AI visibility monitoring
Tracks mentions, citations, and share of voice across a curated or tracked set of prompts. It answers an essential question: do you appear?
Views is a decision workspace for people who need more from AI than a quick answer. Bring selected models into one Situation Room, compare the way they describe the same subject, and decide what deserves your attention.
Join the private previewAI visibility is valuable when you need to know whether you appear in tracked prompts. Views begins when the work needs a closer reading: what leading models are saying about a specific subject, why their narratives align or split, and what deserves human review before an answer becomes a decision input.
Tracks mentions, citations, and share of voice across a curated or tracked set of prompts. It answers an essential question: do you appear?
Asks a different question: what are leading models saying about this exact subject, in this context, now? Views keeps the responses together so a person can inspect framing, disagreement, confidence, and time.
Inside every Situation Room, a dedicated Judge reviews facts, chronology, and key claims across the panel. It surfaces contradictions, unsupported assertions, stale context, and false consensus - the signals simpler monitoring can flatten into noise.
It does not replace human judgment. It shows where human judgment is needed.
A Situation Room is not a one-shot comparison. It is the place to keep working until the picture is clear.
Start with the question, document, market, company, or narrative that matters now.
Keep selected model responses visible instead of flattening them into a single answer too soon.
Discuss the issue with the panel over multiple turns, add fresh context, and challenge an assertion.
Use the Judge to bring claims, chronology, and disagreement back into focus.
Carry forward a clearer, inspectable view of what can be trusted enough to use.
Views is currently in private preview. No subscription or card is required: enter with Google in under a minute and help shape a more accountable answer layer.
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