The Branch Node in the SigmaMind AI platform is a fundamental component for constructing advanced and dynamic conversational AI agents. It enables the AI to make decisions and follow specific conversational paths based on various conditions, allowing for complex business logic implementation.

​
1. Purpose of the Branch Node

The primary purpose of the Branch Node is to introduce conditional logic into the conversational flow of an AI agent. This is crucial for building sophisticated agents that can respond intelligently to diverse user inputs and external data. It allows the AI to:

  • Handle multiple conditions, both static and dynamic.
  • Execute specific instructions based on the evaluation of these conditions.
  • Implement complex business rules within the conversational experience.

​
2. Key Use Cases

The versatility of the Branch Node makes it suitable for a wide range of applications across various industries:

  • Customer Support: Tailoring responses and escalating issues based on the nature of customer queries, customer history, or service level agreements.
  • Sales & Lead Qualification: Guiding users through sales funnels, providing product recommendations, or qualifying leads based on user responses and profile data.
  • Channel-Specific Logic: Adapting the AI’s behavior and responses depending on the communication channel (e.g., email, live chat, voice, social media). For example, providing shorter, more direct answers on mobile chat versus more detailed explanations via email.
  • Time-Based Logic: Adjusting conversational flow based on the time of day, day of the week, or specific dates (e.g., business hours vs. after-hours, weekdays vs. weekends, holiday promotions).
  • Order Status Management: Providing specific updates or actions based on the status of an order (e.g., fulfilled, pending, shipped, cancelled).
  • Appointment Management: Handling scenarios such as checking appointment availability, scheduling new appointments, rescheduling existing ones, or cancellations.
  • User Personalization: Delivering personalized content or experiences based on user preferences, past interactions, or demographic data.

​
3. Types of Conditions

The Branch Node supports two primary mechanisms for defining conditions:

​
3.1. Static Conditions

Static conditions are pre-defined, readily available options within the SigmaMind AI platform, ideal for handling simple “if-else” logic.

  • Ease of Use: Developers can simply select these conditions from a dropdown menu within the Branch Node configuration interface.
  • Multiple Conditions: On the “if” side of the branch, it’s possible to define multiple static conditions. These conditions can be evaluated in two ways:
    • All True (AND logic): All defined conditions must be met for the branch to be taken.
    • Any True (OR logic): At least one of the defined conditions must be met for the branch to be taken.
  • Performance: Static conditions are optimized for rapid evaluation at runtime, ensuring minimal latency in the AI agent’s responses.
  • Examples:
    • Checking if the conversation originated from a specific channel (e.g., “Is channel ‘Email’?”, “Is channel ‘Chat’?”).
    • Verifying if it’s currently a weekend.
    • Determining if it’s within business hours.

​
3.2. Expressions (JavaScript-based)

For scenarios requiring more intricate, custom, or dynamic logic that cannot be covered by static conditions, developers can leverage JavaScript-based expressions. These are designed for more complex conditions.

  • Flexibility: This provides a high degree of control and allows developers to implement virtually any custom logic.
  • Syntax: Expressions are written using standard JavaScript syntax.
  • Data Access: Expressions can access and evaluate various data points, including:
    • Session variables.
    • User input.
    • Data retrieved from external APIs.
    • Contextual information about the conversation.
  • Example: To check if a shopify_order_id exists and is valid (e.g., has a certain length), you might write an expression like: 
    session.shopify_order_id && typeof session.shopify_order_id === 'string' && session.shopify_order_id.length > 5
    This expression evaluates to true if shopify_order_id exists in the session, is a string, and its length is greater than 5 characters.

​
4. Benefits of Using the Branch Node

Implementing the Branch Node in your AI agent development offers several significant advantages:

  • Enhanced Flexibility: Allows for the definition of highly intricate and adaptive business logic, making AI agents more intelligent and capable.
  • Improved Efficiency: Static conditions are evaluated quickly, contributing to a responsive and seamless user experience.
  • Reduced Coding Effort (for static conditions): For common conditional scenarios, the no-code selection of static conditions simplifies and accelerates development.
  • Scalability: Enables the creation of complex conversational flows that can scale with the growing needs of your application.
  • Better User Experience: By guiding users through relevant paths and providing context-aware responses, the Branch Node helps create more intuitive and satisfying interactions.