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AI Visibility Check
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No login. We fetch your homepage once and store nothing.Summary free, full report after your email.
What the check looks at · 5 components
What the check looks at
You enter your domain and brand name. The check reads your homepage, derives your category from it and asks eight questions the way a customer would ask an AI assistant. Every answer is scored on mention, citation and competition.
01
Mentions per engine
Six buyer questions without your brand name — 'what are the best …', 'which … would you recommend' — go to multiple AI models. For every answer you see whether your brand is named, per engine, because the engines differ more than you would expect.
02
Citations of your domain
Being named is one thing; being linked as the source is the prize. The check looks for your domain in the answer itself. That tells you whether engines know your pages or only your name.
03
Share of voice against competitors
Every brand named in the answers is counted. So you see not just whether you are missing, but who stands in your place — often not the competitor you would name yourself.
04
Brand recognition
Two questions contain your brand name: 'is … trustworthy?' and 'what is …?'. They show whether an engine knows your brand at all, or honestly says it has no information. That is the foundation all other visibility rests on.
05
Concrete next steps
Based on the pattern — not named, named but not cited, not recognised — you get prioritised steps: which pages you are missing, which facts need to be citable and what to do about robots.txt and llms.txt.
Why it matters · the short version
Why an AI answer is not a search result
An AI answer has no page 2. You are in it, or you do not exist.
More and more buying decisions start with a question to ChatGPT, Gemini or Perplexity instead of a Google search. The answer is one text with a handful of brands at most. Whoever is in it gets considered; whoever is missing does not exist for that customer. Rankings tell you nothing about this — position 3 in Google can go together with zero mentions in AI answers.
Engines pick brands based on what they meet in text: comparisons, guides, reviews, news and the brand's own pages. They favour sources that answer a question directly, give facts that can be checked and call a brand by the same name everywhere. You can influence that, but only once you know where you stand today.
This check is a snapshot, not a verdict. We ask a fixed set of questions to model APIs without live web search, and AI answers vary per run. The same question can produce a different brand tomorrow. So use the result as a direction: which questions you are missing from, which competitor keeps coming back and whether your brand is recognised. How exactly we measure is on the methodology page.
Methodology · what is what
What we decide, measure and estimate
Every number in the result belongs to one of these three. The report itself says which, per item, so you know what to lean on.
Assessed by our decision model
A judgement with a probability behind it: certain, likely or uncertain. Not a fact, but traceable — the same input gives the same judgement, and the certainty is always shown.
Whether an answer names your brand, how it talks about you (positive, neutral, negative) and where in the answer you appear. Plus, upfront: whether it is clear who you are and what you do.
Measured
What we literally fetched or counted: HTTP status, HTML, robots.txt, sitemaps, feeds and search results. If it is not there, we say so.
The answers themselves, whether your domain is literally cited as a source, your schema markup, your llms.txt and the AI rules in your robots.txt.
Estimated
Models and rules of thumb: search volumes, click rates, expected return. Good enough to prioritise with, not to budget on.
Visibility and share of voice: percentages calculated over a sample of questions and engines at one moment in time.
Simulated. When no decision model, provider or cluster is available — or the daily ceiling for the free tools is reached — the tool keeps running on deterministic example data. That is labelled on every item it touches.
Good to know
Questions about AI Visibility Check
From check to system
One measurement shows the gap. Traze closes it, every week.
The AI Visibility Check is a snapshot of eight questions. Traze fixes a prompt set per topic, measures six engines weekly, sees which sources do get cited and turns every missed mention into a page that makes the difference — written, published and tracked, with you in the loop.
Keep going · next check
Done? Check the rest.
Every tool answers one question. These two follow on from what you just saw.
One check is a snapshot
Traze is the loop.
Traze researches, writes, publishes and optimises the content that gets you found in Google and in AI answers — automatically, with you in the loop. See pricing or book a demo.