Definition
A search cache layer is a local store (SQLite, Redis, DuckDB) of typed search API responses, keyed by query plus surface, that returns cached results for repeat queries within a TTL — typically 1 hour for SERP, 6+ hours for static pages.
In Depth
AI agents repeat queries more than humans do. A research agent that fans out to the same 30 keywords every morning can hit a 60-80% cache rate after week one. The pattern documented by an r/crewai post used SQLite returning JSON in 50ms; the same pattern works with any structured search API (Scavio, Serper, Tavily). Cache key composition matters: include the surface (search vs reddit/search vs youtube/search), the full query string, and any modifiers (search_type, country, language). TTL choice depends on freshness need — SERP for breaking news at 5-15 minutes, Reddit threads at 30 minutes, structured product data at 24 hours.
Example Usage
The agent's search cache layer hit 67% on day five of operation, cutting Scavio per-day spend from $0.42 to $0.14 and reducing tail latency from 1.2s to 35ms on repeat queries.
Platforms
Search Cache Layer is relevant across the following platforms, all accessible through Scavio's unified API:
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