Pipeline template

Transform e-commerce orders with AI Draft

Transform nested e-commerce order exports into normalized analytics-ready records with selected fields, computed totals, and predictable output shape.

Run Template

Runnable example

Run this template on your JSON

Start from the sample input, edit the JSON, and open the same pipeline in the visual editor when you want to customize it.

Output

{
  "orders": [
    {
      "id": "ORD_001",
      "created_at": "2024-01-10T12:30:00Z",
      "customer": {
        "id": "C123",
        "name": "John Doe",
        "email": "john@example.com"
      },
      "items": [
        {
          "sku": "SKU_1",
          "name": "T-Shirt",
          "qty": 2,
          "price": "19.99"
        }
      ],
      "payments": [
        {
          "provider": "stripe",
          "amount": 39.98,
          "currency": "USD",
          "status": "succeeded"
        }
      ],
      "shipping": {
        "address": {
          "country": "US",
          "city": "San Francisco"
        },
        "status": "delivered"
      }
    }
  ]
}

Output

Output will appear here after you run the pipeline.

Love the result?

Use this exact pipeline in your app, backend, or LLM workflow.

No setup needed. Works with curl, Node, Python.

Uses example data. For edited input, copy from the playground.

Read integration guide

Need multiple transformations?

Try ForgeJSON Pipeline to combine extraction, cleanup, normalization, validation, and export steps into one reusable workflow.

Try ForgeJSON Pipeline