Retrieval-Augmented Generation (RAG)

RAG is the architecture that makes LLMs useful in enterprise settings — grounding responses in your actual documentation rather than training data that may be outdated or incomplete.

RAG System Components

• Document ingestion pipeline with chunking and embedding
• Vector database selection, configuration, and scaling
• Retrieval optimization for precision and recall
• LLM integration and prompt engineering
• Evaluation framework and quality monitoring
• Continuous ingestion for keeping the knowledge base current