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> Use this file to discover all available pages before exploring further.

# Post-call analysis

> Automatic AI summary, sentiment, intents, topics, action items and outcome scoring for every completed call.

After every completed call the platform automatically analyzes the
transcript in the background and attaches a structured report to the run.
You'll see it in the call details under **Call analysis**, and via the
[API](/en/api-reference/introduction) (the
`gathered_context.post_call_analysis` field on the run).

## What the report contains

* **Summary** - 3–5 sentences of prose in the language of the call.
* **Sentiment** - overall (`positive` / `neutral` / `negative`) with a
  score in the `-1.0 .. 1.0` range, optionally split by caller and agent.
* **Caller intents** - up to 5 short phrases describing what they wanted.
* **Topics** - up to 6 tags for the threads discussed.
* **Action items** - up to 6 concrete next steps
  (e.g. *"call back Thursday at 10:00"*).
* **Call outcome** - a `success` flag with a one-sentence justification of
  whether the call's goal was achieved.

## Where you see it

* **Call details** - the full report with section icons (outcome,
  sentiment, topics, intents, action items). While the analysis is
  running, a "Generating full analysis…" spinner is shown.
* **Overview and Analytics** - aggregated indicators: call mood (average
  score) and the most frequent topics, also per agent.
* **Agent improvement suggestions** - the analysis feeds the AI prompt
  improvement proposals in the agent editor (always subject to your
  approval).

## Example report (API)

```json theme={null}
{
  "summary": "The customer booked a table for 4 on Friday at 7:30 PM...",
  "sentiment": "positive",
  "sentiment_score": 0.62,
  "sentiment_per_speaker": {
    "user":  { "label": "positive", "score": 0.5 },
    "agent": { "label": "positive", "score": 0.7 }
  },
  "intents": ["table reservation for 4", "question about vegan options"],
  "topics":  ["reservation", "menu", "opening hours"],
  "action_items": [
    "Confirm the reservation by SMS before 6:00 PM",
    "Email the vegan menu"
  ],
  "success": true,
  "success_reason": "Reservation booked for Friday 7:30 PM.",
  "language": "en",
  "generated_at": "2026-04-23T22:15:01+00:00"
}
```

## Notes

* The analysis requires a transcript of at least \~50 characters - very
  short calls are skipped.
* The report language follows the **AI Summary Language** setting on the
  agent's **Settings** tab. The default, **Auto**, takes the language the agent
  itself speaks (from its transcriber and voice configuration), so an agent set
  to Polish gets a Polish report even after a short call. Only a
  multi-language agent follows the language of the call itself.
* The short `call_summary` and the full analysis are generated
  independently - even if the full analysis temporarily fails, the
  summary remains.


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