This paper introduces Decision Infrastructure as a governance-first computational layer for modern digital systems. Unlike traditional architectures that focus on computation, storage, and prediction, Decision Infrastructure formalizes decision-making as a structured, auditable, reproducible, and risk-aware computational process. The proposed framework defines decisions as first-class system objects with explicit evidence, governance constraints, risk models, uncertainty handling, and deterministic replay capability. A mathematical optimization model is introduced to evaluate decisions under value, risk, uncertainty, and optionality trade-offs, while ensuring compliance with governance constraints and human-final authority. The AICOS reference architecture demonstrates how Decision Infrastructure can be implemented as a layered system consisting of evidence, risk, governance, decision engine, and replay modules. This work aims to establish Decision Infrastructure as a foundational paradigm for next-generation AI systems, financial technologies, and governance-critical computing infrastructures.
YASIN KALAFATOGLU (Mon,) studied this question.