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This paper introduces GRACE-RAG, a retrieval-governed, graph-augmented RAG architecture that externalizes structural reasoning from generation to a structured retrieval layer, enabling lightweight deployment in closed-domain institutional settings. Experiments show up to 20% quality gains with mid-scale models, reducing computational and latency footprint.