How do you model failure probability in LLM pipelines?

Failure probability is modeled using historical error rates, uncertainty signals, retrieval quality, and system telemetry.

LLM failures can be predicted probabilistically using signals like token entropy, retrieval confidence, past error distributions, and user feedback. Systems combine these into a composite failure risk score. This allows proactive mitigation such as rerouting to safer models or triggering verification pipelines before output delivery.