This n8n workflow automates the process of analyzing, storing, and querying document data using AI and vector similarity search integrated with Google Drive, Pinecone, Azure OpenAI, and Slack. It begins with triggering on new files in Google Drive, then extracts, splits, and embeds the content using Azure OpenAI’s language models and embeddings. The data is stored and managed within Pinecone for efficient semantic search. The workflow also includes AI-powered reranking and question-answering agents to generate and refine responses based on specific queries, with notifications sent via Slack. This automation is useful in scenarios such as intelligent document management, knowledge bases, or research summarization where fast, AI-enhanced search and analysis are required.
AI-Powered Document Processing and Semantic Search Workflow
| Node Count | >20 Nodes |
|---|---|
| Nodes Used | @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.documentDefaultDataLoader, @n8n/n8n-nodes-langchain.embeddingsAzureOpenAi, @n8n/n8n-nodes-langchain.lmChatAzureOpenAi, @n8n/n8n-nodes-langchain.outputParserAutofixing, @n8n/n8n-nodes-langchain.outputParserStructured, @n8n/n8n-nodes-langchain.rerankerCohere, @n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter, @n8n/n8n-nodes-langchain.vectorStorePinecone, extractFromFile, googleDrive, googleDriveTrigger, googleSheets, googleSheetsTool, if, set, slack, stickyNote |
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