The visibility scorecard
Which assistants cite us on our top buyer questions, and who they cite instead.
It fires real buyer questions at the live AI assistants and records who gets cited, reads share of voice from the mention index, audits the site for citability, and returns a scorecard with the prioritized moves that win mentions.
Real buyer questions put to the assistants, with the brands each answer favored recorded per model - what actually happened, per question.
The mention index read for who owns the category’s answers, and how that share is moving.
Crawler access, structure and the specific blockers that keep pages out of AI answers.
The questions your buyers ask, mined for the answers nobody is giving well yet.
Which assistants cite us on our top buyer questions, and who they cite instead.
Build the AI-visibility strategy for the domain: ranked moves grounded in observed failures.
A competitor owns the "best in category" answer - find why, and the move that changes it.
What comes back: A per-model scorecard and ranked actions, each grounded in a specific observed failure.
Each run reserves budget before it executes and settles after - the cap is enforced by the ledger, never advisory.
Numbers come from tool output only, and every finding cites the capability that surfaced it.
Anything that spends, publishes or reaches out routes through your approval policies before it moves.
The console for teams, REST with an API key, MCP inside your assistant - the same agent on the same meter.
Every workspace ships with all eight agents and the full capability stack behind them. The first mission runs minutes after signup.