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AI Governance & Operations

Ensure AI reliability, safety, and cost control.

UC-AIML-003: AI Guardrails & Safety

Purpose: Prevent hallucinations and ensure brand-safe AI interactions.

Property Value
Actor System / AI Manager
Trigger AI Generation Event
Priority P0

Capabilities:

  • Content Filtering: Block profanity, PII (Personal Identifiable Information), or competitor mentions in generated messages.

  • RAG / Search Endpoints:

    • Context Injection: Retrieve relevant docs (e.g., "Refund Policy") before answering queries.

    • Citation: AI links to the source policy "According to [Refund Policy]...".

  • Budgeted Automation Limits:

    • Cost Control: "Stop AI generation if monthly API bill > $500".

    • Volume caps: "Max 500 AI calls/day per tenant".

Main Success Scenario:

  1. User asks AI: "Write a rude message to the client."
  2. Guardrail detects negative sentiment/profanity logic.
  3. System overrides output: "I cannot generate offensive content. Here is a professional alternative."

UC-AIML-004: Automated ML Retraining

Purpose: Keep models fresh with recent data.

Property Value
Actor MLOps System
Trigger Schedule (Weekly) / Drift Detection
Priority P1

Capabilities:

  • Pipeline Automation:

    • Ingest new booking/cancellation data.

    • Re-train "No-Show Prediction" model.

    • Compare accuracy vs previous model (Shadow Mode).

    • Auto-promote new model if Accuracy > Threshold.
    • Rollback if performance degrades.

Acceptance Criteria:

  1. [ ] Pipeline runs automatically on schedule (e.g., Weekly).
  2. [ ] Drift detection alerts admins if model accuracy drops < 80%.
  3. [ ] Shadow mode allows testing new models without affecting live users.