About Pharma AI Monitor

Pharma AI Monitor exists to solve a new problem: patients and HCPs now ask AI first. Every day, over 40 million people ask ChatGPT health-related questions^{[2, 3]} - and three in five U.S. adults have used AI tools for healthcare queries in just the past three months^[4].

These AI systems don't just search - they synthesize. They pull from hundreds of sources, blend information, and deliver answers with confidence. But they can drift, omit, or cite weak sources. For regulated pharmaceutical brands, that creates visibility risk, compliance risk, and competitive risk.

Our mission: give pharma brand teams the visibility and governance they need to monitor, measure, and fix how AI represents their products - across ChatGPT, Claude, Gemini, and Perplexity.

The shift is already here. When a patient wonders whether a new therapy is right for them, they increasingly turn to AI assistants alongside - or instead of - Google. When an HCP needs a quick refresher on dosing or drug interactions, ChatGPT is faster than digging through PDFs.

This creates three challenges for pharma brands:

• Visibility: Is your brand appearing in AI answers at all? How often, and in what context? Share-of-answer is the new share-of-voice.
• Accuracy: Models vary. ChatGPT, Claude, Gemini, and Perplexity each pull from different sources and weight information differently. One might cite your PI accurately; another might hallucinate a claim you never made.
• Drift: AI answers change over time as models update and sources shift. What was accurate last month may not be accurate today - and you won't know unless you're monitoring.

Citations matter more than ever. AI systems don't just give answers - they cite sources. Those sources shape credibility. If AI cites a low-quality blog instead of your peer-reviewed evidence, that's a problem your competitors may be exploiting.

AI Pulse is the monitoring layer for AI-driven customer journeys. It uses proprietary response indexing to track share-of-answer, narrative drift, and PI-backed claim defensibility across ChatGPT, Claude, Gemini, and Perplexity - then turns findings into a governed action queue your teams can run.

What you get:

• AI Pulse Score with sub-scores for Visibility, Positioning, and Truth Alignment
• Provider-level monitoring across all major LLMs
• Influence Graph showing which domains and pages shape AI answers
• PI-backed verification categorizing claims as Supported, Ambiguous, or Not-in-PI
• Governance queue with owners, due dates, and audit trail
• Retest loop to verify fixes and prove lift

AI Pulse is designed for regulated pharmaceutical environments where accuracy, compliance, and audit trails are non-negotiable.

AI Pulse is built for pharmaceutical brand teams - the people responsible for how the market perceives and talks about their products:

• Brand Marketing: Track competitive visibility and positioning in AI answers. Understand share-of-answer trends and identify where competitors are winning.
• Omnichannel Marketing: Ensure consistent messaging across the AI layer. Monitor how AI-synthesized answers align with your approved content across touchpoints.
• Medical Affairs: Verify that AI-generated claims align with prescribing information and approved medical education. Flag inaccuracies before they spread.
• Communications: Monitor narrative drift and misinformation. Prepare for questions about what AI says about your brand.

Whether you're launching a new therapy, defending market share, or ensuring global consistency, AI Pulse gives you the visibility and governance to act.

"Monitoring" alone isn't enough. In regulated pharma, findings need evidence, actions need owners, and outcomes need verification. That's what governed monitoring means:

• Evidence: Every finding includes source citations, exact AI responses, and context. No black boxes - you can see exactly what the AI said and why it's flagged.
• Ownership: Findings route to a governance queue with clear owners (Brand, Medical, Omnichannel, Comms), due dates, and escalation paths.
• Retest loop: After fixes are implemented, AI Pulse reruns question sets to verify improvement. You get delta metrics vs baseline - proof that your actions worked.

This creates accountability and audit trails that pharma companies require. When regulators or leadership ask "What did you do about it?", you have the answer documented.

AI Pulse monitors the major large language models where patients and HCPs ask health questions:

• ChatGPT (OpenAI) - The largest consumer AI assistant, with over 40 million daily health queries^{[2, 3]}
• Claude (Anthropic) - Increasingly used in professional and enterprise contexts
• Gemini (Google) - Integrated with Google Search and Android devices
• Perplexity - AI-native search engine with citation-heavy answers

Each provider has different source preferences, training data, and answer patterns. AI Pulse tracks performance by provider over time, so you can see where you're strong, where you're weak, and where drift is occurring.

Pharmaceutical marketing operates under strict regulatory oversight. The FDA's Office of Prescription Drug Promotion (OPDP) monitors advertising and has issued enforcement letters for overstated efficacy claims or missing risk information^{[5, 6]}.

AI Pulse is designed with this environment in mind:

• PI-backed verification: Every AI-generated claim is checked against your prescribing information. Claims are categorized as Supported, Ambiguous, or Not-in-PI.
• Audit trail: All findings, actions, and outcomes are logged with timestamps, owners, and evidence links. This supports MLR review and regulatory inquiries.
• Governance queue: Issues don't get lost. They route to accountable owners with due dates, ensuring nothing falls through the cracks.
• Evidence-based reporting: Reports include source citations and exact AI responses - not summaries or interpretations. You can verify everything.

We don't generate content or make claims on your behalf. AI Pulse is a monitoring and governance layer - your teams decide how to act on findings.