SAS AI Governance Features List
AI model life cycle management
- Model life cycle management: End-to-end tracking from development to deployment and monitoring.
- Versioning and documentation: Version control, audit trails, automated model cards and documentation for transparency.
Risk, bias & performance monitoring
- Risk and bias detection: Tools to identify, assess and mitigate risks, including bias detection and fairness evaluations.
- Monitoring and performance tracking: Continuous monitoring, real-time alerts for model drift, performance degradation or anomalies.
Compliance & data governance
- Compliance and regulation support: Built-in frameworks for industry-specific regulations and audit documentation (e.g., EU Artificial Intelligence Act).
- Data governance: Ensuring data quality, integrity, traceability and data lineage tracking.
Collaboration & stakeholder engagement
- Stakeholder collaboration: Tools for team collaboration, feedback loops and model reviews.
- Scalability and flexibility: Ability to scale governance across projects and customizable workflows.
Reporting, dashboards & insights
- Reporting and dashboards: Comprehensive reporting tools and customizable dashboards for stakeholders.
Interoperability & integration
- Interoperability with other systems: Integration with business, IT and risk management systems, with API support for third-party applications.