A/B Testing Analytics and Reporting in Logs

Problem: A/B experiments lack clear labeling and result visualization.

Use case: Make data-driven decisions about prompts, flows, and model choices.

Functionality: Experiment labels on runs, statistical analysis with confidence intervals, dashboards for variant comparison, and filtering/grouping by experiment tags.