Natural-Language Copilot Cut Analyst Query Turnaround From 3 Days to 90 Seconds

SpeedMVPs built a natural-language analytics copilot on top of their existing Snowflake warehouse, using GPT-4o for NL-to-SQL generation with a schema-aware prompt layer that respected their existing column-level permissions and data masking policies. The system included a governed query sandbox (read-only analyst role, query cost cap via Snowflake resource monitors), an in-browser result explorer with chart auto-generation via Recharts, and a full audit log of every question, generated SQL, and result set stored in Postgres for compliance review.