> ## Documentation Index
> Fetch the complete documentation index at: https://docs.volubile.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Data Extraction

> Extractors are a key feature of Volubile that enables your voice agents to identify and automatically collect specific information during phone conversations.

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## Structure of an Extractor

Each extractor in Volubile consists of three fundamental elements:

<CardGroup cols={3}>
  <Card title="Name" icon="tag">
    Unique identifier used to reference the extractor in your system
  </Card>

  <Card title="Description" icon="file-lines">
    Detailed explanation of the data to be extracted, serving as a guide for the AI model
  </Card>

  <Card title="Type" icon="layer-group">
    Category of extractor defining its behavior and capabilities
  </Card>
</CardGroup>

## Types of Extractors

Volubile offers three distinct types of extractors, each suited to specific needs:

### General Information

<Note>
  Standard type of extractor that captures simple textual information such as names, phone numbers, emails, or references.
</Note>

Examples of use:

* Customer's first name
* Last name
* Phone number
* Email address
* Customer reference

### Date

<Note>
  Specialized extractor for identifying and properly formatting temporal information mentioned during the conversation.
</Note>

Examples of use:

* Appointment date
* Date of birth
* Availability period
* Desired deadline

### Extractor Group

<Note>
  Special type that allows logically grouping several related extractors into a single entity. An Extractor Group can contain other extractors of all types.
</Note>

Examples of use:

* Complete contact details (grouping name, phone, email)
* Delivery information (grouping address, date, time slot)
* Booking details (grouping date, number of people, preferences)

## Configuration Interface

To create a new extractor, follow these steps:

1. Go to the "Extractors" tab in your Volubile dashboard
2. Click on the <strong>Add Extractor</strong> button (represented by the "+" icon)
3. Fill out the configuration form

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</Frame>

### Organizing Extractors

Extractors can be hierarchically structured to reflect the logical structure of the information to be collected:

* **First-level Extractors**: Represent general categories of information
* **Sub-extractors**: Detail specific points within a category

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In the illustrated example, we have configured:

1. **Customer Information** - A group extractor for customer data
2. **Quote Request** - A group extractor for quote requests, containing three sub-extractors:

* **Number of Attendees** (Type: General Information) - Captures the number of participants in the seminar
* **Location** (Type: General Information) - Records the seminar location
* **Event Date** (Type: Date) - Identifies the planned date for the event

<Warning>
  For changes to take effect, you need to publish the new configuration by clicking the **Publish** button after saving it.
</Warning>