Plain-language overview
This page provides general information. It is not legal advice. If you need a tailored policy for your jurisdiction or industry, consult a qualified attorney.
Security principles
- Least privilege: access limited to what is required to deliver the service.
- Data minimization: collect only what is needed to complete the workflow.
- Retention controls: define how long data is stored and where.
- Observability: logging and alerts to detect failures and misuse.
AI-specific privacy considerations
- Avoid placing sensitive personal data into prompts unless explicitly required.
- Use approved knowledge sources (RAG) where accuracy matters.
- Define escalation rules for edge cases and high-stakes queries.
- Use evaluations and regression testing to keep behavior stable.
Security + privacy guardrails
AI systems should not become data leaks. We design workflows that minimize sensitive data, enforce access controls, and keep “who can see what” simple.
Data minimization
Collect only what you need to serve the customer. Avoid storing unnecessary PII in logs.
Least-privilege integrations
Use scoped credentials and limit write-access until the system is proven in production.
Human-in-the-loop
For high-stakes actions (pricing, commitments, account changes), we include review and approval gates.