AI Governance, Risk & Security

Models in production carry risk: drift, bias, misuse and unclear ownership. The governance we put around them means an inventory, controls, monitoring and an audit trail that stands up to review. Regulators want to see more than a model that works. They want evidence that someone controls it.

Guardrails at runtime

AI opens new ways to leak data, and new ways for someone to misuse a system. Runtime guardrails block unsafe actions, mask sensitive data, and stop prompt-injection before it reaches your systems. Teams get to use AI while the risky paths stay closed by default.