Block 1 - AI Agent
- Type / Role
- @n8n/n8n-nodes-langchain.agent - agent
- Config choices
- Version 2
This workflow is provided as-is. Please review and test before using in production.
This n8n workflow automates support ticket handling with AI driven classification, response generation, and safety checks. Responses are based solely on your Mintlify documentation, ensuring accura...
@n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.lmchatopenrouter, n8n-nodes-base.switch, n8n-nodes-base.webhook, n8n-nodes-base.code, n8n-nodes-base.httprequest, n8n-nodes-base.noop
This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Alex Gurinovich.
Original n8n.io sourceThis n8n workflow automates support ticket handling with AI-driven classification, response generation, and safety checks. Responses are based solely on your Mintlify documentation, ensuring accuracy, consistency, and reduced manual effort in customer support.
✅ Trigger: New Ticket Received The workflow is triggered whenever a new support ticket is created.
🔍 Check for Assignee If the ticket is already assigned to a human agent, the bot does nothing and exits. If the ticket is unassigned, the bot continues processing.
🔢 Bot Response Count Check The workflow checks how many times the bot has already responded to this ticket. If the bot has replied more than 3 times, it stops and waits for a human to take over. This prevents endless loops and flags potentially complex cases for review.
🧠 AI-Based Ticket Categorization An AI model analyzes the ticket content and classifies it into one of the following categories:
🤖 Mintlify Integration For tickets categorized as "Other", the customer’s question is sent to the Mintlify API, which returns a documentation-based answer.
✍️ AI Response Formatter The raw response from Mintlify is passed to an AI model that: Summarizes and rewrites the answer in a clear, friendly tone Limits the response to 120 words Adds conversational elements like “Hi,” “Thanks,” and a proper closing
🛡️ AI Confidence Filter A second AI model reviews the formatted response to ensure it sounds confident and accurate. It looks for uncertainty phrases like:
📤 Send Response & Update Ticket If the response passes the confidence check: The reply is sent to the customer The ticket status is updated to “Pending”
This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.
Showing the first 24 of 32 workflow blocks. Download the JSON for the full node graph.
| Workflow | Automate customer support with Mintlify documentation & Zendesk AI agent |
|---|---|
| Complexity | advanced |
| Nodes | 32 |
| Categories | Ticket Management, AI Chatbot |
| Author | Alex Gurinovich |
| Published | 19 Jun 2025 |
Use the JSON export at /data/workflows/5046/5046.json as the source template for this automation.
Open n8n, import the downloaded JSON, and review each node before activating the workflow.
Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.
Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.
Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.
This n8n workflow automates support ticket handling with AI driven classification, response generation, and safety checks. Responses are based solely on your Mintlify documentation, ensuring accura...
Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.
Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Ticket Management, AI Chatbot use case.