The case for runtime assurance
in production AI.

Existing AI governance tools usually miss one of two things:

• Static checklists: Documents that describe what teams should do, but do not protect the application in production.
• Slow software layers: Software that adds so much latency or complexity that teams eventually route around it.

Enforce in the runtime path

We built TalosRed to sit between applications and models so policy can be enforced before unsafe traffic leaves the stack, not after an incident has already happened.

Validate quality continuously

Drift, prompt changes, and workflow regressions need to be measured continuously if AI is going to be treated like production infrastructure. That is the job of the evaluation layer.