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Famulor Tool

The Famulor tool is the core component that connects your AI calling system with automation flows. It enables real-time data exchange between your AI assistants and business systems, allowing for personalized conversations and automated follow-ups.
You can find the Famulor tool prominently displayed at the top of the searching sidebar when looking for either triggers or actions.

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Triggers

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Call Ended

The Call Ended trigger activates immediately after an AI call completes, providing comprehensive data about the interaction:
  • Complete conversation transcript with timestamps
  • AI assistant responses and decisions
  • Call duration and technical metadata
  • Customer information and phone number
  • Call outcome and sentiment analysis
  • Variables set during the conversation

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Configuration

  1. Select “Call Ended” as your trigger
  2. Choose specific AI assistant to monitor
  3. Configure variable mapping

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Inbound Call Variable Injection

This powerful trigger activates before your AI assistant picks up an inbound call, allowing you to:
  • Fetch and inject real-time customer data
  • Customize AI behavior based on context
  • Set conversation parameters
  • Define AI personality traits
  • Provide business logic variables

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Configuration

  1. Select “Inbound Call” as your trigger
  2. Define required variables for AI context

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Actions

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Add Lead to Campaign

Famulor Action This action helps manage your AI calling campaigns by:
  • Creating new leads from extenal tools like Sheets, Hubspot, Facebook leads
  • Assigning leads to specific AI campaigns
  • Adding context for future calls

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Configuration

  1. Select target AI campaign
  2. Map contact details from trigger data
  3. Add custom attributes for AI context

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Return Variables

This action is crucial for inbound calls, returning context that gets injected into the AI’s prompt:
  • Customer profile and preferences
  • Conversation history summary
  • Business rules and constraints
  • Custom AI behavior flags
  • Dynamic response templates

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Configuration

  1. Structure response JSON
  2. Map customer data to variables
  3. Set AI conversation parameters
  4. Configure timeout handling

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Example Usage

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Post-Call Lead Management

Trigger: AI Call Ended
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Extract conversation insights
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Update Hubspot record
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Add to follow-up campaign if qualified

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Intelligent Inbound Routing

Trigger: Inbound Call to AI
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Fetch customer profile from CRM
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Get interaction history
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Return enriched context for AI prompt

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Best Practices

  1. Variable Injection Performance
    • Keep processing under 2 seconds
    • Set sensible defaults
  2. Data Structure
    • Follow AI prompt requirements
    • Validate all variables
    • Structure nested objects clearly
    • Document custom fields
  3. Error Handling
    • Provide fallback values
    • Log injection failures
    • Monitor response times
    • Handle missing data gracefully