## Extract Databricks AI model lineage

URL: https://docs.atlan.com/apps/connectors/data-warehouses/databricks/how-tos/extract-databricks-ai-model-lineage

> Build upstream lineage between Databricks AI models and the datasets, tables, and functions they depend on.

:::warning Supported tracking servers only
Atlan supports lineage only for models tracked on **Databricks-hosted MLflow tracking servers** (where the tracking URI is `databricks`). External or self-hosted MLflow tracking servers aren't supported.
:::

Once you have [crawled Databricks AI models](https://docs.atlan.com/llms/connectors/databricks/crawl-databricks-ai-models/llms.txt), Atlan can build lineage connecting those models to the upstream datasets, tables, and functions they depend on. This gives you end-to-end visibility into how data flows from source assets into trained model versions.

## Prerequisites

Before extracting AI model lineage, make sure you have:

- A [Unity Catalog-enabled](https://docs.databricks.com/en/data-governance/unity-catalog/get-started.html) Databricks workspace
- [Crawled Databricks AI models](https://docs.atlan.com/llms/connectors/databricks/crawl-databricks-ai-models/llms.txt) at least once
- All permissions required for [AI model crawling](https://docs.atlan.com/llms/connectors/databricks/crawl-databricks-ai-models/llms.txt) are in place

## Extract lineage

Lineage is built automatically during the Databricks crawler run—no separate workflow is needed.

To extract AI model lineage:

1. Make sure the Databricks crawler is [configured for AI models](https://docs.atlan.com/llms/connectors/databricks/crawl-databricks-ai-models/llms.txt) with the **Direct** extraction strategy.
2. If your models use [Databricks Feature Store](https://docs.databricks.com/en/machine-learning/feature-store/index.html) and the `feature_spec.yaml` artifact is stored in an external location, grant read access to the Atlan service account:

 ```sql
 GRANT READ FILES ON EXTERNAL LOCATION <external_location_name> TO <atlan_user_or_role>;
 ```

 If the artifact is inaccessible, Atlan skips Feature Store lineage for that model version and falls back to run-based lineage where available.

3. Run the Databricks crawler workflow.
4. After the workflow completes, navigate to any **AI Model Version** asset in Atlan to view its lineage. The lineage graph shows upstream tables, feature views, and functions that fed into the model version.

Cross-workspace lineage for Databricks AI models isn't yet supported. Support for tracing lineage across Databricks workspaces is planned for a future release.

## See also

- [Crawl Databricks AI models](https://docs.atlan.com/llms/connectors/databricks/crawl-databricks-ai-models/llms.txt): Discover and catalog AI models from your Unity Catalog Model Registry.
- [How Atlan builds lineage for Databricks AI models](https://docs.atlan.com/llms/connectors/databricks/how-databricks-ai-model-lineage-works/llms.txt): Understand the lineage sources, relationships created, and asset behavior.

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