AI compliance is becoming increasingly critical as AI systems grow more powerful and pervasive. Yet the rapid expansion of AI policies creates substantial burdens for resource-constrained practitioners lacking policy expertise. Existing approaches typically address one policy at a time, making multi-policy compliance costly. We present PASTA, a scalable compliance tool integrating four innovations: (1) a comprehensive model-card format supporting descriptive inputs across development stages; (2) a policy normalization scheme; (3) an efficient LLM-powered pairwise evaluation engine with cost-saving strategies; and (4) an interface delivering interpretable evaluations via compliance heatmaps and actionable recommendations. Expert evaluation shows PASTA's judgments closely align with human experts ($ρ\geq .626$). The system evaluates five major policies in under two minutes at approximately \$3. A user study (N = 12) confirms practitioners found outputs easy-to-understand and actionable, introducing a novel framework for scalable automated AI governance.

翻译：人工智能合规正随着AI系统日益强大与普及而变得愈发关键。然而，政策的迅速扩展给缺乏政策专业知识、资源受限的实践者带来了沉重负担。现有方法通常一次仅处理单一政策，使得多政策合规成本高昂。我们提出PASTA——一种可扩展的合规工具，集成四项创新：（1）支持开发阶段描述性输入的全面模型卡格式；（2）政策规范化方案；（3）配备成本节约策略的高效LLM驱动成对评估引擎；（4）通过合规热图与可操作建议提供可解释评估的交互界面。专家评估表明，PASTA的判断结果与人类专家高度一致（ρ≥.626）。该系统可在不到两分钟内以约3美元的成本评估五项主要政策。一项用户研究（N=12）证实，实践者认为输出结果易于理解且具备可操作性，为可扩展的自动化AI治理提供了全新框架。