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

[
  {
    "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.