Policy Engine

Policies that keep your AI safe, compliant and in control.

SuperAgentX Policy Engine enforces your rules before any AI action happens — so every request is safe, compliant, and auditable by design.

  • Safe Block risky actions before they run
  • Compliant Meet regulatory and internal rules
  • Governed Control who can do what, and when
  • Auditable Full traceability for every decision
Policy Engine flow: user request, policy checks, allow, approve, deny, action, and audit log

How Policy Engine works

Every request is evaluated in real time against your policies before any AI action is executed.

How Policy Engine works: Request, Evaluate, Decision, Action, and Audit workflow

Policy examples

Define rules in simple YAML — enforce them across every agent, workflow, and tool.

1. Data Protection (PII)

Block agents from sharing PII outside the company.

rules:
  - id: block-pii-sharing
    when:
      output.contains("pii")
    then: deny
    message: "Sharing PII is not allowed"

2. Model Routing

Use the right model based on the task type.

rules:
  - id: route-by-task
    when: task.type == "complex"
    then: use_model: "gpt-4o"
    else_if: task.type == "fast"
    then: use_model: "gemini-1.5"

3. Production API Protection

Restrict high risk actions in production environment.

rules:
  - id: block-delete-prod
    description: Block destructive API calls in production
    scope: tool
    when:
      env: production
      action: delete
    decision: deny

4. Model Access Control

Only allow specific teams to use certain models.

rules:
  - id: model-access
    description: Restrict model access by team
    scope: model
    when:
      team: finance
      model: claude-3
    decision: allow

Human-in-the-Loop (HITL)

Require human approval for high-impact actions — with full context and audit trails.

Human-in-the-Loop workflow: Request, Policy Check, Human Review, Decision Applied, Action and Audit