Whispey Documentation

Overview

Whispey is a professional voice analytics platform that helps you monitor, analyze, and gain insights from your AI voice agent conversations. Track performance metrics, analyze conversation quality, and optimize your voice agents with comprehensive analytics.

Quick Navigation

• Quick Start - Get up and running in minutes
• SDK - SDK documentation and guides
• Configuration - Set up your environment and configure Whispey
• Complete Implementation - Full LiveKit integration example
• Observability - Comprehensive monitoring and telemetry
• Examples - Real-world use cases and implementations
• API Reference - Complete API documentation

Key Features

Real-time Analytics

• Speech-to-Text (STT) metrics: Audio duration, processing time
• Large Language Model (LLM) metrics: Token usage, response time
• Text-to-Speech (TTS) metrics: Character count, audio duration
• Voice Activity Detection (VAD): Voice detection metrics
• Conversation flow and turn tracking

Conversation Analytics

• Full transcript with timestamps
• Turn tracking for user and agent interactions
• Performance insights and response times
• Success metrics and call completion rates

Dashboard Integration

View detailed analytics at the Whispey Dashboard:

• Call performance metrics
• Voice quality analysis
• Conversation flow patterns
• Usage statistics and cost tracking
• Business metrics and customer satisfaction

Getting Started

1. Install Whispey: pip install whispey or install from PyPI
2. Get Credentials: Sign up at Whispey Dashboard
3. Configure Environment: Set up your API key and agent ID
4. Integrate: Add Whispey to your LiveKit voice agent
5. Analyze: View insights in the dashboard

Examples and Resources

• GitHub Examples: https://github.com/PYPE-AI-MAIN/whispey-examples
• Live Examples: Check out real-world implementations and use cases

Support

• Website: https://whispey.xyz/
• PyPI: https://pypi.org/project/Whispey/
• Email: deepesh@pypeai.com
• Examples: GitHub Examples Repository