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Build a fixed battery of buyer-intent questions for your service, market, and geography.
AI Visibility
Sectair checks the questions your buyers actually ask across ChatGPT, Claude, Perplexity, and Gemini. You get the transcripts, a named-or-not-named baseline, and a practical plan for the public footprint those tools can retrieve.
The Question
AI answers often draw from public websites, directories, profiles, and other sources they can retrieve. If those sources are thin, unclear, or inconsistent, the answer may be a national tool, a distant competitor, or nobody at all. AI Visibility shows what is happening before deciding what to change.
Build a fixed battery of buyer-intent questions for your service, market, and geography.
Run each question more than once, keep the transcripts, and score only what was observed.
Prioritize the public pages, profiles, facts, and citations the engines may retrieve.
The Monthly Read
The instrument stays deliberately plain. No mystery score and no claim that one result controls the next. You see what was asked, what came back, what changed, and what is worth fixing.
Sectair as Client One
The initial baseline recorded 34 filled baseline cells for questions about who to hire for AI automation and lead help in Telluride and southwest Colorado. Sectair was named in 0. Of those cells, 24 live consumer-surface checks came from Perplexity and ChatGPT; 10 were a separately labeled Claude training-knowledge data point, not queries against the Claude consumer product. The remaining ChatGPT checks and Gemini were not yet complete at freeze.
Sectair was absent from every completed check. Every firm that was named in the live Perplexity runs was cited from its own website or an agency-directory listing.
A stronger retrievable footprint gives the engines more relevant evidence to work with. It does not make a particular answer predictable.
Sectair improves its own public footprint first, then repeats the same questions. Any movement will be labeled by date, engine, access method, and transcript.
Founding Plans
Founding prices are locked for 12 months. If the report and action plan do not ship in a given month, that month is refunded.
You or your web person handles the changes. Sectair supplies the measured read and the order of work.
Sectair handles the approved footprint work as well as the monthly measurement.
Founding Authority is capped at eight clients because Sectair completes the work personally. No plan promises naming, ranking, citation, or a particular engine outcome.
Best Fit
Realtors, lodges, outfitters, galleries, and other owner-led businesses whose customers ask AI for local recommendations.
Consultants, speakers, and authors whose expertise exists, but is scattered across a site, profile, talks, and old mentions.
A new business with no clear offer, anyone looking for manufactured reviews, or anyone who needs a promise about rankings or referrals.
Measure the answer. Keep the transcript. Improve what can actually be found.
AI Visibility is not a story about controlling an engine. It is a disciplined way to see whether your business appears, correct what is wrong, and strengthen the public evidence that supports accurate retrieval.
Bring the business name, the market, and the questions customers ask before they hire.
FAQ
Sectair runs a fixed set of buyer-intent questions across ChatGPT, Claude, Perplexity, and Gemini, more than once, and records whether the business was named. Transcripts are kept. Results are counts and presence bands, not an invented score.
No. No one controls what an AI engine will name, rank, or cite. Sectair can measure the current answer and improve the public footprint those engines may retrieve.
For $150 per month, Sectair runs the monthly checks, provides a transcript-backed evidence report, notes anything wrong or stale, compares the result with the prior month, and gives a short action plan.
For $500 per month, Founding Authority includes the monthly evidence report plus Sectair’s work on approved site structure, schema, service and answer pages, Google Business Profile guidance, llms.txt, and relevant directory or community citations.
It is adjacent, but the evidence is different. Traditional search visibility and AI retrieval can overlap. AI Visibility measures named and not-named answers on specific AI surfaces, then works on the public sources those tools can retrieve.