End-to-End AI Voice Agent
Budget: $1,500 – $3,000 AUD
I need a production-ready AI voice agent that answers customer-support calls directly on the phone line, handling both general inquiries and technical support without relying on IVR trees or the usual STT-TTS pipeline. The goal is true speech-to-speech conversational flow powered by a modern, unified neural model so callers experience natural, low-latency dialogue from the first “hello”.
Core workflow
• Incoming calls land on RingCentral; the agent picks up, converses in real time, and can transfer or conference in a human when confidence drops.
• Throughout the call, it fetches answers from my knowledge base or external APIs, then logs the full interaction—audio plus structured summary—into Zoho CRM under the correct contact or ticket.
• At hang-up, the caller receives a follow-up email (template supplied) triggered from Zoho.
Must-haves
• End-to-end voice model only—no separate speech-to-text or text-to-speech layers.
• Latency comparable to human conversation.
• Natural turn-taking, interruption handling, and sentiment detection to decide whether to escalate.
• Dockerised deployment with environment variables for RingCentral SIP creds, Zoho OAuth, and knowledge-base endpoints.
• Clear documentation and a short demo video showing a live call routed through RingCentral into the agent and the resulting Zoho log.
Acceptance criteria
1. A test call lasting at least three minutes in which the agent correctly answers two general questions and one technical question, all echoed in Zoho as separate conversation notes.
2. Average end-to-end latency per turn under 600 ms.
3. Handover command (“let me connect you to a specialist”) successfully routes to a live extension.
4. Complete source code, Dockerfile, and setup guide delivered.
If you have hands-on experience with speech-to-speech systems such as OpenAI’s new voice models, NeMo-Guardrails, or similar, let me know—speed to quality prototype matters more than brand-name libraries.
See comprehensive brief.
Core workflow
• Incoming calls land on RingCentral; the agent picks up, converses in real time, and can transfer or conference in a human when confidence drops.
• Throughout the call, it fetches answers from my knowledge base or external APIs, then logs the full interaction—audio plus structured summary—into Zoho CRM under the correct contact or ticket.
• At hang-up, the caller receives a follow-up email (template supplied) triggered from Zoho.
Must-haves
• End-to-end voice model only—no separate speech-to-text or text-to-speech layers.
• Latency comparable to human conversation.
• Natural turn-taking, interruption handling, and sentiment detection to decide whether to escalate.
• Dockerised deployment with environment variables for RingCentral SIP creds, Zoho OAuth, and knowledge-base endpoints.
• Clear documentation and a short demo video showing a live call routed through RingCentral into the agent and the resulting Zoho log.
Acceptance criteria
1. A test call lasting at least three minutes in which the agent correctly answers two general questions and one technical question, all echoed in Zoho as separate conversation notes.
2. Average end-to-end latency per turn under 600 ms.
3. Handover command (“let me connect you to a specialist”) successfully routes to a live extension.
4. Complete source code, Dockerfile, and setup guide delivered.
If you have hands-on experience with speech-to-speech systems such as OpenAI’s new voice models, NeMo-Guardrails, or similar, let me know—speed to quality prototype matters more than brand-name libraries.
See comprehensive brief.