AGO AI Quality Gate (AGO) is an evidence-first quality-gate framework for retrieval-augmented generation (RAG) systems that enterprises can use to decide whether to promote, revise, or block a system version when evidence is incomplete and metrics come from fallible LLM judges. The framework was reported as deployed to address this recurring operational decision.
Enterprises adopting retrieval-augmented generation (RAG) face a recurring operational decision: promote, revise, or block a system version. The evidence is incomplete and the metrics come from fallible LLM judges. We report on AGO AI Quality Gate (AGO), an evidence-first quality-gate framework depl
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