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 suitable for scheduled runs on a daily or weekly cadence, though on-demand execution remains viable if latency tolerance is 2–5 minutes. To reduce future runtime, prioritize filtering or aggregating rows upstream of LLM processing—reducing the 891-row payload would yield the highest return, since synthesis scales linearly with input volume while SQL execution is already lean.