AI-Powered Customer Service & Appointment Booking System
Conversational booking system that pairs Twilio telephony with a fine-tuned LLaMA model for real-time, voice-driven appointment scheduling.
Python
Django
React
LLaMA
Twilio
MySQL
Overview
A customer-service system that answers calls, holds a natural conversation, and books appointments end-to-end without a human in the loop. Built around a fine-tuned LLaMA model wired into Twilio for telephony and a Django + React stack for the booking workflow.
What it does
- Accepts inbound calls via Twilio and streams audio into the model layer
- Generates dynamic, context-aware conversational responses using a fine-tuned LLaMA model
- Books, reschedules, and cancels appointments against a MySQL-backed Django backend
- Surfaces a React dashboard for staff to view, edit, and override bookings in real time
Stack
- Voice & telephony — Twilio
- Model — Fine-tuned LLaMA, served behind a Python service
- Backend — Django + MySQL
- Frontend — React
Why it mattered
Manual phone-based booking was the bottleneck. Replacing the first call leg with a conversational agent kept the customer experience warm while removing the back-and-forth that staff used to handle by hand.