Data Extraction Stage

The Data Extraction stage systematically collects information from callers. Define the variables you need, and the AI asks for and validates each piece of data.

Overview

Data Extraction nodes are ideal when you need to:

Collect customer information (name, email, phone)
Gather order details
Capture booking requirements
Validate input formats

Data Extraction nodes are colored purple on the canvas.

Configuration

Extraction Method

Method	Description
Ask User	The agent explicitly asks for each piece of information
Infer	The agent extracts information mentioned naturally in conversation

Ask User
Infer

The agent asks for each variable directly:

Agent: "May I have your full name, please?"
Caller: "John Smith"
Agent: "Thank you, John. And what's your email address?"

Best for: Forms, registrations, structured data collection

The agent extracts data from natural conversation:

Caller: "Hi, this is John Smith calling about order 12345"
Agent: (internally captures: name="John Smith", order_number="12345")

Best for: Conversational flows where users volunteer information

Max Attempts

Number of times to retry if validation fails (default: 3). After max attempts, the conversation continues without the variable (if not required) or triggers a fallback transition.

Variables

Each variable defines a piece of information to collect:

Variable Properties

Property	Description
Name	Identifier (snake_case, e.g., `customer_name`)
Type	Data type for validation
Required	Whether collection can continue without it
Prompt	Question to ask the user
Description	Context for the AI about this field
Validation	Regex pattern for format validation
Options	Choices for `select` type

Variable Types

Type	Description	Example
`string`	Short text	Name, city
`long_text`	Extended text	Issue description
`number`	Numeric value	Age, quantity
`boolean`	Yes/No	Confirmation
`select`	Choice from options	Size (S/M/L)
`date`	Date value	Appointment date
`email`	Email address	contact@example.com
`phone`	Phone number	+1-555-123-4567

Validation Patterns

Use regex patterns to validate format:

# Order number: 2 letters + 6 digits
order_number:
  type: string
  validation: "^[A-Z]{2}[0-9]{6}$"
  prompt: "What's your order number? It starts with two letters followed by 6 digits."

# US Phone number
phone:
  type: phone
  validation: "^\\+?1?[0-9]{10}$"
  prompt: "What's your phone number?"

# Email
email:
  type: email
  validation: "^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\\.[a-zA-Z]{2,}$"
  prompt: "What's your email address?"

Transitions

Data Extraction nodes support special transition types:

Type	Trigger
All Extracted	All required variables collected successfully
Timeout	User didn’t respond in time
Keyword	User said a specific trigger word

All Extracted Transition

Automatically fires when all required variables have been collected:

Transitions:
  - Type: all_extracted
    Target: Process Order

Example Configurations

Customer Contact Info

Extraction Method: Ask User
Max Attempts: 3

Variables:
  - name: customer_name
    type: string
    required: true
    prompt: "May I have your full name, please?"

  - name: email
    type: email
    required: true
    prompt: "What's the best email address to reach you?"

  - name: phone
    type: phone
    required: false
    prompt: "And a phone number in case we need to call you back?"

Transitions:
  - all_extracted → Confirmation
  - keyword: "stop", "cancel" → End Call

Order Lookup

Extraction Method: Ask User
Max Attempts: 3

Variables:
  - name: order_number
    type: string
    required: true
    validation: "^[A-Z]{2}[0-9]{6}$"
    prompt: |
      What's your order number?
      It starts with two letters followed by six digits,
      like AB123456.

Transitions:
  - all_extracted → Order Status
  - keyword: "don't have it", "don't know" → Alternative Lookup

Appointment Booking

Extraction Method: Ask User
Max Attempts: 3

Variables:
  - name: preferred_date
    type: date
    required: true
    prompt: "What date works best for your appointment?"

  - name: preferred_time
    type: select
    required: true
    options: ["Morning (9-12)", "Afternoon (12-5)", "Evening (5-8)"]
    prompt: "Do you prefer morning, afternoon, or evening?"

  - name: appointment_type
    type: select
    required: true
    options: ["Consultation", "Follow-up", "New Patient"]
    prompt: "Is this a consultation, follow-up, or new patient visit?"

Transitions:
  - all_extracted → Calendar Booking

Using Extracted Variables

Once collected, variables can be used in:

Subsequent prompts: Reference as {{variable_name}}
If/Else conditions: Branch based on values
Function calls: Pass to external systems
Transfer briefings: Include in human transfer context

Prompt: |
  Help {{customer_name}} with their order {{order_number}}.
  Their preferred contact is {{email}}.

Best Practices

Ask One Thing at a Time

Don’t overwhelm callers. Collect variables sequentially.

Explain Format Requirements

If validation is strict, tell callers the expected format upfront.

Make Optional Fields Optional

Don’t require information you don’t actually need.

Handle Failures Gracefully

Set reasonable max attempts and provide fallback paths.

If/Else Stage

Branch based on extracted data

Transitions

Configure extraction-based routing

Calendar Booking

Book appointments with extracted data

Getting Started

Agent Builder

Agent Configuration

Test Agent

Publish

Data Extraction Stage

Overview

Configuration

Extraction Method

Max Attempts

Variables

Variable Properties

Variable Types

Validation Patterns

Transitions

All Extracted Transition

Example Configurations

Using Extracted Variables

Best Practices

Ask One Thing at a Time

Explain Format Requirements

Make Optional Fields Optional

Handle Failures Gracefully

If/Else Stage

Transitions

Calendar Booking

​Overview

​Configuration

​Extraction Method

​Max Attempts

​Variables

​Variable Properties

​Variable Types

​Validation Patterns

​Transitions

​All Extracted Transition

​Example Configurations

​Using Extracted Variables

​Best Practices

Ask One Thing at a Time

Explain Format Requirements

Make Optional Fields Optional

Handle Failures Gracefully

​Related

If/Else Stage

Transitions

Calendar Booking

Overview

Configuration

Extraction Method

Max Attempts

Variables

Variable Properties

Variable Types

Validation Patterns

Transitions

All Extracted Transition

Example Configurations

Using Extracted Variables

Best Practices

Related