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• Pre-Call Variables: Define key details before the call, making conversations more personalized and efficient. Your agent starts the call with relevant details like customer name, account status, issue type, etc.
  • Add as many variables as required and specify the details:
    • Unique Identifier: Select one variable as the primary key for each call.
    • Variable: A named placeholder storing a value from a database (e.g., customer_name, policy_status).
    • Description: A short note for the LLM to understand the variable’s purpose.
  • Using Pre-Call Variables:
    • In the Greeting Message, Ending Message, and System Prompt, use double curly braces to insert variables dynamically.
    • Example: “Hi , I’m speaking from Gnani Technical Support.”
  • Example: If the agent is calling a customer regarding their insurance policy, pre-call variables like policy_status and renewal_date ensure it starts with relevant information instead of asking redundant questions.

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Lesson 5: Categorizing Call Outcomes

• Toggle the Call Dispositions feature ON and enter a default prompt that helps the LLM understand how to categorize calls.
• Click Add Disposition to create a new category. Each disposition includes:
• Prompt: Define when a call should be classified under this status.
• Once configured, the AI will automatically categorize calls based on the provided conditions and you can see the predefined disposition in Call Analytics and Agent Analytics.

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Lesson 6: Testing your Agent

• Click on Test → Chat Window → Start Testing </> to use the built-in chat interface to test responses.

• Click on Test → Web-based (Voice) → Start Testing </> to use the web-based voice test to simulate real-world scenarios.
• To share the web-based voice testing tool, go to Test → Web-based (Voice) → Generate Sharable Link. The link works for 5 minutes, perfect for giving teammates or clients quick access without login requirements.