Langchain.agent Langchain.lmChatGoogleGemini Langchain.memoryBufferWindow Langchain.chatTrigger Langchain.textClassifier ServiceNow +8 more

Automate ITSM ticket classification and resolution using Gemini, Qdrant and ServiceNow

This intelligent ITSM assistant leverages Google Gemini and Qdrant to automatically categorize user queries and manage support tickets. It seamlessly routes incidents into ServiceNow while utilizing semantic search to provide instant answers for general requests. By automating classification and knowledge retrieval, it significantly reduces the manual workload for IT support teams.

Run this with your team's AI

What This Recipe Does

Managing IT service requests often involves navigating complex legacy systems that slow down productivity and frustrate employees. This automation transforms your ServiceNow instance into an intelligent, conversational interface, allowing your team to interact with IT support using natural language. Instead of manually filling out cumbersome forms or searching through technical ticketing portals, users can simply ask questions or report issues through a streamlined chat-based application. The AI processing layer identifies the intent behind every request, automatically categorizing incidents and retrieving real-time status updates directly from your IT infrastructure. This significantly reduces the administrative burden on IT departments by filtering out routine inquiries and ensuring that high-priority issues are logged accurately. By centralizing request management and automating the initial intake process, organizations can ensure faster resolution times and more consistent service delivery. This tool acts as a vital bridge between your technical backend and your non-technical workforce, ensuring that IT operations remain fluid, transparent, and responsive to the needs of the business. It eliminates the friction inherent in traditional ITSM processes, turning a complex database into a proactive service assistant.

What your team gets

Something anyone can use

Forms and dashboards, so it is not a script only one person understands

It keeps running

Runs on your schedule in the cloud, so it does not stop when a laptop closes

Your other tools can call it

Endpoints, so the rest of your stack can trigger the same work

Accounts connected once

Langchain.agent, Langchain.lmChatGoogleGemini, Langchain.memoryBufferWindow, Langchain.chatTrigger, Langchain.textClassifier connected for the team, not per person

How It Works

  1. 1

    Open the recipe and connect your accounts

    Connect Langchain.agent and Langchain.lmChatGoogleGemini once, in your team cloud, and nobody has to do it again on their own machine

  2. 2

    Tell your own agent what is different about your process

    Claude, ChatGPT, Cursor, whichever your team already uses. It adapts the recipe to how you actually work

  3. 3

    Run it, then leave it running

    It lives in your team cloud, so it keeps going after you close the laptop and every teammate's AI can use it

Who Uses This

Frequently Asked Questions

What is required to connect this to my ServiceNow instance?

You only need your ServiceNow instance URL and standard API credentials. The setup process securely links the workflow to your existing environment without requiring complex backend modifications.

Can I customize the types of IT requests the AI can handle?

Yes. You can define specific parameters and response logic within the workflow to ensure the AI follows your organization's unique IT policies, service catalogs, and escalation procedures.

Does this work with custom fields and tables in ServiceNow?

The automation is designed to map to both standard and custom ServiceNow fields, ensuring it can capture and display all the specific data points required for your ticketing workflows.

What kind of interface do my end-users see?

Runwork converts this workflow into a clean, standalone web application. Your employees interact with a simplified chat window that hides the complexity of the underlying ServiceNow architecture.

Coming from n8n?

This recipe uses nodes like Langchain.agent, Langchain.lmChatGoogleGemini, Langchain.memoryBufferWindow, Langchain.chatTrigger and 10 more. On Runwork, you don't need to learn n8n's workflow syntax. Describe what you want to your own AI agent in plain English.

Langchain.agent Langchain.lmChatGoogleGemini Langchain.memoryBufferWindow Langchain.chatTrigger Langchain.textClassifier ServiceNow Langchain.vectorStoreQdrant Set Langchain.embeddingsGoogleGemini ManualTrigger Langchain.documentDefaultDataLoader Langchain.chainSummarization HttpRequest StickyNote

Based on n8n community workflow. View original

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Run this with the AI your team already uses

Your agent adapts it, your team cloud keeps it running, and everyone's AI can find it.

Open this recipe in Runwork