Integrating your AI models in Collibra

When assessing the value and risks associated with an AI use case, it's important to be able to quickly identify which AI model is used by the use case. From the AI Use Case asset page, you can easily link to any AI Model assets (or assets of child asset types) that exist in your Collibra environment.

Tip For complete details on the out-of-the-box attribute types and relation types specific to the AI Model asset type, go to AI Governance operating model.

When you're linking to an AI model, all relevant assets appear in an Assets drop-down list. But what if you can't find your AI model?

Can't find your AI model?

You're trying to link an AI model to your use case, but no assets appear in the Assets drop-down list, or you can't find the right one. What then?

As shown in the following image, you have three options.

Supported integrations

We offer the following Collibra-supported AI integrations:

Important These integrations are only available via Edge, not via Jobserver.

During an integration, Machine Learning (ML) model metadata is ingested as assets on the Collibra Platform. The following table shows the asset types associated with each integration.

Integration Assets of this type are ingested in Data Catalog Parent asset type

AWS Bedrock AI

AWS Bedrock AI Model AI Model

AWS SageMaker AI

AWS SageMaker AI Model AI Model

Azure AI Foundry

Azure AI Foundry Model AI Model
Azure AI Foundry Agent AI Agent

Azure ML

Azure AI Model AI Model
Databricks Unity Catalog Databricks AI Model AI Model
Google Vertex AI Vertex AI Model AI Model

MLflow AI

MLflow AI Model AI Model
SAP AI Core

SAP AI Model

AI Model

These integration-specific asset types are child asset types of the AI Model asset type.

All assets of these types in your Collibra environment appear in the Assets drop-down list when linking AI models to your registered AI use cases.

Custom integration

If our Collibra-supported integrations don't suit your needs, you can perform a custom integration. On the Collibra Developer Portal, you can find a tutorial explaining how to use Python to create and synchronize AI Models in Collibra.

Metadata from your ML models is ingested as assets in Collibra. All AI Model assets (and assets of child asset types) appear in the Assets drop-down list when linking AI models to your registered AI use cases.

Manually create an AI Model asset

You can manually create AI Model assets: