Be the answer in Google AND ChatGPT.

Around 15-20% of high-intent product and service searches now happen inside AI assistants instead of Google. For dental, the share is smaller today but growing fast - and the patients using it skew higher-income and more research-driven (cosmetic, implants, Invisalign). When ChatGPT or Perplexity answers "who's a good dentist near me in [city] for implants?", you either get cited or you don't exist.

Xcare Search & AI Visibility makes your practice legible to both classic Google crawlers and the new generation of AI snippet engines: ChatGPT (GPTBot, OAI-SearchBot), Perplexity (PerplexityBot), Claude (ClaudeBot), Gemini (Google-Extended).

Three layers, in order of impact. First, llms.txt - a structured plain-text summary of your practice (services, locations, hours, philosophy, named providers, signature procedures) that AI crawlers preferentially ingest. Second, JSON-LD schema markup on every page (Dentist, MedicalBusiness, FAQPage, Review, Person for each provider) so the same facts are machine-readable in HTML. Third, citation strategy - getting your practice mentioned with consistent NAP (name, address, phone) on the third-party sources AI models pull from: Healthgrades, Vitals, Yelp, ZocDoc, local press.

We also write FAQ content that mirrors the shape of questions patients actually ask AI assistants - long-form, conversational, with named entities and numeric specifics that models can quote directly.

• llms.txt published and maintained at /llms.txt
• Full schema markup: Dentist, MedicalBusiness, FAQ, Review, Person
• Citation hygiene across Healthgrades, Vitals, Yelp, ZocDoc
• FAQ content engineered for AI quotation
• Quarterly visibility audits across all four major AI engines

Quarterly, we run the same 40-60 high-intent prompts ("best dentist for veneers in [city]," "emergency dentist near [neighborhood] open Saturday") across ChatGPT, Perplexity, Claude, and Gemini. We track citation rate (how often you're named) and citation position (first, top three, mentioned anywhere). The goal is top-three citation on at least 40% of relevant prompts inside 6 months.

This is the same methodology we use for our own llms.txt - and the reason our content is showing up in AI answers about "dental growth platform" and "dental marketing software."

Classic SEO is about keywords on a page and links pointing to that page. AI visibility is about facts in a knowledge graph and citations in trusted sources. The two overlap, but optimizing for one without the other leaves rank on the table.

Practical differences: AI engines weight named entities heavily (provider names, procedure names with the right ADA terminology, neighborhood names), they pull from llms.txt and structured data more than from meta descriptions, and they cite a small list of high-trust sources (Healthgrades, Vitals, ADA, well-known local press) far more than the long tail Google uses. The AI visibility playbook is narrower, more factual, and more concerned with consistency across sources than with content volume.