<?xml version="1.0" encoding="UTF-8"?><oembed><type>video</type><version>1.0</version><html>&lt;iframe src=&quot;https://www.loom.com/embed/5ff405847bb74171b5aae7efeefc8e96&quot; frameborder=&quot;0&quot; width=&quot;1662&quot; height=&quot;1246&quot; webkitallowfullscreen mozallowfullscreen allowfullscreen&gt;&lt;/iframe&gt;</html><height>1246</height><width>1662</width><provider_name>Loom</provider_name><provider_url>https://www.loom.com</provider_url><thumbnail_height>1246</thumbnail_height><thumbnail_width>1662</thumbnail_width><thumbnail_url>https://cdn.loom.com/sessions/thumbnails/5ff405847bb74171b5aae7efeefc8e96-9255259ab1a84b45.gif</thumbnail_url><duration>189.275</duration><title>Local First GEO for Elective Healthcare 🤖</title><description>Today I walked you through what local-first generative engine optimization, GEO, looks like. I shared an audit report for ReviveMD, our early pilot customer, an eight location MedSpot based in California, where we computed visibility across 1,600 AI answers. We start with brand level citations in AI engines like ChatGPT, Gemini, and Perplexity, then go deeper because each location is its own market and competes differently. We run realistic high intent prompts and measure how AI recommends your clinics versus competitors. Our AI agents can implement fixes and create new pages, and I did not request any action from viewers.</description></oembed>