Be the Brand AI Assistants Recommend

GEO is the practice of structuring a brand's content, data and third-party footprint so AI assistants such as ChatGPT, Claude, Gemini and Perplexity retrieve it, understand it correctly, and name the brand when a user asks for a recommendation. Where SEO competes for a position in a list of links, GEO competes to be included in a generated answer the user reads instead of clicking.

AEO targets answer engines that summarise and cite sources — Google AI Overviews, Perplexity, Copilot — and the win condition is having content extracted and cited. GEO targets conversational assistants where the win condition is your brand being named in a recommendation, often with no link at all. AEO is largely about content structure; GEO adds entity consistency and third-party corroboration on top.

Eight to sixteen weeks for retrieval-based visibility. Fixes that affect live retrieval — crawler access, schema, factual corrections, new cornerstone content — can register within four to eight weeks. Changes that depend on a model's training data take far longer and cannot be scheduled, because they only take effect at the next training cycle, which no vendor controls.

No, and neither can anyone else. There is no ranking to buy, no index to submit to and no placement to secure. What can be committed to is measurable improvement in mention rate across a fixed prompt set, tracked monthly. If a vendor guarantees inclusion in AI answers, they are describing something that does not exist.

No. Traditional search still drives the majority of B2B discovery traffic, and generative engines lean heavily on the same web content that ranks well organically. GEO is additive: it protects you in the research layer where an increasing share of shortlisting now happens. The two share infrastructure, so running both costs considerably less than running them separately.

Through a fixed prompt set. We build thirty to a hundred questions your buyers actually ask, run them monthly across four assistants, and record whether you were named, which competitors were named, whether your URLs were cited, and whether what was said about you was accurate. We also segment GA4 referral traffic from assistant domains.

The correction path is to publish the accurate version prominently, mark it up in schema, and get it corroborated by independent third-party sources until retrieval favours the correct information. There is no delete button and no support ticket. This is why factual consistency across your own properties is the first thing we fix — most inaccuracies originate from a contradiction the brand published itself.

Yes, if you want to be retrieved. GPTBot, OAI-SearchBot, ClaudeBot, PerplexityBot and Google-Extended need permission in robots.txt and must not be blocked at CDN or firewall level. A surprising number of sites block them unintentionally through a security plugin default and never discover it. This is the first item in every audit because it is free to fix and total in its effect.

llms.txt is a proposed convention — a plain-text file at your site root listing important pages in a form easy for language models to parse. Adoption by major model providers is not universal or guaranteed. We implement it because it takes under an hour and costs nothing, but we do not present it as a significant lever. Crawler access, schema and factual consistency matter far more.