customer_support · saas · workflow
Tackling AI Hallucinations in LLM Apps: Token Log-Probabilities as LLM Confidence Signal
LLMs can produce irrelevant or hallucinated responses, making it risky to surface their outputs directly to customers in support applications without a reliability filter.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · Support questions enter LLM service
A sample of 1000 support questions is run through the question answering LLM service.
Tools used
OpenAI API
Outcome
Using sequence log-probability as a confidence score revealed a 69% relative difference between the most and least confident LLM responses, supporting precision-recall-style filtering of poor-quality outputs before customer exposure.
Results
Volume69%
Grounding & classification
Source type: technical build writeup
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