RAG Is a Retrieval Problem First

RAG is an information retrieval problem first, an LLM problem second. The quality of retrieval — hybrid search, reranking, chunking, metadata preservation — determines whether generated answers are grounded and useful.

Enterprise knowledge systems need multi-stage retrieval, query intelligence, citation coverage, abstention when evidence is weak, and continuous evaluation. A thin wrapper around embeddings will not survive production scrutiny.

RAGForge was built with this philosophy: serious retrieval engineering, grounded generation, ingestion infrastructure, and operational rigor as first-class concerns.