XBot
  • Overview
    • Introduction
    • How xBot Works
    • Target Audience
    • Key Benefits of xBot
    • Core Concepts of xBot
  • Quick Start
    • Quick Setup
    • Getting Started
      • Zalo Channel
      • Azure Bot Framework
      • FaceBook Channel
      • Team Channel
      • Webchat Channel
      • Email Channel
    • Basic Configuration
    • First AI Flow Setup
    • Initial Testing and Go Live
  • Features
    • Using xBot to Handle End-User Queries
    • Communication Channels
      • Zalo OA
      • Facebook
      • Teams
      • WebChat
      • Email
    • Understanding the Message Handling Flow
    • Understanding AI Bots in xBot
    • Configuring Dispatch Rules in xBot
    • User Functions and Permissions
      • Custom Roles and Permissions
      • Auditing and Monitoring User Activities
    • Cross-Platform Message Type Compatibility
    • AI Flow
      • Core Concepts
      • AI Services
        • Knowledge Base Agent
        • AI Agent
        • AI Proxy Agent
      • Knowledge Base
      • Functions
      • Evaluation Metrics
        • Essential Information
        • Basic Metrics
        • Extra Metrics
  • Integration Guide
    • Integrates with multiple channels
      • API reference
        • Webhook
          • ZaloPushToXBot
          • AzbotPushToXBot
        • Webchat
          • InitForClient
  • References
    • Industry-Specific Use Cases
      • Media and Entertainment
      • Wholesale
      • Transportation and Logistics
      • Manufacturing
      • Energy and Utilities
      • Real Estate
      • Agriculture
      • Travel and Hospitality
      • Healthcare and Wellness
      • Retail and E-Commerce
      • Public Administration
      • Legal
      • Training
      • Education
      • xBot Use Case: Insurance
      • Securities -Use Case
      • Banking - Use Case
      • xBot Use Case: Finance
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On this page
  • Introduce
  • Types of AI bots
  • 1. AI Pre
  • 2. AI agent
  • 3. AI Post
  1. Features

AI bots

Introduce

In the AI bot framework, there are three distinct types of AI bots designed to handle different aspects of interacting with messages. These AI bots are integrated into the system to manage, analyze, and respond to customer messages effectively. Here is an explanation of each type and their roles:

Types of AI bots

1. AI Pre

This AI bot is responsible for initially screening incoming messages from customers. It checks for inappropriate content or negative sentiments. If the AI PRE agent detects negative content, it returns true, marking the message as NEGATIVE. In such cases, the message is flagged and forwarded to a human agent with a warning, and the AI PRE does not respond to these messages. AI pre will immediately respond to the user's answers in the configuration messages. Here's a basic example class in Java to represent this functionality:

public class AiPreAgent {
    public boolean checkMessageContent(String message) {
        // Implement logic to check for negative content
        boolean isNegative = false;
        // Example logic
        if (message.contains("negative keyword")) {
            isNegative = true;
        }
        return isNegative;
    }
}

User Interface (UI):

2. AI agent

This AI bot handles responses to customer queries based on the knowledge it has been trained on. It automatically provides answers to customer questions using its AI capabilities. Below is a simple example of how this might be implemented in a Java class:

public class AiAgent {
    public String respondToCustomer(String query) {
        // Logic to generate response based on AI knowledge
        String response = "This is an automated response based on your query.";
        return response;
    }
}

User Interface (UI):

3. AI Post

This AI bot is configured to post-process the responses given by the AI AGENT. It logs or monitors the answers to ensure quality or for further analysis. This agent does not interact directly with customers but acts as a backend process to gather data on AI performance. An example Java class might look like this:

public class AiPostAgent {
    public void logResponse(String response) {
        // Logic to log or monitor responses
        System.out.println("Logging response: " + response);
    }
}

User Interface (UI):

Integration in Conversational Systems

These AI bots are assigned to specific groups within the conversational system. They perform checks, respond, and post-process messages as they arrive in a conversation. This structured approach allows for efficient handling of messages, ensuring that each is processed appropriately according to its content and the system's operational requirements. By leveraging these AI bots, the system can manage conversations dynamically, ensuring appropriate interactions and maintaining the quality of service.

Last updated 10 months ago

Group configuration