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AI/ML2024

AI Voice Calling Bot (Real-Time Lead & Worker Interaction)

Streaming AI voice bot for automated worker assessments using WebSockets and OpenAI Realtime API.

Overview

A real-time AI voice calling system built to automate the worker onboarding assessment process at Broomees. The bot conducts live phone-like conversations, evaluates responses, and scores workers automatically.

Architecture

  • Streaming Voice Pipeline: Audio streamed via WebSockets with sub-200ms latency
  • OpenAI Realtime API: Used for speech-to-text and response generation
  • Assessment Engine: Custom scoring logic based on conversation analysis
  • Integration: Plugged into the worker onboarding flow seamlessly

Technical Highlights

// WebSocket audio streaming pipeline
const audioStream = new WebRTCStream({
  sampleRate: 24000,
  channels: 1,
  encoding: 'pcm16'
});

The system reduced assessment time by 70% and enabled 24/7 automated onboarding.

Impact

Results & Metrics

10k+
Users
at launch
98%
Uptime
< 1s
Load time
4.9★
App rating
What it does

Key Features

🤖

AI-Powered Search

Semantic search using embeddings for smarter results.

📱

Cross-Platform

Native feel on iOS, Android, and the web.

🔒

End-to-End Encryption

All user data encrypted at rest and in transit.

Real-Time Sync

Live updates via WebSockets across all devices.

How it was built

Development Process

Phase 1

Discovery & Planning

Defined scope, mapped user flows, and set up the monorepo.

1 week
Phase 2

Design System

Built tokens, components, and Figma prototypes.

2 weeks
Phase 3

Core Development

Implemented authentication, data layer, and main features.

5 weeks
Phase 4

Testing & Launch

E2E tests, performance tuning, and staged rollout.

1 week
Problem solving

Challenges & Solutions

Contribution

My Role

Lead Engineer & Designer

I was solely responsible for the full product, from initial concept to production deployment.

  • Architected the backend API and database schema
  • Built the design system from scratch in Figma
  • Implemented CI/CD pipeline with GitHub Actions
  • Conducted user interviews and iterated on feedback
See also

Related Projects

Tech Stack

Node.jsWebSocketsWebRTCOpenAI Realtime APIExpress.jsRedisCeleryMongoDB

Links

🔗 Live Project

Private repository