发表机构
MasterControl AI Lab（MasterControl AI实验室）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
该研究提出一种语言模型结合确定性策略的企业分析管控方法，经实验验证，策略执行的分析器在110次测试中全部匹配结果与证据契约，为企业分析提供了可复现的方案。
AI 中文摘要
我们研究一种受管控的企业分析方法：语言模型解读问题，而确定性策略则选择并运行预先批准的分析程序，该程序会同时返回结果和证据。我们表明，在定义的分析类别内，通过关系运算加上聚合、比较、窗口、排序和相似度操作，这种限制仍能保持表达能力。固定的含义、策略、数据和执行规则也使结果可复现。在440次运行中，三个8B模型在运行时生成SQL并选择工具，而Qwen3-8B仅解读意图，由策略执行批准的程序。在所有测试数据集中，330次运行时规划事件均未满足完整的结果与证据契约；经策略执行的分析器在110次运行中全部匹配。这是特定配置下的结果，并非运行时智能体在其他设计下无法成功的证据。
英文摘要
We study a governed approach to enterprise analytics: a language model interprets the question, while deterministic policy selects and runs a pre-approved analytical program that returns both results and evidence. We show that this restriction can remain expressive within a defined analytical class, using relational operations plus aggregation, comparison, windows, ranking, and similarity. Fixed meaning, policy, data, and execution rules also make results replayable. Across 440 runs, three 8B models generated SQL and selected tools at runtime, while Qwen3-8B interpreted intent only and policy executed the approved program. None of 330 runtime-planning episodes matched the full answer-and-evidence contract across all test datasets; the policy-executed analyzer matched 110 of 110. This is a configuration-specific result, not evidence that runtime agents cannot succeed under other designs.
