Service
AI Answer Intelligence for Post-Market Surveillance
Structured monitoring of AI-generated product answers, recurring question themes, sentiment signals, and misinformation patterns; packaged as inputs internal teams can consider alongside existing PMS, complaint, and CAPA workflows.
Definition
AI Answer Intelligence for PMS
The structured monitoring of AI-generated product answers, recurring question themes, sentiment signals, and misinformation patterns that may support internal PMS review, complaint triage, CAPA consideration, and product content improvement.
Who this is for
- Post-Market Surveillance
- Quality Assurance
- Regulatory Affairs
- Medical / Clinical Affairs
- Customer Support leadership
- Product and content owners
What may be monitored
Public AI answers about safety and use
How AI tools describe product use, safety information, and warnings.
Repeated customer question themes
Patterns in what customers, clinicians, and distributors are asking AI.
AI-generated misinformation patterns
Recurring inaccurate or misleading answer types.
Sentiment signals
Tone, confidence, and framing patterns in AI responses about products.
Confusing or missing product information
Gaps in approved sources that AI tools fill incorrectly.
Misunderstood product issues
Where AI tools misinterpret known product behaviors.
Regional variations
How AI answers differ by country, language, or regulatory context.
Example prompts
Illustrative prompts from a typical scoping exercise. Actual prompt libraries are tailored to your product portfolio, risk categories, and regions.
- Prompt
Is [Product] safe to use for [scenario]?
- Prompt
What problems are people reporting with [Product]?
- Prompt
How does [Product] handle [edge case]?
- Prompt
What should I do if [Product] malfunctions?
- Prompt
Is [Product] approved in [Country]?
Example findings
Illustrative finding rows. Each finding includes the prompt, channel tested, observed issue, a risk rating, and a recommended action.
| Prompt tested | Channel tested | Observed issue | Risk level | Recommended action |
|---|---|---|---|---|
| Is [Product] safe to use for [scenario]? | Public AI Assistant | Recurring off-label suggestion across multiple test cycles. | High | Internal PMS review consideration; strengthen authoritative source content |
| What problems are people reporting with [Product]? | AI Search Overview | Misattributed third-party complaint surfaced confidently. | Medium | Monitor recurrence; consider content clarification |
| What should I do if [Product] malfunctions? | Distributor Chatbot | No reference to complaint reporting channel. | Medium | Distributor communication improvement |
Illustrative examples.
Deliverables
Each engagement produces a structured evidence package designed to be reviewed, prioritized, and acted on.
- Executive summary
- Tested products and regions
- Prompt themes
- Key findings with risk ratings
- Risk rating summary
- Evidence captures
- Recommended actions
- Trend comparison across cycles
Disclaimer. Reports are designed to support internal review and decision-making; they do not replace required complaint handling, PMS, regulatory, or quality system processes.
Frequently asked questions
Does this replace post-market surveillance?
No. Reports are designed to support internal review and decision-making. They do not replace required complaint handling, post-market surveillance, CAPA, regulatory, or quality system processes.
How are themes identified?
Recurring prompts, observed answer patterns, and misinformation signals are coded against your product portfolio and risk categories.
What is the typical cadence?
Monthly or quarterly reporting, scoped to product families, regions, and risk priorities you select.
Can outputs feed internal complaint triage?
Trend and pattern observations may be reviewed by internal teams as one input into existing complaint triage and CAPA consideration workflows.
Ready to see what AI is saying about your products?
Request a scoped AI Answer Audit for your product portfolio and risk categories.