Buyers stopped Googling. They ask ChatGPT — and right now it recommends the competitor. Nobody could measure that, let alone fix it.
Aureo needed to turn a fuzzy question — “what does AI say about us?” — into a measurement with a sample size, and then into a to-do list. 15 queries × 3 engines × 3 samples, every week, with share of voice, mention rate, average position and citation presence. Plus the part monitoring tools skip: which source AI cites instead of you, and which page to publish. Built for agencies reporting on Monday.
Queries run through three engines, three times each; unusable answers are excluded and n drops rather than the number lying. Every figure in the product carries its sample count.
Share of voice, mention rate, average position, citation presence — trended per query, per engine, per week, with a “named vs recommended” distinction.
The citation-gap engine names the domain AI leaned on instead of you and the comparison page to publish — then proves the fix moved the line.
Ten client brands from one pool of 300 queries, white-label PDF reports, alerts on share-of-voice swings.
A documented REST API with scoped keys, an MCP server so Claude or Cursor can ask “which client slipped this week?”, and signed webhooks into Slack.
A fuzzy question becomes a weekly measurement with a sample size — and the exact page to publish to move it.