Holistic AI Governance Platform

Classifies, assesses and mitigates AI-specific risks such as bias and robustness, with content libraries for regulations and frameworks including the EU AI Act, NIST AI RMF and ISO 42001.

Documents trust, risk and security assessments, testing and validation results, and remediation evidence for AI systems.

Maintains a centralized, discoverable registry of all AI use cases, applications, agents and models with metadata, ownership and deployment status.

Discovers the AI models, agents, MCP servers and AI-enabled applications in use across the organization, including those deployed without IT authorization, and keeps them in an inventory that records type, ownership and criticality. Discovery runs through traffic inspection and code repository scanning at minimum; some products add cloud provider, application server or AI engineering tool integrations. The inventory anchors exposure management and risk scoring.

Scores deployed AI models by risk level based on data sensitivity processed, deployment scope, capability classification, and applicable regulatory requirements.

Detects sensitive or regulated data in AI training, fine-tuning, or third-party LLM flows without appropriate controls, such as unencrypted PII in inputs or PHI sent to external APIs.

Tests LLMs and AI applications against a library of direct and indirect prompt-injection and jailbreak techniques, reporting which payloads bypass system instructions and safety controls.

Reports validated AI vulnerabilities with reproduction evidence, attacker context, and remediation guidance, mapped to the OWASP LLM Top 10, MITRE ATLAS, EU AI Act, and NIST AI RMF for auditable AI risk reporting.