Holistic AI Governance Platform

Automatically discovers AI models, LLM API connections, ML pipelines, and AI-enabled SaaS applications in use across the organization, including those deployed without IT authorization.

Maps the AI inventory and controls to EU AI Act risk classification, ISO/IEC 42001, and NIST AI RMF, generating auditable evidence for each framework.

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.

Autonomously plans and executes multi-step adversarial campaigns against AI systems, emulating real attacker workflows across reconnaissance, exploitation, and escalation rather than running a fixed checklist of tests.

Re-runs red-team campaigns continuously and at release gates in the CI/CD pipeline as models, prompts, and configurations change, catching new exploit paths before and after deployment.