The discipline of making sure a brand is correctly represented in AI-mediated search — ChatGPT, Claude, Perplexity, Gemini, Google AI Overviews, Bing Copilot.
Generative Engine Optimization (GEO) is the discipline of making sure a brand, product, or topic is correctly represented in the AI engines that increasingly mediate buyer attention — ChatGPT, Claude, Perplexity, Gemini, Google AI Overviews, Bing Copilot, and the next wave of AI-mediated search and discovery surfaces. GEO is to AI search what SEO was to traditional Google search — the practice of structuring content, signals, and citations to influence how a brand appears in the engine's outputs.
GEO matters because AI engines are increasingly the answer layer between users and the open web. A user asking ChatGPT "what's the best AI agent platform for healthcare" or Perplexity "what is decision intelligence for communications" gets an AI-generated answer that may or may not mention a given brand, may or may not represent it correctly, and may or may not link to its actual content. The discipline of GEO is shaping that AI-engine answer in ways that traditional SEO doesn't address. Common GEO tactics include: structured-data markup tuned for AI ingestion, llms.txt and llms-full.txt files, FAQ-style content optimized for direct citation, third-party citation density across authoritative sources, and entity-graph completeness via cross-referenced schema.org markup.
AI search is now a material share of buyer discovery for many enterprise categories. Brands that aren't optimized for AI engines are increasingly invisible at the discovery layer regardless of how strong their traditional SEO is.
An enterprise software vendor that gets cited correctly by ChatGPT when users ask about its product category
A legal-tech company that appears in Perplexity's answer when users ask "what's the best AI tool for contract review"
A consultancy that gets quoted by Claude when users ask about its specific methodology
A B2B SaaS company that's mentioned in Google AI Overviews for the relevant buyer queries
GEO Audit (Huper Technology's third product, in build) is the GEO measurement and remediation platform. Inputs: a brand or domain. Outputs: a measurement of how the brand is currently cited (or not cited, or misquoted) across AI engines, plus a prioritized remediation plan covering structured data, content architecture, llms.txt curation, and external-citation building. GEO Audit's category is GEO; the product is the measurement and remediation tool. (Internal codename: Ezra.)
SEO targets the traditional Google search results page — link-based ranking, click-through to the brand's site. GEO targets AI-engine outputs — citation-based ranking, often with the user staying inside the AI engine. The tactical overlap is partial; some traditional SEO best practices (structured data, content depth) help with both, but GEO has its own dedicated practices (llms.txt, AI-engine specific citation patterns, entity-graph completeness for AI ingestion).
Closely related but not identical. AEO (Answer Engine Optimization) emphasizes optimization for direct-answer surfaces like Google AI Overviews. GEO (Generative Engine Optimization) is the broader category covering all AI-engine surfaces (ChatGPT, Claude, Perplexity, Gemini, plus the answer-engine surfaces). The two terms are often used interchangeably in industry coverage; precision matters mostly in technical or research contexts.
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