“Zero Rule” is a one-stop AI content security review system based on a large self-evolving model. It is designed for enterprises to solve the pain points of low efficiency, high cost, and inaccurate risk identification of mass content reviews. Adhering to the concept of “AI Governance AI” in response to the high cost of traditional manual review, low efficiency, different standards, and the new risks brought about by the proliferation of AIGC content, the “Zero Rule” provides full-modal, high-accuracy, 7×24 uninterrupted content security protection. It supports full-mode recognition of text, images, audio, and video, and can accurately identify 350+ risks, with an accuracy rate of up to 99.98%; the review efficiency is increased by more than 50 times, the comprehensive cost is reduced by 60%, and the P95 delay is as low as 30 seconds, and the performance far exceeds that of traditional machine review. Relying on multi-agent collaborative decision-making and self-evolution capabilities, the system can deeply understand complex semantics, cope with complex scenarios such as metaphors and variants, calibrate rules in real time according to business requirements, and continuously optimize protection effects. It currently serves leading customers in various industries such as gaming, e-commerce, social networking, and AIGC. It processes tens of millions of levels of content per day, and is a mature solution verified by companies such as People's Online and Acquire. Build a content security infrastructure in the digital age to help enterprises reduce costs and increase efficiency, focus on core business, avoid compliance risks, and clean up the content ecosystem.