AI voice agent

The same agent that answers your chat can answer the phone. Hiveflow orchestrates the brain — understanding, tools, CRM, escalation — and a voice provider (Twilio, or a voice-AI provider) turns speech into text and text back into a natural voice. You wire the two together with the nodes you already have.

The pattern

Voice provider (call) → Webhook Input → LLM Agent ⇄ CRM (contacts & cases)
                                                  ⇄ Kanban (ticket board)
                        LLM Agent → HTTP Request → Voice provider (speaks the reply)
                                 ↘ Human in the Loop (transfer to a person)

The voice provider handles the call and speech-to-text / text-to-speech. Hiveflow handles what to say and what to do.

Step by step

1. Webhook Input (Base) — the voice provider posts each caller utterance (the transcript) to your flow. Enable context memory so the agent remembers the conversation across turns.
2. LLM Agent (AI) — objective: "You are ACME's phone agent. Speak naturally and briefly, one question at a time. Register the caller and their reason in the CRM. If the caller asks for a person, is upset, or you can't resolve it, escalate." Prompt: {{transcript}}.
3. HiveApp → CRM / Kanban (Tools) — wire them into the LLM node as function-calling tools so the call is logged and a ticket is created while you talk.
4. HTTP Request (Base) — send the agent's reply back to the voice provider, which speaks it to the caller. (Or expose the flow as an MCP tool the provider calls.)
5. Human in the Loop (Base) — on the escalation branch, ask the provider to transfer the call to a rep, with the full transcript as context.

Inbound vs outbound

• Inbound (support): the provider forwards incoming calls to the Webhook; the agent answers 24/7 and books, resolves or escalates.
• Outbound (sales): trigger the flow from a new CRM lead (Trigger or a scheduled run), and have the HTTP Request tell the provider to place the call and qualify the lead by voice.

Variations

• Keep an auditable transcript with human takeover by adding a Chat tool instance alongside the CRM.
• Reuse your product docs as Skills so the voice agent answers from your real knowledge — the same knowledge your chat agent uses.
• Run the exact same agent on chat and WhatsApp by swapping the input node — one brain, every channel.

Genius prompt: "Create a voice agent flow: a webhook that receives call transcripts, an AI agent connected to a CRM and a ticket Kanban, an HTTP node to reply to the voice provider, and human escalation."