Post-call analysis

Every endpoint on this page requires either a Clerk-issued JWT (Authorization: Bearer <token>) or an organization API key (x-api-key: pk_…). Anonymous calls return 401 Unauthorized. See Authentication for the full setup.

Once a call ends, Agntix runs an analysis pass over the transcript. Configure what to extract on the agent’s Analytics tab — open any agent from Agents in the left nav, then switch to the Analytics tab on the right-hand panel. Four independent toggles are available. Enable only the ones you need.

Toggle	What it returns	Where it appears
Intent Recognition	Best-fit intent against your custom list	`analysis.intent.*`
Resolution Analysis	Whether the call achieved its objective	`analysis.resolution.*`
Sentiment	Score and label per call	`analysis.sentiment.*`
Data Extraction	Structured fields you defined	`analysis.extractedData.<name>`

All four surface in the analysis block of the session.ended webhook and in GET /api/v1/chat/sessions/{id}.

Intent Recognition

Classifies the purpose of the conversation against a list of intents you define under Custom Intent (comma-separated). Example for a delivery-confirmation use case:

Slot-Confirmed, Slot-Rescheduled, Customer-Unavailable, Wrong-Number, Refund-Request

The analysis returns:

string

Best-fit intent across the whole call.

number

Confidence score, 0 – 1.

string

Short LLM-generated rationale for the classification.

string

Best-fit on the trigger message (less useful for voice).

"intent": {
  "conversation": {
    "intent": "Slot-Confirmed",
    "confidence": 0.92,
    "explanation": "Customer agreed to Wednesday afternoon delivery."
  },
  "message": { "intent": null, "confidence": 0, "explanation": "…" }
}

Resolution Analysis

Classifies whether the call achieved its objective, against a resolution definition you provide. Click + Add Resolution Definition and describe in plain language what counts as resolved. Example resolution definition:

Call is resolved if the customer confirmed a delivery slot for the order. If a slot was discussed but not finalised, mark PARTIALLY_RESOLVED. If the customer refused or the call dropped, mark UNRESOLVED.

The payload then carries:

enum

RESOLVED / PARTIALLY_RESOLVED / UNRESOLVED / NOT_APPLICABLE.

number

0 – 1 confidence in the verdict.

string[]

The checklist points met during the call.

string[]

Quoted turns from the transcript supporting the verdict.

string

Short rationale.

"resolution": {
  "classification": "RESOLVED",
  "confidenceScore": 0.88,
  "satisfiedChecklistItems": ["delivery_slot_agreed"],
  "evidence": ["Customer: yes Wednesday afternoon works."],
  "explanation": "Customer agreed to a specific slot."
}

Sentiment

Returns a score and label per call:

enum

POSITIVE / NEUTRAL / NEGATIVE.

number

-1.0 – +1.0.

string

ISO-639-1 code; useful when callers may switch language mid-conversation.

"sentiment": {
  "conversation": {
    "sentiment": "POSITIVE",
    "score": 0.4,
    "detectedLanguage": "en",
    "explanation": "Customer was cooperative throughout."
  }
}

Data Extraction

Define a structured schema and Agntix will pull the values out of the transcript. Click + Add Data Extraction and define one schema entry at a time. Each entry asks for:

Name — the JSON key that will appear under analysis.extractedData.<name> in the webhook / session API.
Description — a one-line hint that tells the analysis model what to look for. Treat this like a mini-prompt: the more precise, the better the extraction.
Type — String, Number, Boolean, or Enum (for Enum you’ll also be asked for the allowed values).

Repeat for each field. There is no hard cap, but five tight fields beat fifteen fuzzy ones. Example schema for a delivery-confirmation call:

Name	Description	Type
`slotConfirmed`	True if the customer agreed to a specific delivery slot.	Boolean
`preferredDay`	The day the customer chose for delivery.	String
`preferredTimeWindow`	Time window the customer preferred.	Enum (`Morning`, `Afternoon`, `Evening`)
`callbackRequested`	True if the customer asked to be called back later.	Boolean
`callOutcome`	Short categorical outcome.	Enum (`Confirmed`, `Rescheduled`, `Unavailable`, `WrongNumber`)

Extracted values surface under analysis.extractedData.<name> in the webhook and the session detail API:

"extractedData": {
  "slotConfirmed": true,
  "preferredDay": "Wednesday",
  "preferredTimeWindow": "Afternoon",
  "callbackRequested": false,
  "callOutcome": "Confirmed"
}

Keep field descriptions specific and unambiguous. A description like “True if the customer agreed to a specific delivery slot (e.g. ‘Wednesday afternoon’ counts, ‘sometime next week’ does not)” is much more reliable than “Did they confirm?”.

Combined `analysis` block

When all four toggles are on, the full analysis block looks like this:

"analysis": {
  "summary": "Customer confirmed delivery slot for Wednesday afternoon.",
  "intent": {
    "conversation": { "intent": "Slot-Confirmed", "confidence": 0.92, "explanation": "…" },
    "message":      { "intent": null, "confidence": 0, "explanation": "…" }
  },
  "resolution": {
    "classification": "RESOLVED",
    "confidenceScore": 0.88,
    "status": "Completed",
    "satisfiedChecklistItems": ["delivery_slot_agreed"],
    "evidence": ["Customer: yes Wednesday afternoon works."],
    "explanation": "Customer agreed to a specific slot."
  },
  "sentiment": {
    "conversation": { "sentiment": "POSITIVE", "score": 0.4, "detectedLanguage": "en", "explanation": "…" },
    "message":      { "sentiment": null, "score": 0, "detectedLanguage": "N/A", "explanation": "…" }
  },
  "extractedData": {
    "slotConfirmed": true,
    "preferredDay": "Wednesday",
    "preferredTimeWindow": "Afternoon",
    "callbackRequested": false,
    "callOutcome": "Confirmed"
  }
}

Next steps

Webhook events

See the full session.ended payload that carries the analysis block.

Get Session

Pull the same analysis block via REST when you need it on demand.

Getting Started

Build

Real-time

SDKs & Examples

Operate

Post-call analysis

Intent Recognition

Resolution Analysis

Sentiment

Data Extraction

Combined `analysis` block

Next steps

Webhook events

Get Session

​Intent Recognition

​Resolution Analysis

​Sentiment

​Data Extraction

​Combined analysis block

​Next steps

Webhook events

Get Session

Intent Recognition

Resolution Analysis

Sentiment

Data Extraction

Combined `analysis` block

Next steps