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Usage Guides

Creating Policies

Creating Policies

Policies are collections of guardrails organized by purpose. They define how your organization governs AI.

Policy Creation

Via Dashboard

  • Policies → Create Policy
  • Name: “Production Governance”
  • Select guardrails to include
  • Configure overrides (optional)
  • Set rollout strategy
  • Click Create

Via API

curl -X POST https://api.governanceai.com/v1/policies \
  -H "Authorization: Bearer $API_KEY" \
  -d '{
    "name": "Production LLM Governance",
    "description": "Enforce safety and compliance in production",
    "guardrail_ids": ["guardrail_pii", "guardrail_toxic", "guardrail_rate_limit"],
    "scope": "organization",
    "enforcement": {
      "mode": "blocking",
      "log_violations": true
    }
  }'

Policy Versions

Policies are versioned automatically:

  • v1.0 - Initial policy
  • v1.1 - Added guardrail
  • v2.0 - Major update

Rollback to previous version anytime.

Scopes

  • Organization - Apply to entire org
  • Workspace - Apply to specific workspace
  • Application - Apply to specific app
  • User - Apply to specific user

Narrower scopes override broader ones.

Policy Testing

Test impact before deploying:

curl -X POST https://api.governanceai.com/v1/policies/test \
  -H "Authorization: Bearer $API_KEY" \
  -d '{
    "policy_id": "policy_123",
    "test_requests": [
      {
        "input": "What is my password?",
        "context": {"user_id": "user_test"}
      }
    ]
  }'

Rollout Strategies

  • Immediate - Deploy to all users now
  • Canary - Roll out to 5% → 25% → 100%
  • Scheduled - Deploy at specific time

Next Steps