1
AI Discovery & Inventory Management
Automatically detects and catalogs all AI systems, models, agents, and third-party applications across the organization including shadow AI, maintaining a continuously updated centralized AI register.
2
AI Risk Assessment
Uses a 12-Pillar Responsible AI Risk Framework with a database of over 2,000 AI risks to assess bias, explainability, privacy, security, operational, and compliance risks for each AI system.
3
Regulatory Compliance Mapping
Automatically maps AI inventory to 30+ global regulations including the EU AI Act, GDPR, HIPAA, ISO 42001, and various state and international laws, with cross-mapped controls to avoid redundant work.
4
Real-Time AI Observability
Monitors AI models and applications in production using an observability SDK to detect hallucinations, bias drift, performance degradation, PII exposure, and prompt injection attacks with alerts and enforcement actions.
5
Automated Evidence Collection and Audit-Ready Reporting
Automatically collects, validates, and organizes evidence against governance controls, maintaining audit-ready documentation and generating compliance reports on demand.
6
AI Lifecycle Governance
Implements structured governance checkpoints from AI ideation through retirement with role-based workflows, approvals, and human-review gates to ensure continuous governance.
7
Vendor AI Governance
Assesses and governs third-party AI vendors and embedded AI applications with automated assurance checks and risk gap assessments to manage supply chain AI risks.
8
Integrations and APIs
Integrates with enterprise tools like Snowflake, Databricks, MLflow, GitHub, S3, Okta, and SIEMs to streamline AI governance workflows and data exchange.
