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Post Call Extraction runs after a call ends. It reads the transcript with an LLM and writes structured results onto the call’s call_analysis object, so you can filter, report on, or sync insights to your CRM without manually reviewing each conversation.
Post Call Extraction dashboard showing various analytics categories and metrics

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How it works

  1. The call ends and Retell fires the call_ended webhook.
  2. Retell analyzes the transcript against your agent’s Post Call Extraction configuration.
  3. Retell fires the call_analyzed webhook. The call_analysis object is now populated on the call.
Because analysis runs after call_ended, the call_ended payload does not include call_analysis. Read results from the call_analyzed webhook or the Get Call API. See Consume the analysis data.
Retell does not populate custom Post Call Extraction fields for calls that were not connected or where no conversation took place. Check whether the field exists before using it.

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Built-in fields

Every call includes these built-in analysis fields. You can customize the prompts behind call_summary and call_successful and rerun analysis on past calls.
  • call_summary — high-level summary of the conversation.
  • user_sentiment — the caller’s overall sentiment.
  • call_successful — whether the call met the success criteria you define.
  • in_voicemail — whether the agent reached a voicemail instead of a live person.

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Custom analysis categories

Define your own fields on the agent’s Post-Call Data Extraction tab. Each field has a name, a description that tells the LLM what to extract, and one of four types: To set up your first custom field, see Define the information you want to extract.

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Next steps

To follow or step into calls while they’re still in progress, see Live monitoring. To score call quality across a sampled set of calls (hallucinations, resolution rate, latency, and more), see AI Quality Assurance. You can also use Post Call Extraction fields as filters when defining a QA cohort.