Build an AI Chatbot to Automate Service Request Submissions

This Dify workflow template creates an intelligent Service Request Chatbot that automates the initial stages of customer support. The chatbot uses a form to capture user requests, then leverages an OpenAI-powered question classifier to understand the user's intent. Based on the classification, it either confirms the request submission or provides a helpful AI-generated response, ensuring every inquiry is handled efficiently and instantly.

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    Workflow Overview

    What is this?

    What is this?

    This is a ready-to-use Dify chatflow that builds an automated service request chatbot. It presents users with a simple form to submit their requests, then uses AI to intelligently classify the inquiry and route it down the correct path for an instant response.
    What problem does it solve?

    What problem does it solve?

    Do your support teams spend too much time manually categorizing incoming requests or answering repetitive questions? This workflow eliminates that initial triage step, freeing up your team to focus on complex issues while ensuring users receive immediate acknowledgment or answers.
    What will you get?

    What will you get?

    You get a fully automated system to capture and classify service requests 24/7. It provides instant feedback to users, improving their experience. This workflow reduces manual workload for support teams, allowing them to focus on high-value tasks. You also gain a scalable foundation for more complex customer service automations.

    Apps Included

    • OpenAI

    How to Use

    Prerequisites

    Setup Steps

    1

    Import the Workflow

    Download the YML file for this workflow and import it into your Dify workspace to create a new application.

    2

    Configure the LLM Nodes

    Navigate to the 'Question Classifier' and 'LLM' nodes within the workflow. In each node, select your configured OpenAI API key from the model provider settings to activate the AI capabilities.

    3

    Customize the Classifier

    Click on the 'Question Classifier' node. Review and edit the pre-defined classes ('Request a service ticket', 'Other topics') to perfectly match your specific business needs and service categories.

    4

    Deploy and Test

    Publish the application. Open the chat interface and test the workflow by submitting different types of requests to ensure the classification and responses work as expected.

    Pro Tips

    1
    To create a more robust system, connect the 'Process the request' branch to an external tool like a ticketing system (e.g., Zendesk, Jira) or a database (e.g., Airtable) using an API call to automatically create a new ticket.
    2
    Enhance the 'LLM' node's prompt by providing it with context from your knowledge base. This will enable it to answer 'Other topics' with more specific and helpful information related to your business.
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    Information

    • Published date8/15/2025
    • Last updated8/15/2025

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