Pairwise Tail-Span Authorization for Resource-Constrained Filtered Search

Across a 50M-vector filtered-retrieval stress grid, the fastest recall-feasible action changes on 364/940 adjacent edges in the 5–15% selectivity band, versus 351/3,860 edges elsewhere. These reversals turn a plausible top-ranked plan into lost generation slack when its fanout or SSD traffic produces a latency-tail error. RAVEL makes execution of that winner a pair-conditioned authorization decision: held-out recall tables and RAM, SSD, and latency caps define feasible P1–P4 actions; calibrated median-to-P95 spans characterize the leading pair; and ambiguous requests take a regime-local fallback. On dual AMD EPYC 7543 CPUs with 128GB RAM and a 1TB SSD budget, RAVEL reaches 37ms P95 and 56ms P99 at a common 0.95 Recall@20 target, improving on GateANN's 44/70ms by 16%/20% and Qdrant's 68/101ms by 46%/45%. With actions, requests, recall tables, provisional ranks, and fallback implementation fixed, the executed-policy mis-pick rate falls from 12.6% for winner-only dispatch to 4.9%. At 80% authorization coverage, RAVEL reduces selective P95 excess latency from RCPS-Tail's 14.6ms [12.8,16.4] to 9.6ms [8.3,10.9]. The enterprise-selected gate also reaches 38.9ms P95 on 356 public band queries, compared with 41.8ms for RCPS-Tail and 58.7ms for the native policy. Layering this measurable tail-risk decision over existing kernels preserves retrieval latency budget for downstream generation without requiring an index replacement.