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Post-Conversation Processing Now Available for Voice AI Assistants

21, Apr 2026

Voice AI Assistants now support Post-Conversation Processing, enabling actions triggered after a voice call ends. Unlike Insights, which provide read-only analysis, Post-Conversation Processing lets your agent execute any action it could perform during a live call, with full conversation context and no real-time latency constraints.

What's new

  • Post-call actions: Configure your assistant to execute tool calls, API requests, and other actions after the conversation ends, using the full context of the call that just happened.
  • Full conversation context: Post-conversation processing runs with the same LLM and data from the call, not a separate model working from metadata alone.
  • No latency ceiling: Without real-time voice constraints, post-conversation steps can use reasoning models and run complex multi-step workflows that would be too slow during a live conversation.
  • Mission Control configuration: Set up post-conversation processing directly in your assistant's instructions in the Mission Control Portal.
{
  "post_conversation_settings": {
    "enabled": true
  }
}

Why it matters

  • Voice AI agents that only talk and then stop are incomplete. The real work, updating a CRM, sending a summary email, filing a ticket, booking an appointment, happens after the caller hangs up. Until now, you had to build and maintain a separate pipeline to handle it.
  • Insights give you analysis. Post-Conversation Processing gives you action. A summary tells you what happened; a triggered workflow does something about it.
  • The same LLM that handled the call processes the post-call steps, so it carries full conversational context rather than working from a transcript summary. No information loss between the call and the follow-up.
  • No other voice AI provider offers this. The standard pattern is a separate post-call service that works from metadata, not an integrated processing layer with full call context.

Example use cases

  • A healthcare scheduling agent that confirms the appointment in the EHR and sends the patient a confirmation text after the call.
  • A sales qualification bot that creates a lead in the CRM, logs the conversation summary, and triggers a follow-up email sequence based on the prospect's stated interests.
  • A support agent that files a ticket with the relevant details, sets priority based on the caller's sentiment, and pings the on-call engineer if the issue is critical.
  • A collections agent that updates the account status, schedules a callback based on the promised payment date, and logs the payment arrangement.

Getting started

  1. In Mission Control, navigate to AI, then Assistants, and select your assistant.
  2. In the assistant's instructions section, write the post-conversation processing steps you want your agent to perform after each call.
  3. Specify which actions to trigger, including tool calls and API requests. Telephony-control tools (hangup, transfer, invite) are not available during post-conversation processing.
  4. Test with a live call and verify that post-call actions fire correctly in your logs.

Learn more in the Telnyx AI Assistants API reference or the Voice AI Agents product page.