Developer Builds Modular RAG Architecture for Internal Knowledge Assistant Guidely

A developer built Guidely, an internal knowledge assistant, using a Retrieval-Augmented Generation (RAG) architecture designed from scratch to handle organizational documents. The system follows a structured pipeline covering document parsing, chunking, embedding generation, vector storage, semantic search, and response generation with citations. Rather than bundling all logic into a single function, each stage was deliberately separated so it could be tested and maintained independently. Supported file types include TXT, PDF, and DOCX, with the upload layer kept isolated from the embedding and search logic. The project prioritized architectural clarity, ensuring that every component answered one specific question about how data moves through the system.