> For the complete documentation index, see [llms.txt](https://docs.veedna.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.veedna.com/unifai/regulatory-compliance.md). # Regulatory Compliance {% hint style="info" %} **Feature availability:** Policy enforcement and compliance reporting require an active UnifAI deployment. See [UnifAI](https://www.lineaje.com/unifai) for details. {% endhint %} UnifAI continuously evaluates AI systems against OWASP AI Top Ten for LLMs, agentic application standards, and 11 major regulations including the EU AI Act and NIST AI RMF. ## What Is AI Compliance? AI compliance is the set of technical and operational controls your organization must implement to satisfy legal obligations across jurisdictions. It covers how AI systems are built, deployed, and monitored. Requirements span data governance, risk assessment, transparency, access controls, and disclosure obligations. Because regulations change and AI systems evolve, compliance must be evaluated continuously, not just at deployment. ## Supported Frameworks UnifAI maps to the following regulatory frameworks: * EU Artificial Intelligence Act (Regulation (EU) 2024/1689) * Executive Order 14110 on Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence * Japan Artificial Intelligence Basic Plan (2025) * California AB 3030 — Health Care Services: Artificial Intelligence * Maryland HB 1202 — Labor and Employment: Use of Facial Recognition Services * NIST Artificial Intelligence Risk Management Framework (AI RMF 1.0) * Interim Measures for the Management of Generative Artificial Intelligence Services (2023) * Saudi Arabia National Strategy for Data and Artificial Intelligence (SDAIA) * California AB 2013 — Generative Artificial Intelligence Training Data Transparency Act * California SB 942 — California AI Transparency Act * Australian Information Security Registered Assessors Program (IRAP) ## Policy-to-Framework Mapping UnifAI also translates regulatory standards into enforceable policies. You can use built-in policies covering AI threats, data security and privacy, identity and access control, vulnerability, and skills. Policies map directly to frameworks like OWASP and the EU AI Act. For example, UnifAI policy *AI\_APP\_SEC\_001: Do not allow malicious content via hidden prompts* maps to OWASP LLM01, LLM02, LLM04, LLM08, OWASP ASI-01, ASI-04, ASI-07, ASI-09, and EU/AI Act Art. 11, 12, 13, 50. To learn more, see [Policies](/unifai/policies.md) and [Viewing and Enabling Policies](/unifai/policies/viewing-and-enabling-policies.md). ## How UnifAI Keeps You Compliant UnifAI provides a structured compliance layer that continuously evaluates your AI systems against each framework's technically addressable requirements. It integrates directly into your deployment workflows — covering external regulations, security standards, and your organization's own internal policies. * **Policy mapping.** Automatically maps your existing policies to requirement areas within each framework, giving you a real-time view of which obligations your current controls address. * **Internal standard enforcement.** Ingests your organization's internal governance documents and corporate standards, translating them into enforceable policies alongside your external regulatory obligations. * **Continuous monitoring.** As frameworks update or new regulations take effect, UnifAI refreshes its mappings and alerts you to changes affecting your coverage status. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://docs.veedna.com/unifai/regulatory-compliance.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.