modellerUpdated 2026-04-18

Export and Import a Model

Explorer page showing Add Model and Import buttons.

What this covers

You can export any model as a single JSON file and import it into the same project, a different project in the same tenant, or a different tenant entirely. Connections never travel — credentials stay in the source database — so on import you pick local connections to rebind the model to. This article covers the export download, the import dialog, and how connections are remapped.

Before you start

Exporting a model

  1. Open the Model Builder for the model you want to export.
  2. On the toolbar, click the Export button (down-arrow into tray icon).
  3. Tessallite downloads a file named {model_slug}.tessallite.json to your browser's download folder.
  4. The file is a single JSON document containing every per-model row — tables, columns, joins, hierarchies, dimensions, measures, aggregates, refresh policies, AI scheduler config, model settings, and the canvas layout.

The file does not contain credentials, query history, miss logs, alerts, or anything stored at tenant, project, or system scope.

Importing a model

  1. From the Explorer, select the project you want to import into.
  2. Click the Import button next to Add Model.
  3. In the dialog, click Choose .tessallite.json file and pick the export file.
  4. The dialog reads the bundle and shows:
  1. For each referenced connection, pick a local connection from the dropdown. Only connections of the matching type appear.
  2. Optionally tick Deploy immediately after import to save v1 and deploy in one click.
  3. Click Import. Tessallite creates a new model in the target project, rewrites every internal UUID, rebinds the connections, and (if you ticked Deploy) saves and deploys v1.
  4. The Explorer navigates to the new model.

If the source slug already exists in the target project, Tessallite auto-suffixes (sales, sales-2, sales-3).

What is and is not in an export

In the exportNot in the export
Tables, columns, joins, hierarchies, UDAsConnection credentials
Dimensions, measuresSource data, target data
Aggregate definitions and refresh policiesQuery logs, miss logs, alerts
Per-model AI scheduler config and model settingsSystem / tenant / project settings
Canvas layout (table positions, viewport)Deployed-version pointer (the import always starts undeployed)

Tips

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