Collibra AI Governance
AI governance platform for compliant, trusted AI
Last verified April 23, 2026About Collibra AI Governance
Collibra AI Governance is a platform that centralizes management of AI use cases, models, and agents with full visibility, trusted data, automated documentation, and built-in compliance features. It supports teams in scaling AI responsibly by providing end-to-end lineage from source data through model training, inference, deployment, and usage across platforms like AWS, Azure, Google, Databricks, SAP, and MLflow. The solution facilitates risk assessment using templates for EU AI Act and NIST AI RMF, policy enforcement, model registries, and ongoing monitoring to ensure audit-readiness and regulatory adherence, particularly for regulated industries such as financial services and healthcare. Distinct from narrower tools, it integrates data governance with AI oversight in a unified system of record, enabling cross-team collaboration between AI, data, and risk functions while recommending governed data products to reduce risks from poor data quality or bias.
Framework coverage
Coverage claims documented by Collibra AI Governance on their own materials. Chip shading reflects the strength of the claim, not an independent audit.
Global · voluntary
EU · in force
US · voluntary
Capabilities
Features Collibra AI Governance markets publicly. Inclusion means the capability is documented — not that it's best-in-class.
AI Model Inventory
Centralized registry of all AI/ML models in use across the organization, with ownership, lifecycle stage, and risk classification.
Policy Management
Authoring, versioning, and distribution of AI usage policies mapped to regulations.
Risk Assessment Workflow
Guided workflows for completing AI impact assessments, risk scoring, and approval routing.
Bias & Fairness Testing
Automated statistical testing for disparate impact across protected attributes, with audit-ready reports.
Audit Evidence Collection
Automated collection, hashing, and retention of evidence (model cards, test results, approvals) for audit.
Model Monitoring
Production monitoring for performance, drift, data quality, and fairness regressions.
Industries served
Integrations
Documented by Collibra AI Governance in public product materials.
- AWS SageMaker
- Azure ML
- Google Vertex AI
- Databricks
- Snowflake
- MLflow
- ServiceNow
- Slack
- Jira
Pricing
Enterprise subscription; contact sales for custom quote based on users, assets, modules.
Sources
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