Clinical operations teams do not need more dashboards connected to existing systems. They need their decision-support applications to live where their data and models live — so that the feedback loop between a prediction and the operational outcome that validates it actually closes.

The conventional approach to clinical decision-support looks like this: analytical data lives in a data warehouse or Lakehouse. A separate application database holds operational state. A pipeline keeps them loosely synchronized. A web application sits in front of both, adding semantic harmonization in the Silver layer. Every layer introduces integration overhead, credential surface area, and a synchronization lag that erodes trust in the data the application shows.

Databricks Apps, Lakebase, and AI/BI Genie eliminate each of those layers — not by abstracting them away but by making them unnecessary.

Databricks Apps run the web application inside the workspace. The app authenticates as a first-class workspace service principal, queries Unity Catalog via the SQL Statement API, and calls AI/BI Genie over the workspace REST API — all on internal connections. Clinical operations data never crosses a workspace boundary. The app inherits Unity Catalog access controls without any additional configuration.