Voice AI platform that orchestrates the full voice agent stack — LLM, voice, transcriber, system prompt, structured outputs, tool registry, phone numbers and call analytics. Central building block for both inbound receptionists and outbound callers across Nate Herk’s voice agent tutorials.

Key facts

  • Holds the system prompt, first message, model (GPT-4.1 or GPT-4o in the examples), voice and transcriber configuration
  • Supports assistant overrides — runtime variable substitution inside the system prompt via {{variable}} syntax, so each call can receive dynamic context (lead name, company, request)
  • Exposes structured outputs as a replacement for deprecated summary and success-evaluation fields; each field is typed (string, boolean, number) and can be reused across multiple assistants
  • Provides up to 10 free US phone numbers per account; Twilio numbers can be imported to bypass outbound call limits
  • Call lifecycle for outbound is two-step: POST to create a call, then GET on the call ID until status equals ended
  • Supports a Handoff tool (assistant-to-assistant) and a Transfer Call tool (to external human phone numbers)
  • Sends end-of-call reports to a configurable server URL with summary and structured data fields
  • Pairs natively with n8n via either HTTP webhooks or an MCP server trigger

Source references

  • [src-007] Nate Herk cluster — Nate Herk — Voice AI agents cluster (4 videos)

– Videos referenced: BO-jFbN4p8Y, y-cq_Qo4zVo, zWLZ3bVVwD8, Qt3zMBH-FNg

Robin Cartier perspective

This page is part of Robin Cartier's working AI knowledge graph: a practical research layer for production AI, recommendation systems, experimentation, GEO, and agentic web readiness.

The useful next step is to connect this concept back to applied product leadership and operating models.

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