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Answer Assurance
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Process

A structured, risk-based process for AI answer assurance

Six structured steps that move from scope definition to actionable, traceable findings; built to produce evidence QA, RA, and PMS teams can use.

Read full methodology View sample report
  1. Step 1

    Define scope

    Product families, regions, languages, AI tools, chatbot channels, prompt categories, and risk priorities.

  2. Step 2

    Build prompt library

    Customer, clinician, distributor, and support scenarios; plus edge cases, misuse, off-label, and regional scenarios.

  3. Step 3

    Run structured testing

    Public AI tools, search assistants, company chatbots, distributor and ecommerce bots, with repeat testing where appropriate.

  4. Step 4

    Capture evidence

    Answer text, screenshots, date/time, channel/source, prompt used, and region/language context.

  5. Step 5

    Classify findings

    Accuracy, safety relevance, labeling/IFU alignment, regional appropriateness, severity, likelihood, and business impact.

  6. Step 6

    Report & recommend actions

    Findings log, executive summary, priority actions, content gap recommendations, and retest recommendations.

Note. 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.

Discuss your testing scope

Share the product families, regions, channels, and risk categories you want covered.

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