The AI extraction + deterministic scoring separation is exactly right, and the reasoning holds beyond SOW analysis. I hit the same wall building internal decision tools: LLMs are useful architects but terrible engines. Same principle — AI reads and structures, deterministic compiler owns the output. Same input, same result, traceable, auditable. The governance argument alone justifies the split even before you consider reproducibility. What does your scoring engine do when the AI extraction is ambiguous or incomplete — does it fail loudly or degrade gracefully?