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AI-Powered ServiceNow Chat Triage with GPT-4 — Incident & Request Router

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Created by: Tushar Mishra || yajna

Tushar Mishra

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Last update a day ago

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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:

  1. Trigger: When chat message received — incoming messages from your chat channel.

  2. Text Classifier: small LLM prompt/classifier that returns one of three labels: Incident, Request, or Everything Else.

  3. Create Incident (ServiceNow connector): when labeled Incident, the workflow creates a Servicenow Incident record (short fields: short_description, description, priority, caller).

  4. Submit General Request (HTTP Request): when labeled Request, the workflow calls your Service Catalog API (POST) to place a catalog item / submit a request.

  5. 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.
  6. 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_description and description fields.
  • 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 logging node, Slack/email notifications

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 variables JSON.

Short sample variables JSON (Service Catalog POST)

{
  "sysparm_quantity": 1,
  "variables": {
    
    "description": "User reports VPN timeout on Windows machine; error code 1234"
  }
}