Retrieval-Augmented Generation in Clojure: A Practical Architecture
In this blog post, we present a Clojure-based Retrieval-Augmented Generation (RAG) system designed to provide accurate, grounded answers using private organizational knowledge. The architecture combines document processing, semantic search, and controlled prompt construction to ensure that large language models operate with domain-specific context rather than relying solely on their internal training data. We walk through the key parts of the pipeline: ingestion, storage, retrieval, and generation.
