---
title: 'Transform'
description: 'Remap fields from upstream data into a new shape.'
---
# Transform

Builds a new object by mapping source fields (referenced with `{{...}}`) onto
target keys. Use this when you need to reshape data between two nodes — e.g.
taking a Stripe payload and producing the shape your CRM expects.

## When to use

- Renaming or restructuring fields between two systems.
- Extracting a subset of fields from a big payload.
- Applying a basic transformation (`uppercase`, `lowercase`, `trim`) while
  copying the value.
- Computing derived fields (concatenation, defaults).

For more complex transformation that needs branching logic, consider
**AI Transform** instead.

## Configuration

| Field | Required | What it does |
|---|---|---|
| `mappings` | Yes | JSON array of mapping rules. |

### Mapping rule format

```json
[
  {
    "targetKey": "customer_email",
    "sourceExpression": "{{trigger.data.customer.email}}",
    "transform": "lowercase"
  },
  {
    "targetKey": "full_name",
    "sourceExpression": "{{trigger.data.first_name}} {{trigger.data.last_name}}"
  },
  {
    "targetKey": "amount_cents",
    "sourceExpression": "{{trigger.data.amount}}"
  }
]
```

`transform` is optional. Supported: `lowercase`, `uppercase`, `trim`,
`number` (coerces strings to numbers), `boolean` (coerces "true"/"false"
strings to booleans).

## What it outputs

An object built from the `targetKey`/result pairs:

```
{
  customer_email: "alice@example.com",
  full_name: "Alice Smith",
  amount_cents: 9999
}
```

Downstream nodes reference fields as
`{{<transform_node_id>.data.customer_email}}` etc.

## Gotchas

- **Missing source fields** produce empty strings in the output, not
  `undefined`. If you need "field was missing" semantics, pair with a
  downstream If/Else checking `exists`.
- **Template concatenation** is string-based — `{{a.b}} {{c.d}}` produces
  a space-separated string, not a number sum. For arithmetic, use
  AI Transform or Set Variable with a computed value.