com 84 match
2 shared topics
The Walden Team | Keller Williams Realty-Alaska Group | PLACE United States~ en real-estate-buying-and-selling robotsllmsaihumans emailphone none
everythingprescott.com 83 match
2 shared topics
The Bergamini Group | Keller Williams Arizona Realty | PLACE United States~ en real-estate-buying-and-selling robotsllmsaihumans emailphone none
danmauz.com 83 match
2 shared topics
The Mauz Group | Dan Mauz | Keller Williams Realty United States~ en real-estate-buying-and-selling robotsllmsaihumans emailphone none
htxhomes4sale.com 82 match
2 shared topics
HTX Realty Group | Austin Jackson | Keller Williams Realty United States~ en real-estate-buying-and-selling robotsllmsaihumans emailphone partial · 10
danmarpropertiesgroup.com 82 match
2 shared topics
Danmar Properties Group | Keller Williams Flagship | PLACE United States~ en real-estate-buying-and-selling robotsllmsaihumans emailphone partial · 10
keating-group.com 82 match
2 shared topics
Keating Group | Jim Keating | Keller Williams Realty Centre United States~ en real-estate-buying-and-selling robotsllmsaihumans emailphone none
designsbytdg.com 81 match
2 shared topics
The Davenport Group | Rachel Davenport | Keller Williams Realty Partners United States~ en real-estate-buying-and-selling robotsllmsaihumans emailphone none
bruinsrealtygroup.com 81 match
2 shared topics
Bruins Realty Group | Shannon Bruins | Keller Williams Realty United States~ en real-estate-buying-and-selling robotsllmsaihumans emailphone partial · 10
hhgre.com 80 match
2 shared topics
Harber Home Group | Matt Harber | Keller Williams Tacoma United States~ en real-estate-buying-and-selling robotsllmsaihumans emailphone none
brodiecapitolrealtygroup.com 80 match
2 shared topics
Brodie Capitol Realty Group | Hykeem Brodie​ | Keller Williams United United States~ en real-estate-buying-and-selling robotsllmsaihumans emailphone none
annsenn.com 80 match
2 shared topics
Ann Senn Real Estate Group | Ann Senn | Keller Williams Green Bay United States~ en real-estate-buying-and-selling robotsllmsaihumans emailphone none
detricewjohnson.com 80 match
2 shared topics
Detrice Johnson | Keller Williams Realty​ United States~ en real-estate-buying-and-selling robotsllmsaihumans emailphone partial · 10
mccadneydreamhome.com 79 match
2 shared topics
McCadney Dream Home Team | Keller Williams St. Louis | PLACE en real-estate-buying-and-selling robotsllmsaihumans emailphone partial · 10
mcrealtygrouptexas.com 79 match
2 shared topics
McRealty Group | Ryan McDaniel | Keller Williams Heritage​ en real-estate-buying-and-selling robotsllmsaihumans emailphone partial · 10
annarborrealestatesearch.com 79 match
2 shared topics
The Bouma Group, Realtors | Martin Bouma | Keller Williams United States~ en real-estate-buying-and-selling robotsllmsaihumans emailphone none
mcrealtor.com 79 match
2 shared topics
MC Realty LLC | Keller Williams Everett United States~ en real-estate-buying-and-selling robotsllmsaihumans emailphone partial · 10
annakintown.com 79 match
2 shared topics
Anna Kilinski | Keller Williams Realty Intown Atlanta United States~ en real-estate-buying-and-selling robotsllmsaihumans emailphone none

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.