Automated Document Processing and AI-Driven Insights

This n8n workflow automates the process of monitoring a local folder for new documents, extracting and summarizing their content, and leveraging AI for advanced analysis and interaction. It begins with a Local File Trigger that detects added files in a specified folder, triggering subsequent nodes to read, process, and interpret the documents. The workflow uses different nodes to identify file types, extract text, and generate summaries, storing these insights into a vector database for efficient retrieval. Integrations with LangChain’s language models facilitate text summarization, embedding creation, and AI-driven chat interactions, supporting retrieval-augmented generation (RAG) for contextual responses.

Practical use cases include automating document analysis for knowledge management, research, or customer support. For example, this workflow can process research papers, generate summaries for quick review, and enable intelligent querying for specific content—streamlining information workflows for data scientists, researchers, or support teams.