Automatically triage incoming chat messages into Incidents, Service Requests, or Other using an LLM-powered classifier; create Incidents in ServiceNow, submit Service Catalog requests (HTTP), and route everything else to an AI Agent with web search + memory. Includes an optional summarization step for ticket context.
This n8n template wires a chat trigger to an LLM-based Text Classifier and then routes messages to the appropriate downstream action:
Trigger: When chat message received
— incoming messages from your chat channel.
Text Classifier: small LLM prompt/classifier that returns one of three labels: Incident
, Request
, or Everything Else
.
Create Incident (ServiceNow connector): when labeled Incident, the workflow creates a Servicenow Incident record (short fields: short_description, description, priority, caller).
Submit General Request (HTTP Request): when labeled Request, the workflow calls your Service Catalog API (POST) to place a catalog item / submit a request.
AI Agent: when labeled Everything Else, route to an AI Agent node that:
Summarization Chain: optional chain to summarize long chat threads into concise ticket descriptions before creating incidents/requests.
This template is ideal for support desks that want automated triage with human-quality context and searchable memory.
short_description
and description
fields.When chat message received
Text Classifier
(OpenAI/LLM)ServiceNow (Create Incident)
HTTP Request
(Service Catalog POST)AI Agent
(OpenAI + SerpAPI + Simple Memory)Summarization Chain
(used before A or B where enabled)Error / Audit logging
node, Slack/email
notifications{ label: "Incident", confidence: 0.92 }
) so you can implement confidence thresholds.variables
JSON.{
"sysparm_quantity": 1,
"variables": {
"description": "User reports VPN timeout on Windows machine; error code 1234"
}
}