Cleanlab addresses the persistent issue of AI models' hallucinations, where systems confidently provide incorrect answers due to gaps in training data and misaligned incentives. To combat this, Cleanlab introduces a trustworthiness guardrail that detects and blocks inaccurate AI outputs in real-time, preventing operational and reputational damage. This system uses advanced uncertainty estimation to evaluate AI confidence and automatically replaces potentially inaccurate responses with safe fallback messages or expert-verified answers. Cleanlab's approach includes a combination of real-time prevention and continuous improvement, leveraging a growing library of verified knowledge to enhance AI accuracy while maintaining human oversight. Their Trustworthy Language Model (TLM) is highlighted as an effective method for detecting hallucinations, and the guardrails are designed for easy deployment without requiring model retraining or infrastructure changes.