Nixflex - AI Voice Platform for Building AI Phone Agents

After every call, Nixflex runs an analysis pass over the transcript. You get a summary, the caller’s sentiment, whether the call succeeded, and any custom fields you’ve defined — automatically. No setup required for the defaults.

What you get out of the box

Every call record has these fields populated automatically:

Field	Type	Description
`call_summary`	string	1–2 sentence summary of what happened
`caller_sentiment`	enum	`happy`, `neutral`, or `frustrated`
`call_successful`	boolean	Did the caller get what they needed?
`extracted_data`	object	Your custom fields (see below). Empty `{}` if none configured.

These are the field names on the call record returned by GET /v1/calls/:id and GET /v1/calls. In the webhook payload the same data is delivered under flat, renamed keys: summary, sentiment, successful, and extracted.

Custom data extraction

Beyond the defaults, you define exactly which fields to pull from each call. Set data_extraction_fields on the agent — an array of field definitions:

{
  "data_extraction_fields": [
    {
      "type": "text",
      "name": "caller_name",
      "description": "The caller's first name",
      "optional": true
    },
    {
      "type": "boolean",
      "name": "wants_callback",
      "description": "Whether the caller asked for a callback"
    },
    {
      "type": "selector",
      "name": "service_requested",
      "description": "Which service the caller asked about",
      "choices": ["check-up", "cleaning", "whitening"]
    },
    {
      "type": "number",
      "name": "party_size",
      "description": "Number of people for a booking"
    }
  ]
}

For each call, the agent reads the transcript and fills in what it can. Missing fields come back as null — the agent won’t invent data.

Field types

Type	Returns	Use for
`text`	string	Names, emails, free-form values. Optional `format_example` guides the format.
`selector`	string from `choices`	Categorising into a fixed set of options. Requires `choices`.
`boolean`	`true` / `false`	Yes/no questions (callback wanted, issue resolved).
`number`	number	Quantities, counts, party sizes.

Field properties

Property	Required	Notes
`type`	yes	One of `text`, `selector`, `boolean`, `number`
`name`	yes	Key used in `extracted_data`. Keep it snake_case.
`description`	yes	What the agent should look for. Be specific — this drives accuracy.
`optional`	no	If `true`, the field stays `null` when not mentioned rather than guessed
`choices`	selector only	The allowed values
`format_example`	text only	Example of the expected format, e.g. `name@example.com`

The result lands in extracted_data:

{
  "extracted_data": {
    "caller_name": "Amir",
    "wants_callback": true,
    "service_requested": "check-up",
    "party_size": null
  }
}

On the API, your custom fields are keyed under extracted_data. In the webhook payload the same fields arrive under extracted.

When analysis runs

Inbound, outbound, and batch calls — all directions, always.
Calls with real conversation — if the caller spoke fewer than 2 turns or fewer than 10 words total (hang-ups, voicemail), the AI pass is skipped to save cost. Defaults fall back to a short summary and call_successful: false.
Asynchronously, after the call ends — by the time your webhook fires (~60s later), all fields are populated.

How extraction works under the hood

Analysis runs in two stages:

Base analysis — always runs. One AI call returns call_summary, caller_sentiment, call_successful.
Custom extraction — only runs if the agent has data_extraction_fields. A second AI call returns your custom fields.

Both stages use the AI and add roughly $0.001 to the call cost. It’s included in the per-minute price — no extra charge.

Configuring in the dashboard

Open your agent’s Post-Call Data Extraction panel. Add fields with the + Add button — pick a type, give it a name and description, and save. Extracted fields are delivered to your webhook after each call. No code required.

Reading analysis programmatically

Each call object includes the analysis inline — there’s no separate endpoint. See Get call for the full schema, or receive it via webhook.

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Best practices

Core concepts

In-call actions

Features

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Reference

Post-call analysis

What you get out of the box

Custom data extraction

Field types

Field properties

When analysis runs

How extraction works under the hood

Configuring in the dashboard

Reading analysis programmatically

​What you get out of the box

​Custom data extraction

​Field types

​Field properties

​When analysis runs

​How extraction works under the hood

​Configuring in the dashboard

​Reading analysis programmatically

What you get out of the box

Custom data extraction

Field types

Field properties

When analysis runs

How extraction works under the hood

Configuring in the dashboard

Reading analysis programmatically