Get named by AI

Generative engine optimization is getting a brand named, cited and described correctly across the six engines that now answer buyer questions directly: ChatGPT, Perplexity, Gemini, Claude, Google AI Overviews and Google AI Mode. The work has three parts. Control what those engines say about you, win the buyer questions themselves, and earn presence in the sources the engines already trust. They only compound together, which is why we run them as one program.

GEO optimizes what an engine cites inside a generated answer. SEO optimizes what ranks as a link on a results page. The two overlap heavily, because the pages that already rank and get linked are usually the pages an engine cites too. GEO also chases questions buyers ask an assistant that never reach a keyword tool, because nobody types them into a search box. AEO, answer engine optimization, is the earlier name for the same target: a direct answer surface such as a featured snippet or a voice result. GEO is the term that stuck, and it covers more ground: any engine that synthesizes an answer from multiple sources, whether that answer sits in a chat window, a results page or an AI overview. We use GEO on this page because it is the frame broad enough to cover all six engines.

One that takes responsibility for what the engines say about you, not just for what you publish. In practice that means a fixed set of your buyers' real questions, run across every engine on a schedule, a roadmap built from where those answers actually fail, and the content and authority work to change them. We run search and AI answers as one program rather than three retainers, and the founder runs every engagement.

Engines assemble answers out of pages that already rank, get linked and get mentioned, so most good SEO work already feeds GEO. What is genuinely new is the conversational long tail: high-intent questions buyers ask an assistant that never surface in a keyword tool, because nobody types them into a search box. That is the part worth new money, and it is where we hunt. We treat AI SEO and GEO as one system.

Against a fixed prompt set, and fixed is the whole point. We call it the Fixed Set Method: the real questions your buyers ask, gathered from sales calls, support tickets, community threads and keyword data, then held constant so every measurement afterwards is comparable to the last. We report AI share of voice per engine, mention share, answer accuracy and AI referral traffic, several runs each because engines are non-deterministic. If the questions change, the number cannot be compared.

Usually, and not by patching the answer. Nobody can edit a model. We find the pages the engine cited when it got you wrong and rebuild the signal there. A wrong answer is rarely a typo. It is what an engine concludes when the stale version of a fact is easier to retrieve than the current one. Fix that condition and the whole cluster of related errors goes with it.

Because the fields engines get wrong most often are the ones that carry legal weight here: incident history, token supply, governance, fee schedules, delisted assets and invented licensing claims. Misstate a hotel check-in time and somebody is annoyed. Misstate a custody model or a regulatory status to every prospect who asks, and you have a compliance exposure nobody on your team can see, in a channel with no impressions report and no complaints inbox.

It is associated with being in the conversation at all, which is the strongest relationship we have managed to measure. In our own study of 45 crypto and fintech brands, third-party presence predicted whether a brand appeared in AI answers, but not the rate at which engines cite the brand’s own site once brand size was held constant. We sell the first claim and refuse the second, because that is where the data landed.

No. We deliver strategy, architecture, templates and detailed briefs; your team or your writers execute them. In crypto and fintech that keeps your voice and your compliance review inside your business, where it legally belongs, and it keeps us on the part that needs a specialist.

Retainers start at $7,500 a month, month to month after the first 90 days, scoped to a set number of tracked prompts, content briefs and outreach targets. Search and AI answers run as one program, because what moves whether an engine names you is the same authority and content work that moves search. Every tier is published on our pricing page. If you only want to watch what the engines say rather than change it, Answer Monitor is $1,500 a month. And if you are not ready for a retainer, start with the $7,500 one-time Diagnostic: your real buyer questions run through every engine, with a 90 day roadmap at the end.