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Airform handles the transform step: dbt-style, version-controlled SQL models that turn raw tables into clean, tested ones. It lives alongside your agents, automations, and semantic model in the same workspace, and is validated and deployed through the standard Git flow — so the tables your semantic model builds on are modeled deterministically, not assembled ad hoc.

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Why model with Airform

  • Version-controlled transforms. Your models are code, reviewed and deployed through the same Git flow as the rest of your project.
  • Tested tables. Transforms land clean, tested tables, so the semantic model compiles over a dependable foundation.
  • One workspace. Modeling sits next to agents, automations, and the semantic model — no separate tool to context-switch into.

airform on GitHub

dbt-style modeling for Oxygen. Open source.

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Next steps

The semantic model

Build measures over the tables Airform lands

Airhouse

Where your data lands