AI Voice Agent.
Engineering case study by Priyansh Dobariya · Retell AI · FastAPI · MongoDB
A conversation that moves things forward.
Voice workflows for lead qualification, appointment scheduling, and contextual follow-ups.
Behind the build.
Built AI voice workflows for lead qualification and appointment scheduling.
Handled conversational context and follow-up workflows.
Implemented MongoDB-based state management with retry and recovery handling.
Tools & technologies
What this solves
Outbound leads need timely qualification and a path to scheduling without requiring a person to handle every first call.
How it works
A FastAPI backend contains prospect and campaign routes, Retell call initiation, Calendly integration, MongoDB prospect records, and jobs for scheduled calls and callbacks.
From input to outcome
A prospect is selected for a campaign, a call is initiated through Retell, and follow-up or scheduling services act on the call outcome. Scheduler jobs handle later calls and retries.
Decisions visible in the code
- Campaign and prospect services separate audience management from provider call initiation.
- Dedicated callback jobs provide a recovery path when the first conversation does not complete the process.
What the workflow enables
The workflow can turn outbound contact into a qualified follow-up or scheduling action while keeping prospect state available for later work.
The reviewed source does not establish call-volume, booking-rate, or provider uptime results.