Responsible AI

The agent follows clear rules; people retain sensitive decisions

We use AI to perform defined work that can be explained and reviewed. We do not assume a model is always correct or give it financial, legal, or other sensitive decisions without appropriate controls and approval.

Last updated: 16 July 2026
01

Transparency

Customers should know when they are interacting with an automated system where appropriate, and the business owner should understand the agent’s capabilities and limits.

  • Clear identification of the agent’s role
  • Explanation of the data used for the task
  • Visible transition when a case moves to an employee
  • No presentation of automated content as a human decision
02

Accuracy and grounded responses

Answers and actions are connected to approved sources and validation rules whenever possible. When information is insufficient or conflicting, the agent pauses, asks for clarification, or routes the case for review.

  • Approved knowledge base
  • Field validation before execution
  • Confidence scores for extracted data
  • No guessing in sensitive cases
03

Decision boundaries

Before launch, decisions are divided into actions that can run automatically, actions requiring user confirmation, and actions requiring approval from an authorized employee.

  • No discounts or financial changes without authority
  • No independent legal or medical decisions
  • No personal data disclosure before verification
  • Escalation of anger, disputes, and unusual cases
04

Testing and review

We test common and exceptional scenarios before launch, then review performance samples and alerts afterward. Test depth depends on the possible impact of an error and process sensitivity.

  • Acceptance tests tied to business rules
  • Missing and conflicting input tests
  • Human handoff review
  • Rule updates when policy or data changes