What are the recommended treatments for Disease X based on recent guidelines?
HCP
Which drug is safer for Disease Y?
Patient
Best treatment options for Disease X?
Patient
Gain a 360 view on how major AI platforms think and talk to Patients and HCPs about your pharma brand
Percivis systematically runs tailored Patient and HCP prompts across major AI models to quantify brand visibility, narrative accuracy, and bias — turning raw AI outputs into actionable strategic insights for cross-functional Pharma Brand Teams
Patient
How does Treatment A compare to Treatment B?
HCP
Can I prescribe Treatment A alongside Treatment B?
Unlock unique value for Pharma
Get visible & prominent
Identify where AI looks for information and strategically place content to get your brand mentioned in AI-generated answers
Own the narrative
Shape how AI describes your brand by optimizing key messages, ensuring the right differentiation surface in AI outputs
Close blind spots
Know where AI underrepresents your brand or disease area and close the gaps through other channels (e.g. FF)
Protect credibility
Monitor compliance risks in how AI discusses your brand, enabling early escalation and proactive reputation management
Shape the ecosystem
Identify high-value partnership opportunities with LLM platforms and data players to expand your brand’s reach and influence
Use Cases
Learn how visible & prominent your brand is across AI answers
Gain an in-depth view of brand visibility & ranking across HCP or Patient segments and geographies
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Benchmarks against competitors, track over time and spot signals of competitive moves
Benchmark how AI describes your and competitors’ brands
See how AI interpret your and competitors’ product profile across key attributes
Spot where AI narratives diverge from your intended positioning
Track campaign impact by monitoring attribute shifts over time
Monitor medical accuracy about your product in AI answers
Identify and flag compliance risks before they trigger reputational or legal exposure
Quantify risk by cluster areas, informing corrective actions
Provide transparent evidence trails for med-legal escalation
Quantify AI disease awareness and spot knowledge gaps
Benchmark AI disease awareness by comparing answers to gold-standard sources (e.g. clinical literature, guidelines)
Identify high-impact gaps to inform targeted interventions (e.g. content strategy, partnerships with LLM providers)
Identify most influenceable sources where AI takes information
Quantify which source types AI relies on the most and spot high-impact channels to guide content strategy
Track the balance between validated and non-validated sources to monitor potential bias amplification
Be where patients are
"Search engines, such as Google, democratized access to health information and changed the dynamics of the patient-provider relationship, with 72% of internet users in the United States looking on the web for health information."
Frequently Asked Questions
What does Percivis actually do?
Percivis analyzes how major AI models (like ChatGPT, Gemini, Claude, or Perplexity) “talk” about pharmaceutical brands. By running thousands of tailored HCP and patient prompts, it quantifies brand visibility, narrative accuracy, and bias — turning raw AI responses into actionable insights for Brand, Medical, and Communications Team.
Does Percivis do GEO (Generative Engine Optimization)?
Percivis systematically runs curated sets of Patient and HCP prompts across leading AI platforms. Each prompt is normalized, timestamped, and scored across visibility, accuracy, and sentiment dimensions using proprietary algorithms. The system aggregates these signals into dashboards and benchmarks that reveal how AI currently represents your brand, your competitors, and your disease area.
How reliable are LLM-based analytics — can we trust the signal?
Yes — Percivis is built for scientific and statistical rigor. Every data point is generated through controlled, repeatable prompting and multi-model sampling to minimize randomness and bias. Outputs are validated through reproducibility checks and benchmarked over time, ensuring each insight reflects a consistent, measurable trend — not one-off model noise.
Why should I care about LLM mentions?
Because AI is becoming the new gateway to medical information.
What patients, HCPs, and payers read through these models increasingly shapes awareness, trust, and treatment choices.
Tracking and influencing how your brand appears in AI answers lets you own the emerging digital narrative — before competitors do.
How is this different from traditional social listening or search analytics?
Unlike social or search data, which reflect what people look for or say, Percivis measures what AI systems themselves say — the emerging layer that increasingly shapes patient and HCP perceptions. This lets you monitor how algorithms describe your brand, not just how users discuss it — unlocking a forward-looking view of digital reputation, influence, and misinformation risk.
Does Percivis do GEO (Generative Engine Optimization)?
Yes — but in a compliant, analytics-first way.
Percivis doesn’t “game” AI models; it helps you understand what drives visibility and identify content, channels, and partnerships that can organically improve brand presence and message accuracy across AI platforms.
Which AI platforms do you monitor?
Percivis continuously tests prompts across all major public and healthcare-relevant LLMs, like ChatGPT, Gemini, Claude, Perplexity, and selected specialized medical models. Coverage expands dynamically as new models gain adoption and significance.
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