How do you design decision engines on top of LLM outputs?

Decision engines convert LLM outputs into structured actions using rules, policies, and confidence scoring.

LLMs generate probabilistic outputs that cannot directly trigger business actions. Decision engines validate outputs, apply business rules, compute confidence thresholds, and map responses to structured actions. This is critical in enterprise workflows like finance, healthcare, or automation systems.