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Pipelines and automation

This route is for automation and data-tool builders who want typed boundaries, reproducible commands, and CI-friendly native artifacts.

Choose your route

The typed data processor is the executable next step when your workflow reads typed JSON, validates records, and emits a report artifact.

Install once

Follow Getting Started for the current installer choices and canonical first-project commands.

What transfers

  • Staged transformations, explicit inputs and outputs, and repeatable operational boundaries
  • Deterministic commands, exit codes, locked dependencies, and inspectable reports
  • Modules, file I/O, typed errors, tests, and release artifacts

What changes

  • Each fallible boundary returns a typed value rather than relying on logs or ambient shell state.
  • Data contracts and transformations can live in ordinary program modules with tests.
  • A native executable becomes the repeatable automation unit.

What not to expect

  • SQL, dataframe, Spark, or notebook compatibility; classify relational query and plan work with the Incan or IncQL? chooser
  • A remote package registry or hosted pipeline service
  • Enterprise deployment policy beyond the documented lock, offline, report, and exit-code contracts

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