Automate WHMCS support ticket creation with Gemini AI chatbot
This n8n template implements an AI-Powered Chatbot for Automated WHMCS Support Ticket Creation
Who's it for
This template is designed for web hosting companies, domain registrars, and IT service providers who want to automate their customer support ticket creation process. It's perfect for businesses looking to streamline support operations by automatically converting customer chat conversations into structured WHMCS support tickets while maintaining professional, empathetic customer interactions.
How it works / What it does
This workflow creates an AI-powered chatbot that automatically converts customer chat messages into structured support tickets within the WHMCS system. The AI agent automatically:
- Receives customer queries through a webhook endpoint
- Processes natural language requests using Google Gemini AI
- Extracts key information from customer conversations:
- Customer name and email
- Issue description and subject
- Appropriate support department
- Priority level (Low, Medium, High)
- Fetches valid support departments from WHMCS using the GetSupportDepartments API
- Creates structured support tickets via WHMCS OpenTicket API
- Maintains conversation context with session-based memory
- Provides professional responses while gathering necessary information
The system ensures 100% accuracy by always mapping to valid WHMCS departments and never inventing ticket fields, maintaining data integrity and proper ticket routing.
How to set up
1. Configure Google Gemini API
- Set up your Google Gemini API credentials in the Google Gemini Chat Model node
- Ensure you have sufficient API quota for your expected usage
2. Configure WHMCS API
- Update the WHMCS API credentials in both HTTP Request Tool nodes
- Replace
https://WHMCS_URL.com/includes/api.phpwith your actual WHMCS API endpoint - Ensure your WHMCS API has the necessary permissions for:
GetSupportDepartmentsactionOpenTicketaction
3. Customize AI Agent Behavior
- Modify the system message in the AI Agent node to match your company's tone and policies
- Adjust the agent's response style and ticket creation workflow
- Customize department mapping and priority assignment logic
4. Set up the Webhook
- The workflow creates a unique webhook endpoint for receiving customer queries
- Use this endpoint URL in your customer-facing chat interface
- Ensure proper security measures for webhook access
5. Test Department Integration
- Verify that the
GetSupportDepartmentsAPI call returns your actual support departments - Test ticket creation with various customer scenarios
- Ensure proper error handling for API failures
Requirements
- Google Gemini API account with appropriate credentials
- n8n instance (self-hosted or cloud)
- WHMCS installation with API access enabled
- Support department structure already configured in WHMCS
- Customer chat interface or messaging system
How to customize the workflow
Modify AI Agent Behavior
- Edit the system message in the AI Agent node to change the bot's personality and response style
- Adjust ticket creation logic and required field validation
- Customize priority assignment algorithms based on keywords or urgency indicators
Enhance Ticket Creation
- Add custom fields to the ticket creation process
- Implement ticket categorization based on conversation content
- Add automatic assignment to specific support staff members
Improve Customer Experience
- Add ticket confirmation and tracking information
- Implement follow-up message scheduling
- Add customer satisfaction surveys after ticket resolution
Security Enhancements
- Implement API key rotation and monitoring
- Add request validation and sanitization
- Set up usage analytics and abuse prevention
Key Features
- Automatic ticket creation from natural language conversations
- Intelligent department mapping using WHMCS API
- Professional customer interaction with empathetic responses
- Session-based memory for contextual conversations
- Structured ticket data with proper validation
- Priority assignment based on conversation analysis
- Scalable webhook architecture for high-volume usage
- Direct WHMCS integration for seamless ticket management
Use Cases
- 24/7 automated support ticket creation for web hosting companies
- Customer service automation with human-like interaction
- Support team efficiency by reducing manual ticket entry
- Consistent ticket formatting across all customer interactions
- Improved response times through immediate ticket creation
- Customer self-service with professional guidance
Chat Session Management
The workflow automatically manages chat sessions with the following features:
- Unique Session IDs for each customer conversation
- Automatic information extraction from customer messages
- Conversation history tracking with chronological message storage
- Session persistence across multiple interactions
- Contextual responses based on conversation history
Example Customer Interactions
The AI agent can handle various customer scenarios:
- Technical Issues: "My website is down" → Creates ticket in Technical Support department
- Billing Questions: "I need help with my invoice" → Creates ticket in Billing department
- Domain Services: "I want to transfer my domain" → Creates ticket in Domain Services department
- General Support: "I have a question about my hosting plan" → Creates ticket in General Support department
Ticket Creation Process
The workflow follows a structured approach:
- Information Gathering: The AI agent identifies missing required information (email, name, etc.)
- Department Selection: Fetches available departments from WHMCS and maps customer needs appropriately
- Priority Assessment: Determines ticket priority based on urgency indicators in the conversation
- Ticket Creation: Generates a well-structured ticket with clear subject and detailed message
- Confirmation: Provides customer with ticket creation confirmation and next steps
This template transforms your web hosting business by providing instant, automated support ticket creation while maintaining the personal touch that customers expect from professional service providers. The AI agent becomes an extension of your support team, handling routine inquiries and ensuring no customer request goes unaddressed.
AI Chatbot with Google Gemini and LangChain
This n8n workflow demonstrates a basic AI chatbot powered by Google Gemini and LangChain, featuring conversational memory. It provides a foundational setup for building interactive AI agents that can remember previous interactions.
What it does
This workflow sets up a simple AI chatbot that:
- Listens for Chat Messages: It acts as a trigger, initiating the workflow whenever a new chat message is received.
- Maintains Conversational Memory: Uses a "Simple Memory" node to store and recall past messages within the conversation, allowing the AI to maintain context.
- Processes Messages with Google Gemini: Utilizes the Google Gemini Chat Model as the underlying large language model to generate responses based on the input and the conversational history.
- Orchestrates with an AI Agent: An "AI Agent" node (likely a LangChain agent) ties together the memory and the language model, enabling more complex conversational capabilities and potentially tool usage (though no specific tools are defined in this basic setup).
Prerequisites/Requirements
- n8n Instance: A running instance of n8n.
- Google Gemini API Key: An API key for the Google Gemini model, configured as a credential in n8n.
Setup/Usage
- Import the workflow: Download the provided JSON and import it into your n8n instance.
- Configure Credentials:
- You will need to set up a credential for the "Google Gemini Chat Model" node. This typically involves providing your Google Gemini API key.
- Activate the workflow: Once imported and configured, activate the workflow.
- Interact with the Chat Trigger: The "When chat message received" node acts as the entry point. You would typically interact with this trigger through an n8n chat integration (e.g., a custom chat UI, Telegram, Slack, etc., depending on how the Chat Trigger is exposed in your n8n setup). Send a message to initiate a conversation with the AI.
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