The 30 SQL queries across 5 tables and 8,948 rows indicate that data retrieval is the primary compute driver; LLM synthesis typically consumes less wall-clock time than multi-table joins and aggregations at this scale. This workload is suitable for scheduled runs on a 4–6 hour cadence but risks timeout on on-demand execution if users expect sub-minute latency. The primary lever to reduce future cost is query optimization—specifically, pre-aggregating the Sales Pipeline and Accounts tables at ingest time and eliminating redundant joins across Products, which would collapse the 30-query count to 8–12 and proportionally reduce database load.