Commit-Gated Execution for Regulated Artificial Intelligence

Kayllo™ introduces a deterministic execution governance architecture designed for deployment of artificial intelligence within regulated environments. As AI systems transition from analytical tools into externally effective actors capable of initiating operational, financial, and legal outcomes, existing computing architectures lack a formal mechanism governing when computation is permitted to create real-world effect. This work defines commit-gated execution, a control-plane model that separates computational output from externally effective state change. Under this model, AI systems generate provisional decisions that become operational only after deterministic qualification against a snapshot-bound governance context. The resulting activation event produces immutable transition evidence enabling independent verification, jurisdictional enforcement, and long-term auditability without reliance on runtime reconstruction. The paper positions execution governance as a new infrastructure layer within modern computing stacks, analogous to the historical emergence of transport encryption, zero-trust identity, and distributed orchestration. Rather than constraining model reasoning, the architecture governs activation itself, enabling regulated deployment of autonomous systems while preserving innovation. This publication presents the architectural principles underlying deterministic activation and establishes AI execution governance as a foundational requirement for trustworthy autonomous systems operating within financial, healthcare, public-sector, and critical infrastructure domains.