Product: AI Pulse for Pharma GEO Monitoring

AI Pulse is the monitoring layer for AI-driven customer journeys. It uses proprietary response indexing to track how large language models describe, recommend, and cite your pharmaceutical brand - then turns findings into a governed action queue your teams can run.

Every day, over 40 million people ask ChatGPT health-related questions^{[2, 3]}. Those answers shape perceptions, influence decisions, and increasingly replace traditional search for both patients and HCPs. But AI systems can drift, omit, or cite weak sources - and without monitoring, you won't know until the damage is done.

AI Pulse gives you visibility into what AI says, how it positions you vs competitors, and whether claims align with your prescribing information. Then it routes findings to accountable owners with evidence and audit trail.

AI Pulse measures your brand across three dimensions, each with its own sub-score:

These three pillars combine into an overall AI Pulse Score - a single metric to track brand health in the AI layer over time.

AI Pulse monitors for three critical risks:

• Share-of-Answer Loss: Your brand is missing from AI answers where it should appear, or appearing less often than competitors. This is the new battleground for brand visibility - share-of-voice in the AI era.
• Narrative Drift: AI systems are framing your brand differently than intended, using competitor language, or shifting positioning over time. Drift is gradual and hard to catch without continuous monitoring.
• Claim Defensibility Gaps: AI is making claims about your product that aren't supported by prescribing information, citing low-quality sources, or omitting required safety information^{[4, 5]}.

AI Pulse follows a four-step loop:

1. Measure: Run standardized question sets across ChatGPT, Claude, Gemini, and Perplexity. Capture exact AI responses, citations, and context.
2. Diagnose: Analyze responses for share-of-answer, positioning, and claim accuracy. Identify which sources are shaping AI answers (Influence Graph).
3. Fix: Route findings to governance queue with owners, evidence, and due dates. Teams publish content, refresh sources, or escalate to Medical/MLR.
4. Re-test: Run question sets again weekly to verify fixes and track improvement. Delta metrics prove lift vs baseline.

This creates a continuous improvement loop - not a one-time audit. AI answers change; your monitoring should too.

AI Pulse provides the following capabilities for pharma brand teams:

AI Pulse monitors across all major LLMs where patients and HCPs ask health questions:

• ChatGPT (OpenAI) - 40M+ daily health queries^[2]
• Claude (Anthropic) - Growing enterprise adoption
• Gemini (Google) - Integrated with Search and Android
• Perplexity - Citation-heavy AI search

Each provider has different source preferences and answer patterns. AI Pulse shows you performance by provider, so you can see where you're strong and where to focus.

The Influence Graph maps which domains and pages are shaping AI answers about your brand. It shows:

• Citation frequency: Which sources AI cites most often
• Domain authority: Government, academic, commercial, or unknown sources
• Context: How each source is used (supportive, contradictory, neutral)

This reveals whether AI is citing your peer-reviewed evidence, your competitors' marketing, or low-quality blogs. You can then prioritize content publishing to strengthen high-authority sources.

Every AI-generated claim about your product is checked against your prescribing information (PI). Claims are categorized as:

• Supported: Claim directly matches approved labeling
• Ambiguous: Claim is partially supported or requires interpretation
• Not-in-PI: Claim not found in approved labeling - potential compliance risk

Not-in-PI claims are flagged for immediate Medical/MLR review. This catches hallucinations and inaccuracies before they spread.

Findings don't disappear into reports. The governance queue routes every finding to an accountable owner with:

• Owner assignment: Brand, Medical, Omnichannel, or Comms
• Due dates: Clear deadlines for action
• Priority levels: Based on compliance risk and competitive impact
• Audit trail: Timestamp, evidence, and resolution logged

This creates MLR-friendly workflows where every action is documented. When regulators or leadership ask what you did, you have the answer.

For multi-brand organizations, AI Pulse aggregates scores across your portfolio. See which brands are performing well in the AI layer, which need attention, and how trends compare across therapeutic areas.

Portfolio views help prioritize resources and identify systemic issues (e.g., all oncology brands citing the same weak source).

An AI Pulse baseline establishes your starting point across all dimensions:

• AI Pulse Score with Visibility, Positioning, and Truth Alignment sub-scores
• Share-of-answer metrics by provider and question type
• Competitive positioning analysis (your brand vs top 3-5 competitors)
• PI-backed verification of all current AI claims
• Influence Graph of sources shaping AI answers
• Prioritized findings in the governance queue

A baseline typically covers 50-200 question variations across patient and HCP intent patterns, run across all four providers. Results are available within days.

AI Pulse is designed for fast implementation - days, not quarters:

1. PI upload: Provide your prescribing information (PDF or structured data)
2. Competitor definition: Identify 3-5 key competitors for share-of-answer tracking
3. Question set configuration: Define patient and HCP question patterns for your therapeutic area
4. Baseline run: First results within 3-5 business days
5. Governance setup: Configure owners, escalation paths, and notification preferences

No complex integrations, no IT dependencies. AI Pulse is a standalone SaaS platform that works with your existing workflows.