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Field Mapping lets you map data from a source system to a destination system — matching fields, transforming values, and shaping the payload your integration sends. It runs in a dedicated Field Mapping tab alongside Build, Connect, and the other workspace tabs.
Prerequisite: the Build Agent only creates field mappings when the field-mapping skill is attached to your integration. Add it to your organisation’s library and attach it when building — see Skills.
With the skill attached, ask the Build Agent to create field mappings for your integration and the Field Mapping tab appears automatically.

Opening the mapper

Open the Field Mapping tab, then pick a mapping from the dropdown at the top. The canvas shows your source fields on the left and destination fields on the right, with the mapping between them.
Workspace tab bar with the Field Mapping tab highlighted

The Field Mapping tab alongside Build, Connect, and the other workspace tabs

Field mapper canvas showing source and destination field trees connected by mapping lines

The mapper canvas, with source fields on the left and destination fields on the right

Guided walkthrough

The quickest way to learn the mapper is the built-in tour.
Click the eye iconnext to Field mapping on the left to launch a guided tour that steps through every feature. The Help icon in the top-right opens the reference documentation.

Adjusting the source and destination schemas

The mapper derives its fields from sample JSON for each side. Use Edit Source and Edit Destination to change those samples in a field-tree editor — add, rename, retype, or remove fields. When you save, the mapper rebuilds the field tree and reconciles your existing mappings against it; if an edit would drop a field that a mapping still uses, you’ll be warned first.

AI assistance

Two AI helpers are available, both powered by the Build Agent with your project’s context:
  • Expression AI — describe what you want and it generates a single JSONata / JSON-formula expression for a field.
  • AI Pipeline — generates an ordered transformation pipeline for a mapping (e.g. format a date, then uppercase).
Generated results appear in the canvas for you to review; nothing is persisted until you save.

Saving

Click Save DSL to persist the mapping to your project. Your integration then uses it at runtime to transform data between the connected systems.