ACX Improvement Loop
Classifying conversations into customer-authored taxonomies
Ada pairs customer-authored intents, full-transcript reading, and a self-improving loop vs. an LLM judge—reaching 90%+ topic and 80%+ intent accuracy.
Custom metrics for conversation analysis
How Ada built a per-conversation quality-scoring judge that scales to millions of conversations and stays calibrated to each customer's definition of "good."