Data & AI Governance

Policy Enforcement for Snowflake and Databricks

Scan and classify data without relying on the limited classification capabilities provided by cloud platforms to enable automated and consistent application of policy actions across Snowflake and Databricks environments. This robust functionality supports the orchestration of masking and row filtering policies to configure access and visibility privileges to sensitive data tables in these systems.

AI Governance Inventory Global/Local Functionality

Establish standardized global records for AI systems, models, and datasets while maintaining contextual variations to enable their use across business units, use cases, and lifecycle stages. This capability ensures consistent governance practices across the enterprise while accommodating variations in regulatory frameworks, risk profiles, and needs across the AI lifecycle.

AI Automations to Detect Models & Agents

Discover AI model and agents across platforms and centralize related models, decisions, outputs, and risks in a single searchable inventory. With our AI Automations, you can capture metadata including model type, owners, input/output behavior, and associated datasets. This provides a real-time, searchable inventory that serves as the foundation for governance policies, risk assessments, and audit trails. AI Automations are deployed using the lightweight worker node, which grants a simplified experience and minimizes the need for specialized personnel. It can retrieve all prerequisites and images from a cloud API, ensuring smooth, firewall-independent deployment.

OneTrust currently supports the following systems to conduct AI automations. The automation setup is the same for each, only their credentials aspects are unique. Each system has its own supported list of discoverable resources (models, agents, datasets), so refer to the feature guide for exact details.

• Amazon Bedrock

• Amazon SageMaker

• Azure Foundry

• Databricks

• GCP Vertex