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RAIDS AI

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RAIDS provides continuous behavioral monitoring for AI systems operating in production environments. Unlike traditional AI observability tools that focus on performance metrics, RAIDS analyzes AI inputs and outputs to detect deviations from normal system behavior as they occur. Using deep learning-based anomaly detection, RAIDS establishes a baseline of typical AI behavior and continuously monitors for anomalies that may indicate security risks, operational failures, data misuse, or unintended system behavior. Detection occurs in real time with sub-100ms latency (23ms average), enabling rapid identification of emerging issues in live AI deployments. RAIDS operates as a black-box, non-intrusive solution, monitoring AI systems in parallel without introducing additional overhead or changes to existing models, pipelines, or workflows. This ensures continuous oversight without affecting operational performance. The platform is independent and vendor-agnostic, allowing organizations to monitor AI systems from any provider using a consistent, unbiased approach. Human-in-the-loop feedback is used to continuously refine behavioral baselines and improve detection accuracy over time.

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