RAG / vector DB infrastructure but no eval framework (Ragas, DeepEval, TruLens, Promptfoo)

This check looks for an evaluation framework, such as Ragas, DeepEval, TruLens or Promptfoo, wired into a site's RAG (retrieval-augmented generation, an AI technique that looks up your own content before answering) or vector database infrastructure. That infrastructure was found here, but no eval framework was detected. Running RAG in production without an eval framework means every model swap, chunking change, or prompt update ships blind, with no automated way to catch a quality regression before it reaches users. Ragas and DeepEval are the standard pre-deploy gate in 2026 specifically because manual spot-checking doesn't catch this reliably. Your engineering team should add Ragas or DeepEval to your CI (continuous integration, the automated pipeline that tests code before it ships) pipeline, defining four metrics: faithfulness, answer relevancy, context precision, and context recall, and block deploys that regress against baseline. Budget two to three weeks to build the evaluation datasets and wire this into every pull request touching retrieval or generation.