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RAG systems often look straightforward in a prototype, but production quality depends on much more than model selection.
In our experience, the main variables are document preparation, retrieval quality, metadata filtering, access control, citation support and a repeatable evaluation set. Monitoring failed retrievals is also more useful than tracking only generic model metrics.
We build these systems at AI Development Services. Which retrieval or evaluation metric has been most useful in your environment?