The architecture of enterprise financial audit systems and fraud detection engines has reached a historic inflection point. For decades, organizations have oscillated between two distinct paradigms: the brittle, highly deterministic rigidity of classical rule engines and relational database constraints, and the fluid, probabilistic, yet dangerously opaque nature of modern Large Language Models (LLMs). Classical engines fail when confronted with unstructured, rapidly evolving regulatory prose, wh...