Drata automates governance, risk, compliance, and assurance—resulting in a stronger security posture, streamlined security reviews, lower costs, and less time spent preparing for annual audits.
Over the last few years, artificial intelligence has moved from an experimental technology to a core product functionality. Organizations rely on AI-enabled product and operates the underlying model.
Simultaneously, AI systems behave dynamically with evolving models, training data changes, inference behavior shifts, and expanding integrations. Static documentation and point-in-time assessment fail to capture these realities, often leaving gaps between perceived risk and actual exposure.
As these two challenges collide, they create a trust gap where vendors struggle to prove that they govern, monitor, and control AI effectively.
The Core Challenge: Proving AI Is Safe for Customers
A primary challenge that AI product companies face is that no unified set of best practices exists. Unlike traditional security and compliance requirements, AI risk management relies on a scattered and evolving set of frameworks, principles, and regulations.
