THE FIELD IS FRAGMENTED, THE ALTERNATIVES ARE PARTIAL, AND THE STANDARD IS ONE : On the Deterministic AI Landscape, the Components That Are Not Standards, and the Only Complete Architecture Available

The deterministic AI space is not empty. It is fragmented. There are inference libraries that achieve bit-perfect execution. There are commercial runtimes that provide deterministic deployment. There are certification frameworks thatdefine replay identity. There are proof-based reasoning architectures that abstain when a rule cannot be proven. There are deterministic language models that replace neural networks with symbolic pattern learning. Every one is a contribution. None is a complete standard. This paper states the taxonomy. It cites each alternative. It applies the same criteria to all ofthem: a bounded object, a specification, a verification mechanism, an attribution chain, and a deployable reference implementation. It then shows that ST-T1024 is the only entry that meets all five criteria in a single, open, Apache-2.0 package. The paper does not dismiss the alternatives. It locates them. A library is not a standard. Aruntime is not an architecture. A certification framework is not a specification. The field hascomponents. The field has one standard.