Know what AI tells patients about your brand
Patients and professionals ask AI about treatments, medications and providers every day. Monitor what each model says about your organization, trace claims to their sources, and correct outdated information where AI actually reads it.
From a wrong health answer to the page that caused it
The monitor, trace and correct loop hospitals, clinics and pharma teams run every week.
Citation Sources
The sources of record behind patient answers
When AI describes a condition you treat or a product you make, it leans on medical reference sites, news coverage and patient forums, with your own pages somewhere in the mix. This ranking shows which of them carry your prompts, so an outdated claim stops being an abstract worry and becomes a specific article with an owner.
- Reference sites and forums ranked by weight
- Your pages measured against third-party sources
- Each wrong claim mapped to its article
Sentiment Tracking
Catch the turn in tone before patients do
One negative story can shape how models frame a hospital or a product for months after the facts change. Sentiment is scored weekly on every mention of your organization, per model, so communications teams see the dip start, act on it, and watch the recovery on the same chart.
- Weekly tone per model, per mention
- Negative turns flagged while still small
- Recovery visible after the correction ships
Correction Workflow
An ordered queue for medical and content teams
Findings arrive as prioritized actions, from refreshing a treatment page to earning a citation on a reference site models already read. Each card ties to the patient prompts it affects, so review time goes to the fixes that change answers. The next weekly run confirms what worked.
- Fixes ranked by patient-facing impact
- Each action tied to specific prompts
- Weekly runs verify every correction
Why Healthcare Teams Choose LLM Pulse
When AI answers a health question wrong, the brand named in the answer carries the risk.
Track Patient-Facing Prompts
Monitor the questions patients ask about the conditions you treat and see when your organization gets named.
Catch Outdated Information
Read the full answers about your treatments, services and locations, and spot claims that no longer match what you publish.
Trace Every Claim to Its Source
Each answer lists the pages AI cited, so you know exactly which outdated article or forum thread to address.
Measure Sentiment Week by Week
A sentiment score on every mention shows how the tone toward your brand develops over time.
Benchmark Against Other Providers
Compare visibility and share of voice with the hospitals, clinics or manufacturers patients weigh you against.
Turn Findings Into Fixes
Content recommendations and GEO optimization audits point to the pages to update so cited sources carry current information.
How It Works
Monitor first, then correct through the sources AI already reads.
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1
Add the questions patients ask
Condition prompts, provider comparisons and medication queries, scoped to the regions and audiences you serve.
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2
Record answers weekly
Every plan runs your prompts across 5 AI models each week and stores the full answer text.
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3
Trace claims to sources
Citation analysis shows which pages produced an outdated or inaccurate description of your brand.
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4
Correct through the sources
Update your own pages, direct outreach at third-party citations, and verify the change in the next run.
Built for Healthcare Use Cases
Where healthcare and pharma teams put LLM Pulse to work.
Hospitals and clinics
Track "best hospital for" and condition-level prompts in the regions you serve.
Pharma brands
Monitor how AI describes your products and which sources those descriptions cite.
Digital health
See whether AI recommends your app or service on category prompts against other providers.
Patient trust
Follow sentiment on your brand's mentions and catch a negative turn before it spreads.
"After noticing rising visits from various LLMs in GA4, we needed visibility into those black boxes: which models were mentioning us, in which answers, and how that was changing over time. LLM Pulse gave us the clarity to understand our brand's evolution across AI models and to shape new strategies to boost our exposure."
Frequently Asked Questions
Common questions from hospitals, clinics and pharma teams.
Explore the features behind this solution
Go deeper on AI search
AI Search Data Studies
Research on how AI models source and phrase sensitive answers.
Read moreFree AI Visibility Report
Get a first snapshot of how AI models describe your organization.
Read moreCitation Sources Analysis
How LLM Pulse maps every URL behind the answers AI gives.
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