What It Does:
  • Accepts conversational, natural responses
  • Uses AI to understand caller intent
  • Extracts specific information from responses
  • Handles multiple attempts and clarifications
Key Features:
  • Natural Language: Accept conversational responses
  • Intent Recognition: Understand caller’s intent
  • Entity Extraction: Pull specific information from responses
  • Context Awareness: Use conversation history
  • Multiple Attempts: Allow rephrasing and clarification
  • Confidence Scoring: Measure response quality
Configuration Options:
  • Question Text: What to ask the caller
  • Expected Entities: What information to extract
  • Confidence Threshold: Minimum confidence for acceptance
  • Retry Logic: How to handle unclear responses
  • Context Usage: How much conversation history to consider
Testing Tips:
  • Test with various response styles and formats
  • Verify intent recognition accuracy
  • Check entity extraction precision
  • Validate confidence scoring and retry logic
Common Use Cases:
  • Gathering customer feedback
  • Collecting appointment preferences
  • Understanding service requests
  • Getting product preferences
  • Collecting general information