Solutions
Eye for Medicine
Track how AI platforms discuss medical topics, treatments, and brands—what they cite, what they get wrong, and how narratives shift over time.
Outcomes teams care about
Eye turns model behavior into visibility, citations, and concrete next steps you can validate.
Reduce misinformation risk
Monitor narratives and catch inaccurate or unsafe representations early.
Improve discoverability
Measure visibility for critical queries across engines and personas.
Understand citations & authority
See which domains models cite and where authority is concentrated.
Validate updates over time
Re-run prompt sets to confirm improvements and prevent regressions.
What you’ll actually do in Eye
Use a small set of repeatable workflows that keep the depth while staying easy to act on.
Define high-stakes query sets
Symptoms, treatments, side effects, comparisons, and “is it safe?” prompts.
Track mention rate & position
See how often you appear and how you rank across platforms.
Inspect citations by domain
Understand what sources models rely on and where you need stronger coverage.
Monitor sentiment & claims
Spot negative drivers and misinformation patterns across runs.
Export for review
Share outputs with compliance, medical, and comms teams.
Prompt Lab for phrasing
Test language and framing to understand how it changes answers.
See the depth you get—without the clutter
Drill down from charts and tables into evidence, sources, and changes across runs.
Platform comparison
Compare how engines answer the same medical query to identify divergences.
Cited domains dynamics
See which sources influence answers and how that changes across runs.
Sources and authority
Understand which domains models cite most when answering medical questions.
Competitive matrix
Spot narrative pressure and where competitors win on key topics.
Ready to see how AI represents you?
Create a project, add prompts, and start measuring visibility across answer engines in minutes.