This visualization dissects the layered architecture of a Retrieval-Augmented Generation (RAG) system, presented as a vertical flowchart. It shows the sequential pipeline from data ingestion through chunking, embedding generation, vector search, reranking, and final LLM generation. The diagram highlights key technical components, including FAISS and Pinecone for vector databases, along with RAGAS for evaluation metrics. The layout visually separates each processing stage with distinct blocks, illustrating the flow of data through semantic search and generative AI layers. It provides a clear technical map of how external knowledge bases integrate with language models.