Your first visibility check establishes a baseline: a set of prompts run against AI models with your brand and competitors in scope. Onboarding can kick this off; you can re-run anytime from Brand Visibility.
What you get
- Visibility score — a rollup of how often and how strongly you appear.
- Per-prompt outcomes — mentioned, preferred, ignored, or competitor-led.
- Narrative clues — how the model describes you when it does answer.
- Gap seeds — candidates for loops (missing proof, weak category claim, etc.).
How to read the first run
Do not optimize the score in isolation on day one. Look for: (1) prompts where you are invisible, (2) prompts where a competitor owns the answer, (3) prompts where you appear but the story is wrong. Those three buckets feed your first loops.
Runtime
Baseline runs use bounded model calls so onboarding and checks finish reliably. Longer multi-model sweeps can follow once the workspace is live.