AI discoverability depends partly on whether public information is accessible and unambiguous. That foundation can be assessed deterministically, while actual live discovery must be investigated manually.
Accessible pages, stable canonical information, descriptive content, structured data and consistent entity details give systems material to parse and compare. They are useful inputs, not proof that every system has ingested or will use them.
Check whether an organization’s name, URL, services and locations agree across its own pages; whether important pages can be accessed; and whether markup matches visible content. A deterministic scan makes those checks reproducible.
An automated Scan never queries ChatGPT, Gemini, Perplexity, Claude or another live answer engine. If a decision depends on observed outputs, citations or recommendations, commission a Deep AI Engine Investigation.
Start with an evidence-based assessment of the information you control.
Start an automated scan