U09IC·09Internal
AI Quality Scoring
AI-powered customer service quality scoring
overview
A quality tool that scores customer-service conversations with Gemini. It takes on a good part of the manual QA work, and supervisor corrections gradually feed back into the AI rules.
- Every conversation auto-scored on tone, speed, professionalism and resolution
- Self-improving loop: supervisor overrides feed back into the AI rules
- Edit prompts from the UI without code: AI re-evaluates on update
- AI accuracy stats, rule-suggestion engine, daily trend reports
Next.jsReactGemini AIBigQueryVercel
impact / value
impact / value
From scoring every conversation by hand to just calibrating AI's results, and making decisions on data.
10 min → 30 sec
Evaluation time (~20× faster)
Every agent, daily
10+ conversations auto-scored
Scoring → calibration
QA no longer scores from scratch
Self-improving
Accuracy rises as it's trained
Before: Every conversation was scored from scratch by hand; a single evaluation took ~10 minutes on average, and coverage was necessarily limited.
After: Now each agent's daily conversations are auto-scored with Gemini (~30 seconds each); the quality team only calibrates. As calibration feeds back into the prompts the model keeps getting sharper, and decisions rest entirely on data.
screens · 6
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