AI-Powered ServiceNow Chat Triage with GPT-4 — Incident & Request Router
Last edited 58 days ago
Short description
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.
Full description
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, orEverything 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:
- uses an OpenAI chat model for contextual replies,
- can consult SerpAPI (web search) as a tool,
- saves relevant context to Simple Memory for future conversations.
-
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.
Key highlights (what to call out)
- Three-way LLM triage: ensures messages are routed automatically to the correct backend action (Incident vs Service Request vs AI handling).
- ServiceNow native connector: uses the ServiceNow node to create Incidents (safer than raw HTTP for incidents).
- Service Catalog via HTTP: flexible — supports organizations using RESTful catalog endpoints.
- Summarization before ticket creation: produces concise, high-quality
short_descriptionanddescriptionfields. - AI Agent + Memory + Web Search: handles non-ticket queries with web-augmented answers and stores context for follow-ups.
- Failover & logging: include a catch node (optional) that logs failures and notifies admins.
Required credentials & inputs (must configure)
- ServiceNow: Instance URL + API user (must have rights to create incidents).
- Service Catalog HTTP endpoint: URL + API key / auth header (for POST).
- OpenAI API key (or other LLM provider): for Text Classifier, Summarization Chain, and AI Agent.
- SerpAPI key (optional): for web search tools inside the AI Agent.
- Memory store: Simple Memory node (or external DB) for conversation history.
Nodes included (quick map)
- Trigger:
When chat message received - Processor:
Text Classifier(OpenAI/LLM) - Branch A:
ServiceNow (Create Incident) - Branch B:
HTTP Request(Service Catalog POST) - Branch C:
AI Agent(OpenAI + SerpAPI + Simple Memory) - Shared:
Summarization Chain(used before A or B where enabled) - Optional:
Error / Audit loggingnode,Slack/emailnotifications
Recommended n8n settings & tips
- Use structured outputs from classifier (
{ label: "Incident", confidence: 0.92 }) so you can implement confidence thresholds. - If confidence < 0.7, route to a human review queue instead of auto-creating a ticket.
- Sanitize user PII before storing in memory or sending to external APIs.
- Rate-limit OpenAI/SerpAPI calls to avoid unexpected bills.
- Test the Service Catalog POST body in Postman first — include sample
variablesJSON.
Short sample variables JSON (Service Catalog POST)
{
"sysparm_quantity": 1,
"variables": {
"description": "User reports VPN timeout on Windows machine; error code 1234"
}
}
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