What to build
A working example of a Deepgram voice agent that can detect when a conversation should be escalated to a human agent and perform a warm handoff — transferring the live transcript, conversation summary, and detected intent to the human agent's interface. Demonstrates the complete escalation flow: AI handles initial interaction → detects escalation trigger → summarizes context → transfers to human with full conversation history.
Why this matters
Production voice agents need a graceful path from AI to human support. Teams deploying voice agents in customer service, healthcare intake, and sales qualification need reliable escalation when the AI reaches its limits — and the human agent receiving the call needs full context to avoid making the customer repeat themselves. This is a critical pattern for enterprise voice agent deployments and one of the most-requested capabilities from teams evaluating voice agent platforms.
Suggested scope
- Language: TypeScript (Node.js backend + React frontend)
- Deepgram APIs: Voice Agent API, Audio Intelligence (intent detection, summarization)
- What to include:
- Voice agent with function calling configured for escalation triggers
- Intent-based escalation detection (e.g., "speak to a human", frustration sentiment)
- Automatic conversation summarization at escalation point
- Human agent dashboard showing: live transcript, conversation summary, detected entities, and customer intent
- WebSocket event handling for handoff coordination
- Post-handoff: human agent sees full AI conversation history with timestamps
Acceptance criteria
Raised by the DX intelligence system.
What to build
A working example of a Deepgram voice agent that can detect when a conversation should be escalated to a human agent and perform a warm handoff — transferring the live transcript, conversation summary, and detected intent to the human agent's interface. Demonstrates the complete escalation flow: AI handles initial interaction → detects escalation trigger → summarizes context → transfers to human with full conversation history.
Why this matters
Production voice agents need a graceful path from AI to human support. Teams deploying voice agents in customer service, healthcare intake, and sales qualification need reliable escalation when the AI reaches its limits — and the human agent receiving the call needs full context to avoid making the customer repeat themselves. This is a critical pattern for enterprise voice agent deployments and one of the most-requested capabilities from teams evaluating voice agent platforms.
Suggested scope
Acceptance criteria
Raised by the DX intelligence system.