Most RAG projects fail not because of the model, but because nobody defined what a "correct answer" means before deployment.
Our framework evaluates in three layers: retrieval precision (did it fetch the right document?), generation fidelity (did it hallucinate?), and operational utility (can the user act on the answer?).
We run this pipeline on every release. No baseline metrics, no deploy.