Advanced Multimodal RAG Al Assistant (n8n)

Designed and developed an advanced Retrieval-Augmented Generation (RAG) Al assistant using n8n. The system ingests knowledge from documents, PDFs, spreadsheets, and other data sources into a vector database, enabling the Al to provide accurate, context-aware responses. It supports multimodal interactions, including text, voice, and image inputs, automatically processes and retrieves relevant information, and generates reliable answers based on the knowledge base rather than relying solely on the language model. The solution is scalable, modular, and optimized for enterprise Al automation.