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AI SEO — also called AI search optimization or Generative Engine Optimization (GEO) — is the practice of structuring your website so AI search engines like ChatGPT, Perplexity, Google AI Overviews, Gemini, and Bing Copilot can read, trust, and cite your business in their answers. It overlaps with traditional SEO (a page still has to be crawlable and authoritative) but adds passage-level answer formatting, schema markup, llms.txt configuration, and entity signals tuned for how language models extract and attribute information.

Traditional SEO optimizes for ranking a blue link in a list of results. AI SEO optimizes for being quoted inside a generated answer. The foundations are shared — crawlability, page authority, and clear content help both — but AI engines reward different signals: answer-first paragraphs under question-style headings, FAQPage and Speakable schema, a configured llms.txt file, and an entity graph (Organization schema, sameAs links) that lets a model recognize your brand as a topic authority. We run both disciplines together rather than treating them as separate channels.

GEO is the formal name for optimizing content to appear inside AI-generated responses. Where SEO targets search engine result pages, GEO targets the answer layer of generative engines. In practice it means engineering pages so a model can lift a clean, self-contained passage and cite it — short factual answers immediately under headings, structured data the model can parse, and authority signals that make your source trustworthy enough to quote.

No. Anyone guaranteeing AI citations or AI Overview placement is overselling — these systems are non-deterministic and change frequently. What we commit to is the work that makes citation possible and measurable: schema and llms.txt deployment, answer-first content restructuring, entity-signal building, and monthly tracking of where and whether your brand is being mentioned across the major AI engines. We report what is actually happening rather than promise a fixed outcome.

Yes. AI engines like ChatGPT, Perplexity, and Bing Copilot pull candidate sources from a live search index — if you do not rank in traditional search for a query, the model usually never sees your page as a citation option. Strong technical and on-page SEO is the prerequisite, not a replacement. AI SEO is the layer on top that converts a ranking page into a citable one. Most engagements run both in parallel.

A typical engagement starts with a GEO and SEO audit to baseline your AI citation readiness and traditional ranking health. From there we deploy the technical foundation (llms.txt, JSON-LD schema including FAQPage and Speakable, AI crawler access), restructure priority pages into answer-first format, build entity and topical authority signals, and set up monthly AI visibility tracking that reports named brand mentions across ChatGPT, Perplexity, Gemini, and AI Overviews. Scope and pricing are based on your site size and content needs, not a fixed package.

We optimize for the engines that drive measurable referral and citation activity: Google AI Overviews, ChatGPT search, Perplexity, Google Gemini, and Microsoft Bing Copilot. Because several of these share retrieval indexes (ChatGPT and Copilot both lean on Bing), the underlying work compounds — improving your structure and authority for one engine usually lifts visibility across the others.