AI→Human Escalation Hub
Seamless handoff from AI agents to human representatives with complete conversation history, context preservation, and intelligent routing
Active Escalation Cases
Intelligent Escalation Triggers
Complex Query Detection
AI identifies technical complexity beyond autonomous resolution capability
Examples:
- •Multi-system integration issues
- •Advanced troubleshooting
- •Policy exceptions
Customer Frustration
Sentiment analysis detects increasing frustration or dissatisfaction
Examples:
- •Repeated failed attempts
- •Negative sentiment escalation
- •Explicit dissatisfaction
Explicit Request
Customer directly requests to speak with human representative
Examples:
- •"I want to talk to a person"
- •"Connect me to an agent"
- •"Human support please"
Low Confidence Score
AI confidence in resolution path falls below threshold (< 75%)
Examples:
- •Ambiguous requests
- •Insufficient training data
- •Edge case scenarios
Proactive Escalation Management
AI continuously monitors conversation quality, customer sentiment, and resolution confidence to identify optimal escalation moments. This ensures customers receive appropriate support level without unnecessary delays or repeated explanations.