AI governance

Create and manage AI use cases with risk classification, framework linking, team assignment, and approval workflows.

Collect structured AI project requests through branded public forms with built-in risk scoring.

Every intake form field type, its settings and what is checked when a form is submitted.

Work out numbers from other answers on an intake form with formulas.

Show an intake form field only when other answers match, with the conditions each field type supports.

Send intake submissions to expert or regular reviewers by risk score, and run second reviews.

Register and track all AI models across your organization.

Track the AI applications your teams use, with owners, approvals, policies, and risk.

Track models from development through deployment and retirement.

Tier models, run independent validations, track findings, monitor metrics against thresholds, and produce a board-level attestation for SR 26-2, SS1/23, and OSFI E-23.

Coordinate AI governance activities and compliance tasks across your teams.

Document, track, and resolve AI-related incidents effectively.

Gather and organize evidence for compliance and audits.

Visualize relationships between models, vendors, risks, and use cases.

Track user actions, system events, and application logs.

Public transparency portal for sharing your AI governance practices.

Register and track datasets used by your AI systems, with PII detection and bulk upload.

Discover and manage service accounts, technical users, and system identities across connected source systems.

View compliance progress, risk summary, and key metadata for a use case.

View which AI models from the inventory are connected to a project.

Set up multi-approver sign-off workflows for use cases, policies, and models.

Share read-only views of resources with external stakeholders via expiring links.

Cross-framework intelligence layer with control mappings, scenario recommendations, and unified coverage analysis.