This n8n workflow enables an intelligent chatbot that interacts with internal business data by leveraging advanced AI models, Vector Store retrieval (RAG), and direct SQL queries via Peliqan. It is designed to provide quick, accurate answers to business inquiries by connecting multiple data sources like Notion, Chargebee, and internal databases. The workflow is triggered by chat messages and manages data through various nodes including language models, embeddings, vector stores, and SQL execution tools. It allows seamless interaction with business data, combining natural language understanding with structured SQL queries, making it ideal for building intelligent business chatbots or knowledge bases.
AI-Driven Business Data Query and Chatbot Workflow
Node Count | 11 – 20 Nodes |
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Nodes Used | @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.chatTrigger, @n8n/n8n-nodes-langchain.documentDefaultDataLoader, @n8n/n8n-nodes-langchain.embeddingsOpenAi, @n8n/n8n-nodes-langchain.lmChatOpenAi, @n8n/n8n-nodes-langchain.memoryBufferWindow, @n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter, @n8n/n8n-nodes-langchain.vectorStoreSupabase, manualTrigger, n8n-nodes-peliqan.peliqan, n8n-nodes-peliqan.peliqanTool, stickyNote |
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