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AI Voice Bot with Human Handoff

Customer challenge

IVR menus impose a rigid, menu-driven experience that frustrates callers and limits deflection to narrow, scripted scenarios. When callers say "I want to check my claim status" and are presented with "Press 1 for billing, Press 2 for claims…", containment rates are poor and CSAT suffers.

Deploying a voice AI bot that genuinely understands natural speech has been difficult: traditional NLU-based voice bots are expensive to train, degrade quickly as product information changes, and fail silently when handed off to agents without context.

ExpertFlow's approach

ExpertFlow's voice AI layer uses Jambonz for voice application logic and integrates with configurable speech engines (including ElevenLabs for voice synthesis) and LLM backends for natural language understanding. Call forking via ExpertFlow's RTC layer sends audio to the AI layer in real time without touching the SIP signaling path — the call remains stable even if the AI layer experiences latency.

The bot retrieves answers from the customer's knowledge base via RAG, so policy and product information is always current without model retraining. When the bot determines escalation is needed — by intent, sentiment, or explicit caller request — it triggers a structured handoff to the routing layer. The agent receives the full bot transcript, identified intent, and sentiment score at the moment of connection. No context is re-asked.

Why ExpertFlow wins here

Unlike cloud CCaaS platforms that bundle a proprietary voice bot with limited integration depth, ExpertFlow's voice AI is architecturally decoupled: the dialog layer, the speech engine, and the LLM are independently configurable. Customers can run a local speech engine on-premise for data residency compliance while using a cloud LLM for reasoning — or run everything locally. The handoff path uses the same routing and conversation model as human-to-human transfers, so context carries naturally.

Typical deployment context

Contact centres with high inbound call volume where a significant fraction of calls are routine and repeatable. Regulated industries (insurance, banking, healthcare) where data residency constraints preclude sending audio to cloud-only AI services benefit most from ExpertFlow's deployment flexibility. Often deployed alongside the chat bot pattern (efv-sol-003) to provide consistent AI self-service across channels.

Open Items

  • [x] Confirm all features in features_included exist in the catalog (forward refs)
  • [x] Set decomposition_status: clean once Window 1 features are committed
  • [x] Derive primary_axioms from features (run bmad-catalog-intake)
  • [ ] Confirm on-premise LLM + on-premise speech engine features are captured