This article presents a generic architecture that replaces per‑request fan‑out with context prefetching: fetch stable user context and policy/rule data once (per session or short time window), then perform local eligibility evaluation across many targets (e.g., merchants, items, or partners). This caching significantly reduces latency by minimizing redundant network calls, improving response times for eligibility checks, and lessening the load on backend user attribute management services. For high‑QPS systems that must annotate many targets per user request, it meaningfully shrinks downstream QPS, improves tail latency, and reduces compute—while aligning with established microservice patterns.