Governance for systems that make decisions

AI systems are moving from answering questions to taking actions. They call tools, change records, trigger workflows and make decisions across organizational boundaries. The infrastructure for running these systems is advancing quickly; the infrastructure for governing them is not.

Most teams end up assembling governance from scattered prompts, application checks, provider settings and operational conventions. That creates a gap between what a system is allowed to do and what anyone can later prove it did. It also makes policy difficult to change without rewriting the applications around it.

Kavach exists to make that boundary explicit. It provides a shared place for policy, authorization, evaluation and audit evidence so AI systems can remain flexible while their important decisions stay controlled, explainable and operationally owned.