The 16 SQL queries against 891 rows suggest modest database overhead, indicating compute time is likely concentrated in LLM synthesis rather than data retrieval. This workload is well-suited for scheduled runs given the predictable query volume and row count, though on-demand execution remains viable if latency tolerance is 2–3 minutes. The primary lever for cost reduction is query consolidation—combining multiple single-table passes into fewer, wider SELECT statements would reduce round-trip overhead and downstream LLM input volume without sacrificing output quality.