Jev judgment model outperforms cross-encoder reranker on agent memory selection in production

According to Unblocked, Jev, a calibrated judgment model, replaced a cross-encoder reranker for selecting which saved notes an agent should view, and showed higher precision and recall on 12,927 labeled question-note pairs from 292 production questions. Cost and latency remained equivalent, with threshold tuning proving more effective than prompt adjustment.

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