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A conditional decision-preservation proposition: successful local admission implies that a specified synchronous policy would authorize the same action at the admission point, provided approval is sound, all policy dependencies are represented and current, observations are faithful, and consumption is atomic.
CAVA transforms the chaotic landscape of agentic AI actions into a standardized framework, enabling reliable governance and verification of AI behavior across heterogeneous environments.