Quickstart
Validate your first interaction against a policy metric in 5 minutes
1. Get Your API Key
Sign up or log in to your Prisma instance and navigate to Settings → API Keys.
2. Install the SDK
pip install prisma-ai3. Configure Your Environment
export PRISMA_API_KEY="your-api-key"
export PRISMA_BASE_URL="https://your-prisma-instance.example.com"4. Define a Policy Metric and Validate
from prisma_ai import Prisma
prisma = Prisma()
# Define a policy metric that checks response compliance
policy = {
"name": "response-compliance",
"evaluation_prompt": """You are validating a customer service interaction.
Policy: The agent must acknowledge the customer's concern and provide
a clear next step. Check if {response} follows this policy given {query}.""",
"options_prompt": "compliant, non_compliant, ambiguous",
"reevaluation_prompt": """Re-examine the interaction.
The agent said: {response}
The customer asked: {query}
Reference policy response: {reference}
Does the agent's response comply with the policy?""",
"reevaluation_options_prompt": "compliant, non_compliant"
}
# Log an interaction for validation
prisma.log(
query="I was charged twice for my subscription",
response="I understand your concern about the double charge. Let me look into your account right now and process a refund for the duplicate payment.",
reference="Acknowledge the billing issue, verify in the system, and initiate refund process."
)Check your Prisma dashboard to see the validation result.
What Just Happened
- You defined a policy metric using the 4-prompt pattern
- You logged a customer interaction
- Prisma validated the interaction against your policy
- The result shows whether the response was compliant, non-compliant, or ambiguous
If the result is ambiguous, it appears in the human review queue for expert feedback — and that feedback makes future validations smarter.
Next Steps
- Policy Metrics — Learn the 4-prompt pattern in depth
- Human Review — Set up expert review workflows
- Installation — Detailed environment setup

