Confidence Scoring

A practical example

Example: an agent classifying inbound leads by intent auto-routes scores above 0.85 to the sales queue and sends anything below to a human reviewer, with the threshold tuned after the first month.

What to evaluate before investing

• Ask whether confidence thresholds are configurable per workflow and whether you can see the score distribution on your own data.
• Check if scores are exposed in logs and analytics, so you can correlate low-confidence cases with downstream errors.
• Test calibration: do items scored 0.9 actually turn out right about 90 percent of the time on your content?

Limitations and tradeoffs

Models can be confidently wrong; a high score is not a guarantee, so confidence should trigger routing decisions, not replace verification on critical actions.