Safety Layer

Safety Layer is the protective component that intercepts prompts and model outputs to enforce ethical, legal, and brand policies before content reaches end users. Deployed in chatbots, autonomous agents, and generative APIs, it combines rule-based filters, classification models, toxicity scorers, and prompt-injection detectors to block disallowed requests, redact sensitive data, or rewrite hazardous text. Advanced implementations add reinforcement-learning shields that score responses against a reward model tuned for harmlessness, while context-aware throttles limit rapid misuse. The layer runs in-process for millisecond latency or as a microservice for centralized governance, logging every decision for audit trails and SOC 2 compliance. Key metrics include false-positive rate, jailbreak success rate, and latency overhead. By sitting between the model and the outside world, a Safety Layer converts raw generative power into enterprise-grade, regulation-ready AI.