MasterControl Seventeen Every Time

The paper introduces a governed approach to enterprise analytics in which a language model interprets user queries and a deterministic policy selects and runs pre‑approved analytical programs that return both results and evidence. The authors demonstrate that this restriction remains expressive for a defined analytical class—including relational operations, aggregation, comparison, windows, ranking, and similarity—while ensuring reproducibility through fixed meaning, policy, data, and execution rules. In experiments with 440 runs, three 8B models generated SQL and selected tools at runtime, whereas a policy‑executed analyzer achieved a perfect 110/110 match across all test datasets, though no runtime‑planning episodes matched the full answer‑and‑evidence contract. "whyItMatters":"The study shows that a governed, policy‑driven framework can reliably produce accurate, reproducible analytics results, highlighting a viable path for controlled AI‑driven data analysis."