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Parmana Agent Guard

AI can propose. Real Parmana authorizes. Execution only happens after authorization.

A focused buildathon MVP showing an AI agent proposing a customer refund while the real Parmana API evaluates the action against the deployed customer-refund@1.0.0 policy.

Real Parmana flow

AI Agent
   |
   | refund proposal
   v
Agent Guard
   |
   | BusinessTransaction
   v
REAL PARMANA API
   |
   | customer-refund@1.0.0
   v
ALLOW / BLOCK
   |
   +---- BLOCK ----> No execution
   |
   +---- ALLOW ----> Mock refund execution
                       |
                       v
                    Evidence

The important boundary is that the local demo no longer makes the authorization decision itself. Parmana does.

Demo scenarios

1. Allowed

₹3,500 damaged-order refund → sent to real Parmana → policy approval → mock execution → evidence.

2. Blocked

₹7,500 damaged-order refund → sent to real Parmana → policy rejection → no execution.

3. Direct API attack

A request attempts to call Agent Guard directly with ₹7,500. The request still goes through the real Parmana authorization boundary before any local execution.

Setup

Create a local .env file:

PORT=3000
PARMANA_API_URL=https://parmana-api-real.vercel.app
PARMANA_API_KEY=your_parmana_demo_key

Install and run:

npm install
npm start

Open:

http://localhost:3000

Important

The API key is a secret. Do not commit .env or paste the key into GitHub.

The real Parmana API expects a BusinessTransaction with:

  • a real UUID businessTransactionId
  • authorityType: SERVICE
  • principalId: demo for the demo key
  • policy customer-refund@1.0.0
  • bound refundAmount matching intent.parameters.amount

The deployed API is documented in the main Parmana repository's LIVE-API-GUIDE.md.

Scope

This is a buildathon MVP. Parmana authorization is real; the final refund connector remains a mock execution so the demo does not move real customer money.

That separation is deliberate:

Parmana proves whether the action is authorized. The execution adapter performs the authorized action.

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