AI search visibility
AI search visibility work grounded in clear content, discoverable pages and reliable business facts. Improve the foundations that search and answer systems can actually use.
An answer system cannot give a useful account of a business whose site hides the service, audience and supporting facts. We start with what a buyer actually needs to know: what you offer, when it fits, what the limits are and how a claim can be checked. Clear page structure and crawlable content matter, but no special file or schema can force inclusion in an AI answer.
The plan is anchored to published facts and the pages that serve real customer questions.
Review which priority pages are accessible, indexable and readable in their rendered form. Check canonical choices, internal routes and whether important answers are trapped in images or interactions.
Explore Discovery and renderingClarify definitions, scope, comparisons and decision points. Add first-hand evidence only when the business can support and approve it; a fabricated case or generic paragraph weakens trust.
Explore Specific, supported answersTrack reported citations or referrals where a source is available, alongside search enquiries and direct customer questions. Record uncertainty instead of presenting an invented AI visibility score.
Explore Measured observationChoose a question a qualified buyer might ask, such as how an integration handles failed orders. We inspect the existing answer, related pages and any technical obstacle to discovery. The revised page should help the buyer even if no answer engine refers to it. We then verify the published content and observe available reporting over time, adjusting the explanation when the offering or underlying facts change.
Different search and assistant products select sources and present answers differently, and their behavior changes. We cannot guarantee a citation, recommendation or position. We do not claim that an llms file, a mass of near-duplicate pages or unsupported structured data creates authority. Business credentials, partner status and customer outcomes need evidence before they become public claims.
The record shows the pages improved, source facts supplied, technical changes made and observations that remain uncertain. Your editors can update a service, policy or proof point through the normal publication process. Our broader SEO service covers the search journey around those answers.
Some of the teams we have worked with.
Across talent, fitness, mobility, payments and local commerce.No. Use structured data only when it accurately describes visible content and fits the search provider's supported features. Helpful, accessible pages and supported facts are the foundation; a schema label cannot make an unsupported claim true.
We identify the limited reports and observable referrals available for the relevant products, then record their scope. We do not treat one manually observed answer as a stable ranking or convert an uncertain citation into a promised lead forecast.
EXPLORE
Google's AI search features use the foundations of search eligibility: accessible, indexed pages with useful visible content. There is no special AI schema or text file that guarantees inclusion.
Explore How Google and AI search discover a websiteServiceTechnical SEO for crawlability, indexation, page structure and performance. Turn audit findings into changes that developers can implement and verify.
Explore Technical SEOGuideMeasure search and AI visibility with observed search reports, relevant referrals and business outcomes. A sampled prompt result is a narrow observation, not a reliable market-share estimate.
Explore Measuring search and AI visibilityService hubSEO, paid search, analytics and conversion work built around your offer and the customers you want to reach. Connect acquisition with what happens after the visit.
Explore Search & digital marketingShare what exists today and what you want to change. We can discuss the scope, dependencies and a practical way forward.
