See the version of you that machines describe
You have a machine-readable double. When someone asks an AI assistant about you or your business, the assistant answers with a confident summary, and that summary, not your website, is increasingly what shapes the first impression. This free tool asks an AI model what it believes about you and shows you the result, including the mistakes, so you can finally see the reflection everyone else is starting to see.
What you get back
- What AI thinks it knows: the profile it would give a stranger who asked about you.
- Uncertain or possibly wrong: facts it is unsure about, out of date, or may have invented.
- Same-name confusion risk: how easily it could mix you up with someone else.
Why the machine view matters now
More and more journeys begin with an AI answer rather than a search page. A customer asks an assistant whether your shop is any good, a recruiter's tool summarises a candidate, a shopping agent checks whether a service exists. If the AI gets your hours wrong, invents a service, repeats an old price, or confuses you with a different person of the same name, that error travels into real decisions, silently. Seeing it is the first step to fixing it.
If AI got you wrong, or knows nothing
Both outcomes are worth acting on. AI systems learn from clear, consistent, authoritative information, so the fix is to make yours easy for machines to read: keep your name, role and key details identical across your website and profiles, add structured data and, for a website, an llms.txt file so assistants get a clean summary, and check how citable your pages are with a GEO audit. You cannot rewrite a model directly, but you can steadily shape what it learns.
Honest about the limits
This samples one AI model once. Different assistants answer differently and every model changes over time, so treat the result as an indicative snapshot, not a definitive report. The model is told to admit uncertainty rather than invent details, but no tool can fully stop AI from being confidently wrong, which is exactly why seeing its answer is so useful. This is part of MirrorCheck: tools for seeing how the machines see you.