AI visibility begins with evidence a brand can inspect: whether its public identity, facts and technical pages are clear and accessible. AEO.METRY scans that foundation; live AI answers require a separate human investigation.
Public pages, crawlability, entity naming, organization markup and corroborating references can show whether a machine-readable foundation is coherent. They can also expose conflicting names, unavailable pages or incomplete structured data that make interpretation harder.
An AEO.METRY Scan is a deterministic assessment of public-web, entity, technical and structured-data signals. It records observable evidence and implementation gaps; it does not send prompts to answer engines or infer a live mention, recommendation, citation, sentiment or rank.
If the question is “What does an engine say for this prompt now?”, public signals are not an answer. Request a human-led Deep AI Engine Investigation to document selected live outputs and their conditions. Neither path guarantees future model behavior.
Assess your public foundation, then choose a manual investigation when live engine evidence is required.
Start an automated scan