We Analyzed 10,000 Automated Healthcare Voice Calls — Here's What We Found

Last October, we hit a milestone at Autor that I didn't see coming: Loquent, our production voice AI platform, processed its 10,000th automated healthcare call. Instead of celebrating, we did what any team of engineers would do — we pulled the data, locked ourselves in a room for a week, and tore apart every single pattern we could find. What we discovered changed how we build voice AI. Some of it confirmed our assumptions. Most of it didn't. The Setup For context, Loquent handles automated calls for healthcare and dental clinics across Canada. We're talking appointment scheduling, confirmations, cancellations, insurance verification questions, and general intake routing. The system runs 24/7 on a stack built with Twilio for telephony, Anthropic Claude for conversation intelligence, Deepgram for speech-to-text, and ElevenLabs for text-to-speech. We built the first version in under 8 weeks and have been iterating on it for the past six months. The 10,000 calls in this dataset span 14 cl