Build a ServiceNow knowledge chatbot with OpenAI and Qdrant RAG
Ready for 3.0Ready for 3.0. This template uses no nodes that n8n 3.0 removes. No removed nodes, versions or helpers found. Static check, last run 2026-10-19.
What this workflow does
This AI workflow has 12 nodes and runs when a chat message arrives (plus 1 other trigger). Along the way it connects Qdrant Vector Store, Embeddings OpenAI, OpenAI Chat Model and ServiceNow.
How it runs
Trigger: When a chat message arrives (plus 1 other trigger).
- AI Agent: runs an AI agent, with model: OpenAI Chat Model; 1 tool (Qdrant Vector Store); memory: Simple Memory
- Get many table records (ServiceNow): get many (table record)
- Qdrant Vector Store: stores documents in the Qdrant vector store, with embeddings: Embeddings OpenAI; document loader: Default Data Loader
Services it uses
Before you upgrade to n8n 3.0
Nothing in this workflow is removed in n8n 3.0, so it should import and run after the upgrade.
Nodes used (10)
- Qdrant Vector Store
@n8n/n8n-nodes-langchain.vectorStoreQdrant - Default Data Loader
@n8n/n8n-nodes-langchain.documentDefaultDataLoader - Recursive Character Text Splitter
@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter - Chat Trigger
@n8n/n8n-nodes-langchain.chatTrigger - AI Agent
@n8n/n8n-nodes-langchain.agent - Simple Memory
@n8n/n8n-nodes-langchain.memoryBufferWindow - Embeddings OpenAI
@n8n/n8n-nodes-langchain.embeddingsOpenAi - OpenAI Chat Model
@n8n/n8n-nodes-langchain.lmChatOpenAi - ServiceNow
n8n-nodes-base.serviceNow - Manual Trigger
n8n-nodes-base.manualTrigger
From the author
1. Data Ingestion Workflow (Left Panel – Pink Section) This part collects data from the ServiceNow Knowledge Article table, processes it into embeddings, and stores it in Qdrant. Steps: 1. Trigger: When clicking ‘Execute workflow’ The workflow starts manually…