How GEO Works Technically
AI search systems generate answers by retrieving information from their training data and from real-time retrieval systems. A brand appears in a generated answer when two conditions are met: first, the AI system has sufficient entity confidence to identify and describe the brand accurately; second, the brand's content and citations appear in the retrieval corpus used to generate the specific answer.
GEO optimization addresses both conditions simultaneously. Entity confidence is built through structured data and citation normalization. Retrieval corpus presence is built through content with high information gain scores, editorial placements in authoritative publications, academic-style citations, and the llms.txt infrastructure that explicitly describes the entity to AI crawlers.
For the explanation of what GEO is, read What Is GEO SEO. For the Dubai-specific GEO context, see GEO Expert Dubai.
The llms.txt Component
The llms.txt file is one of GEO's most direct technical interventions. Placed at the root of the domain, it is a plain-text file written specifically for AI crawlers. It describes who the entity is, what expertise they cover, what their key credentials and proof points are, and which pages are most relevant for each topic. AI systems like ChatGPT, Perplexity, and Bing AI read this file when crawling the domain and use it to build entity understanding.
The GEO optimization service includes writing the file, maintaining it as credentials emerge, and monitoring whether AI systems are reading and reflecting its content in their recommendations. For a related explanation, read How to Appear in ChatGPT and Perplexity Answers.