n8n AI Agent for Lead Qualification and Customer Support

This n8n workflow leverages an AI Agent to automate lead qualification and customer support interactions. It acts as a conversational assistant, processing incoming chat messages, applying business logic, and responding appropriately.

What it does

This workflow sets up a basic AI agent that can process chat messages.

1. Listens for Chat Messages: The workflow is triggered by incoming chat messages via the Chat Trigger node.
2. Initializes AI Agent: An AI Agent node is configured to process the incoming messages.
   • It uses an OpenAI Chat Model (specifically GPT-4o mini, as suggested by the directory name) for natural language understanding and generation.
   • Simple Memory is included to maintain context throughout the conversation, allowing the agent to remember previous turns.
   • A Structured Output Parser is used, indicating that the agent might be designed to extract structured information or respond in a specific format.
3. Processes AI Agent Output: The output from the AI Agent is then passed to an Edit Fields (Set) node, which likely transforms or extracts specific data from the AI's response.
4. Conditional Logic: An If node introduces conditional logic, allowing the workflow to branch based on the processed AI output. This is crucial for implementing different responses or actions depending on the lead qualification status or customer support query.
5. No Operation (Placeholder): A No Operation, do nothing node is present, which typically serves as a placeholder for future actions or simply ends a branch of the workflow without performing any explicit operation.
6. Code Execution (Placeholder): A Code node is included, allowing for custom JavaScript logic to be executed. This could be used for advanced data manipulation, API calls, or integrating with other services based on the AI's output.

Prerequisites/Requirements

• n8n Instance: A running n8n instance (cloud or self-hosted).
• OpenAI API Key: An API key for OpenAI to use their chat models (e.g., GPT-4o mini). This will need to be configured as an n8n credential.

Setup/Usage

1. Import the Workflow:
   • Download the provided JSON file.
   • In your n8n instance, click on "Workflows" in the left sidebar.
   • Click "New" -> "Import from JSON" and upload the downloaded JSON file.
2. Configure Credentials:
   • Locate the OpenAI Chat Model node.
   • Click on the "Credential" field and select an existing OpenAI credential or create a new one. Provide your OpenAI API Key.
3. Configure the Chat Trigger:
   • The Chat Trigger node will need to be configured to connect to your desired chat platform (e.g., Slack, Telegram, custom webhook). Follow the n8n documentation for the specific chat integration you intend to use.
4. Customize AI Agent:
   • Review the AI Agent node's configuration. You may want to adjust the system message, tools, or other parameters to better suit your specific lead qualification or customer support scenarios.
   • The Structured Output Parser might require a specific schema definition depending on the desired output format.
5. Develop Conditional Logic:
   • Customize the If node's conditions to define the branching logic for your workflow. For example, you might check for keywords, sentiment, or extracted entities from the AI's response to determine the next steps.
6. Implement Actions for Branches:
   • Replace or enhance the No Operation, do nothing and Code nodes with actual actions. For instance:
     • Sending qualified leads to a CRM (e.g., HubSpot, Salesforce).
     • Notifying a support team for complex customer issues (e.g., Slack, Email).
     • Updating a database or spreadsheet.
     • Sending a personalized response back to the user via the chat platform.
7. Activate the Workflow: Once configured, activate the workflow to start processing incoming chat messages.