Pathwork Optimizes Life Insurance Underwriting with Precision Vector Search - Qdrant

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This post details how Pathwork uses Qdrant for life insurance underwriting, achieving significant accuracy improvements (MSE from 3.5 to 1.8) through scalar quantization, hybrid search, and advanced filter utilization. Performance was enhanced by storing vectors in RAM and improved scaling methods (replicas, shards, nodes), reducing latency from 9s to 2s. Usage grew 50% MoM, processed thousands of cases, and scaling was managed with additional nodes, sharding, and replicas.