Collibra AI Governance

Collibra AI Governance builds on the company's established data intelligence platform, extending its catalog, lineage and data-quality foundations to the models and agents that consume that data. The premise is that trustworthy AI depends on trustworthy data, so Collibra registers AI models and agents alongside the datasets they use, capturing ownership, metadata, lineage and lifecycle stage in one place. Model and agent registries standardize documentation and route assets through defined lifecycle stages with policy, ethical and regulatory checks. Assessment templates aligned to the EU AI Act and NIST AI RMF let teams record risk levels, controls, performance metrics and required approvals, and the product has been extended with agentic AI compliance assessments. A key differentiator is breadth of integration with AI development platforms: it connects to AWS Bedrock and SageMaker, Azure AI Foundry and ML, Databricks Unity Catalog, Google Vertex AI, MLflow and SAP AI Core, so governance spans a heterogeneous model estate. It is aimed at data governance, compliance and data science teams in data-mature enterprises that already use Collibra, and its distinctiveness lies in tying AI oversight directly to end-to-end data lineage rather than treating models in isolation.