International Journal of Science, Engineering and TechnologyAuthors: Soham S. Jadhav, Omkar N. Gadakh, Atharv S. Gaikwad, Nisha D. Patil
Abstract: Modern enterprise workflows have evolved beyond plain text, now heavily relying on a mix of audio, video, and image-based exchanges. Consequently, the traditional paradigms of content moderation are becoming obsolete. Traditional moderation tools often fail in corporate settings because they were built for public platforms, prioritizing retroactive cleanup rather than real-time privacy and prevention, and relying on static, modality specific classifiers that fail to meet the real-time, privacy-centric, and context-aware demands of modern enterprise environments. This paper presents a comprehensive review of the state-of-the art in intelligent content moderation, analysing over 15 distinct methodologies ranging from Large Language Model (LLM)based guardrails to multimodal fusion architectures. We critically examine the transition from rigid API-based moderation to dynamic “Policy-as-Prompt” frameworks, evaluating their efficacy in handling code-mixed languages, audio-visual semantics, and organizational
