Define how to handle and structure your AI/ML model’s responses.
The Output Schema defines the structure of the response returned by your AI/ML model. This ensures that predictions or insights received from the model are properly formatted, mapped, and usable within downstream components like Data Apps, feedback mechanisms, or automation triggers.AI Squared allows you to specify each expected field and its data type so the platform can interpret and surface the response correctly.
Your output schema should include:churn_risk_score → Floatprediction_label → Stringconfidence → FloatThis structure ensures consistent formatting across visualizations and workflows.
Make sure field names exactly match the keys returned by the model.Use descriptive names that make the output easy to understand in UI or downstream logic.Choose the right type — AI Squared uses this for formatting (e.g., number rounding, boolean flags, etc.).