Beyond the demo: building RAG for production
From data ingestion to evaluation, learn how to build a production-ready retrieval-augmented generation system.
Ingestion is where quality starts
Clean documents, split them along natural boundaries and attach metadata such as source and date. Poor chunking cannot be rescued by a better model later.
Retrieve, then verify
Combine semantic and keyword search, re-rank the top results and cap the context you pass on. Always return sources so users can check the answer.
Evaluate and observe
Measure retrieval quality and answer faithfulness separately on a fixed question set. Log queries, retrieved passages and feedback so you can see where the system fails in production.
