Case Study · Voice AI · Education
Multi-Agent Voice Coaching Platform
A real-time AI assistant that simulates structured conversations and provides feedback through coordinated agents. Designed as a deployable system for training, coaching, and learning applications.
Built
Status
Cloud Run
Deployment
JWT + WS
Realtime Stack
01
Overview
What this system demonstrates
This is not a standalone chatbot. It is a reference implementation for building conversational training systems — showing how multi-agent orchestration, real-time audio, and structured evaluation can be combined into a deployable product.
Real-time voice interaction
Multi-agent orchestration with structured handoffs
Structured evaluation and feedback
Deployable backend architecture
Session-based interaction design
02
Architecture
System design
The system uses a streaming architecture designed for real-time conversational interaction.
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WebSocket streaming backend
Session-based access control
Structured agent handoffs between interviewer, coach, and evaluator
Feedback generation with scoring rubrics
Deployable cloud architecture on GCP Cloud Run
03
Screenshots
Interface
04
Applications
Use cases
Training & Coaching
Interview preparation
Communication practice
Soft-skill training
EdTech
Language learning
Guided tutoring
Assessment workflows
Internal Tools
Sales practice
Customer interaction training
Onboarding simulations
Working on a similar use case?
I'm open to comparing notes on architecture, scope, and prototype direction for voice AI and training systems.