Do AI engines confuse your brand with someone else?
When a brand shares its name with another company, person, or product, AI engines can describe the wrong one. Brand Disambiguation checks whether ChatGPT, Claude, Perplexity, and Gemini link your name to the right entity.
Mentioned, yes. But is it the right you?
This is Named Entity Disambiguation (NED). Radar reads your real identity from your site and llms.txt, asks each AI engine an open question about your brand, and judges whether the answer describes you or a different thing that happens to share your name.
An entity collision means buyers asking an AI about you get details about an unrelated company, quietly redirecting trust and traffic away from you.
Why entity disambiguation matters
Citation tracking asks whether AI mentions you. Disambiguation asks whether the AI mentioning you is describing the right you. A strong citation score still loses if the engine attaches your name to someone else.
“I wanted to see how AI describes my three sites and how to improve those answers. Radar showed me exactly what AI models think about our brand. For example, it caught ChatGPT confusing Side Quest HQ with a tabletop gaming community. That pushed me to clearly define what we do, what we sell, and who we serve. I updated our website to match, and now AI has a precise definition that sets us apart from other brands with the same name.”
Featured clients received complimentary audit credits for taking the time to give feedback.
What the full check does.
4 checks, each with a plain-English reason it matters. Every one maps to a line in the report.
Your verified identity
Reads your homepage, about pages, and llms.txt to extract who you actually are: category, products, and leadership.
4 AI engines
ChatGPT, Claude, Perplexity, and Gemini each get an open identity question about your brand.
Entity collisions
A judge compares each answer to your real identity and names the different, same-named entity it described instead.
Fixes that reclaim you
Severity scoring plus the schema and llms.txt moves that make the correct entity dominate.
Built on our own research
We hit this ourselves: a short, common brand name that other companies also use. The schema and llms.txt moves in the report are the ones that made the right entity win for us.
Want the full picture across four AI engines?
Radar orchestrates 13 AI visibility audits in staged batches: crawl access, llms.txt, structured data, brand citations, and more. It then surfaces cross-tool conflicts and ships a prioritized action plan for your domain.
Run it on your brand. See what AI can read.
One-time $5, no subscription, report on this page. When you want the whole picture, Radar runs all 13 audits in one pass.