Comprehensive visibility and risk mitigation for AI systems and digital identities, with every model call audited, prompt injection and shadow AI detected, and controls mapped to ISO 42001 and the NIST AI RMF.
AI is already present in most environments — inside tools, inside workflows and inside the digital workers performing security tasks. AI Security makes that adoption visible, controlled and evidenced, with an audit trail behind every model call.
Every AI action in security operations is logged, attributable and reviewable, with human-in-the-loop controls applied where the decision warrants them and a record of what the AI did and did not do.
Prompt-injection patterns, LLM data exfiltration, anomalous AI API usage and compromised model credentials are detected in the same pipeline as every other signal.
AI tools and model endpoints in use across the environment are discovered from telemetry already being collected, including unsanctioned deployments.
AI governance operates as a first-class framework alongside PCI and ISO 27001, with model inventory, AI-specific evidence and board-level AI risk reporting.
Models, endpoints and digital workers discovered
Policy, approvals and human-in-the-loop applied
Every call audited, AI-specific threats detected
Mapped to ISO 42001 and the NIST AI RMF, reported
AI can be adopted in the security operations centre with guardrails, an audit trail and expert support behind the deployment.
AI governance is treated as any other framework, with model inventory, evidence and reporting mapped to ISO 42001 and the NIST AI RMF from live data.
Every digital worker action is recorded and attributable, with human-in-the-loop retained where it matters and both evidenced to an auditor.
AI Security runs on the common data context — the same telemetry, the same threat queue and the same control evidence as the rest of the platform.
Shadow-AI discovery and model-call auditing run on telemetry already collected, with no second collection footprint.
AI-specific detections run in the same pipeline as every other signal and cluster into the same threats.
Vulnerable model dependencies, ML libraries carrying CVEs and exposed model endpoints are tracked in the same asset inventory.
AI governance operates as a first-class framework, with model inventory and AI evidence collected continuously like any other control.
