GEO & AI Visibility
Getting cited by ChatGPT, Claude, Perplexity, and Google's AI Overviews — llms.txt, structured-data depth, and the citation architecture that puts you in the answer.
The new front page is an answer, not a list
A growing share of buyers never see ten blue links. They ask ChatGPT, Perplexity, Gemini, or Google's AI Overviews and get a synthesized answer with a few citations. If your business isn't one of those citations, you're invisible at the exact moment of decision — and traditional ranking doesn't guarantee inclusion. Generative Engine Optimization is the work of becoming the source these systems quote.
Why AI engines cite some sources and ignore others
Answer engines favor content they can extract and trust: clear, self-contained passages that answer a specific question; structured data that tells the machine exactly what an entity is; and signals that the publisher is a real, identifiable authority rather than an anonymous page. They reward original information — data, definitions, and first-hand explanation — over content that merely restates what's already everywhere. And much of what they cite is earned off your own site, which means entity clarity and credibility matter as much as on-page polish.
How we build for citation
We structure content into extractable answer blocks, deepen the structured-data layer so entities and authorship are unambiguous, and make the site legible to the crawlers these tools rely on. The goal isn't to game a model — it's to be genuinely the clearest, best-sourced answer to the question, so being cited is the natural outcome. The pieces below explain the tactics, from llms.txt to passage design to the schema that earns the mention.