Retrieval-Augmented Generation: embed documents, store in a vector database, and retrieve context for grounded AI responses.
🔒 Demo mode - RAG with vector search and LLM generation
Build question-answering systems that search through company documents, legal papers, or technical manuals for accurate responses.
Create support systems that retrieve relevant information from documentation, FAQs, and help articles to answer user queries.