Rethinking DataAI Security & Resilience

AI agents operate autonomously at machine speed, accessing data, using permissions, and taking actions across systems. A single mistake or compromise can quickly escalate from a security issue into a business disruption.

Most tools operate in silos, with separate views of data, identities, AI activity, and recovery. This fragmented visibility makes it difficult to detect, understand, and respond to cascading AI-driven risks.

A unified approach combines data security, AI governance, threat detection, policy enforcement, and recovery into a single control plane, enabling organizations to manage AI risks end-to-end.

It is a framework for identifying AI risks, enforcing controls to prevent misuse, and rapidly recovering from AI-driven mistakes or incidents through precise, visibility-driven remediation.

Traditional recovery methods can be slow and disruptive. Surgical resilience enables organizations to quickly pinpoint and reverse specific AI-driven errors, minimizing downtime, data loss, and business impact.