When a patient asks ChatGPT for a dentist, is your practice in the answer?

Your practice can sit at the top of Google Maps for “dentist near me” and still be invisible when a new patient asks an AI assistant who to see. The assistants aren't reading your rankings. They're leaning on the sources they were trained on and the pages they can pull at answer time — directories, review platforms, dental and health listing sites, roundup articles, local press.

If those sources are thin, stale, or inconsistent about your practice — old address, missing specialties, a handful of reviews while the practice down the street has three hundred recent ones — the model reaches for a practice it can describe with more confidence. That's the gap. It's fixable, but only once you can see it.

How the work goes

First we measure. We run the prompts a real patient types — “dentist near Coral Gables,” “Invisalign in South Miami,” “emergency dentist Boca Raton” — across ChatGPT, Claude, Perplexity, and Gemini, and record who gets named, who is named first, and who is missing. Screenshots, dated.

Then we explain the gap: which specific practice is getting recommended and which sources the answer is leaning on to describe them. From there the work is specific and unglamorous — citation and directory consistency, structured data on your site, review depth and recency where it counts, and content that answers the question the way a patient asks it. Then we run the same prompts again on the same four platforms and show you what moved. Some months the change is obvious. Some months it isn't, and we say so.

What we don't do is promise a first mention. No agency controls what a generative model says. We measure it, explain it, work it, and re-measure it.