## 🎯 Session Details
Table of Contents
Converza Case Study [~13:37-13:45]
- Type: Technical Presentation
- Speakers:
- Mo (CTO, Converza)
- Giuseppe (VP of AI, Converza)
- Session Goal: Share insights on implementing AI for call analytics at scale
🤖 Technical Implementation
System Evolution:
- 2001: Initial Analog System
- Hardware-based recording via PBX
- Manual human analysis
- Basic coaching data generation
- 2014: Digital AI Transformation
- Transition to AI-driven analysis
- Automated call monitoring
- Expanded data point collection
- 2024: Platform Enhancement
- Integration with PredaBase
- Scaled to analyze millions of calls monthly
- Customizable data point tracking
💡 Key Technical Metrics
Scale of Operations:
- Total calls analyzed: Over 1 billion
- Current volume: Millions of calls/month
- Implementation results: 78% conversion increase in 90 days (Wheeler/Caterpillar case study)
Data Analysis Capabilities:
- Agent Performance Metrics:
- Proper greeting detection
- Business offering tracking
- Appointment scheduling
- Customer service quality
- Client Side Analysis:
- Buying signal detection
- Lead quality scoring
- Prospect qualification
- Customer sentiment analysis
📈 Technical Architecture
Call Processing Pipeline:
- Call Recording
- AI Analysis
- Data Point Extraction
- Insight Generation
- Action Recommendation
Key Features:
- Custom data point configuration
- Real-time analysis capabilities
- Integrated coaching systems
- Revenue impact tracking
- Automated quality scoring
This session demonstrated a practical implementation of AI technologies for large-scale audio analysis and business intelligence, showing how the architecture evolved from manual processes to sophisticated AI-driven analysis, with particular emphasis on the role of PredaBase in enabling scalable, real-time processing capabilities.