Generative Engine Optimization (GEO). Audit, optimize, and track what AI engines say about your brand — on demand.
AI search engines reason over content, not just rank pages. GEO is the discipline of making your content easy for LLMs to cite — different from traditional keyword SEO.
Learn what ChatGPT and Perplexity actually look for when choosing sources, and how to structure content so you get cited — not just crawled. ChatGPT SEO and Perplexity SEO are different disciplines; we cover both as part of broader AI search optimization.
AEO is the broader category — optimizing for any answer engine. Learn the overlap with GEO and what tactics carry over from traditional SEO.
A new standard for how AI crawlers read your site. Set it up right and make your content machine-readable for the agents that matter.
Paste a URL to audit, or ask an open-ended GEO question. The agent scopes the task before running.
The agent checks structured data, content clarity, citation-worthiness, llms.txt, and how well your content actually gets picked up by AI engines.
A structured report — not a checklist. You get the why, the priority, and example copy for each recommendation.
Re-run the audit after changes, or track how your mentions in ChatGPT and Perplexity evolve week over week.
LLM optimization is the practice of making your content easy for large language models (ChatGPT, Claude, Perplexity, Gemini) to retrieve, reason about, and cite. It overlaps with SEO but emphasizes clarity, structure, and factual density over keyword density.
GEO is the specific subset of LLM optimization focused on generative answer engines — Perplexity, ChatGPT Search, Google AI Overviews. The goal is to get cited in the generated answer, not just to appear in a link list.
Traditional SEO optimizes for a 10-blue-links ranking. GEO optimizes for being a source that an AI decides to cite. Things that matter more: clear factual claims, clean structure, canonical answers, and external corroboration. Things that matter less: exact-match keywords.
ChatGPT Search prefers sources that are clear, factual, well-structured, and widely corroborated. To optimize for AI search: publish canonical answers, use schema markup, have a clean robots.txt that allows GPTBot, and earn citations from other high-authority sources.
Perplexity rewards original, well-sourced content with clear citations. If your content itself cites primary sources cleanly, you're more likely to be cited back. Perplexity also respects content freshness more than ChatGPT does.
llms.txt is a proposed convention (like robots.txt) that tells LLM crawlers how to navigate and prioritize your content. It's a plain-text summary of your site optimized for machine consumption. Not yet a standard, but increasingly adopted.
Yes — for now. Most traffic still comes from Google's classic results. Treat GEO as an additional discipline, not a replacement. The good news: many GEO practices (clear structure, factual claims, strong citations) also help classic SEO.
AEO is a broader umbrella that covers any answer engine — Google's featured snippets, voice assistants, AI chatbots. GEO is the AI-specific subset. Both overlap on structured content, schema markup, and canonical answers.
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