A medical device company wants to feed reports of medical procedures that used the company's devices into an AI assistant. To protect patient privacy, the AI assistant must expose patient personally…

Question

Options

• AEnable Amazon Macie PII detection on the S3 bucket. Use an S3 trigger to invoke an AWS
• BInvoke an AWS Lambda function to sync the S3 bucket and the knowledge base when a new
• CSet up an S3 Lifecycle configuration to remove reports that are older than 3 years. Schedule an
• DCreate a second knowledge base. Use Lambda and Amazon Comprehend to redact PII before

• A
  8% (3)
• B
  5% (2)
• C
  85% (33)
• D
  3% (1)

Explanation

Option C is the correct solution because it enforces privacy controls at inference time, not at ingestion time, which is required when different user roles require different visibility into the same underlying data. Using an S3 Lifecycle configuration ensures that documents older than 3 years are automatically removed, guaranteeing that the knowledge base references only compliant, recent medical Scheduling Lambda-based syncs keeps the knowledge base aligned with the bucket contents without introducing complex per-upload orchestration. The most important requirement is role-based PII exposure. Amazon Bedrock guardrails support dynamic application at inference time, allowing the system to select a guardrail configuration based on the authenticated user's Amazon Cognito group. Surgeons can receive full responses, while engineers receive responses with PII masked--without duplicating data or maintaining multiple knowledge bases. This approach preserves a single source of truth for medical reports while enforcing privacy through response-level controls. It also maintains full auditability of access and redaction

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