This study represents a significant advancement in the field of autonomous laboratory operations and has several far-reaching implications for scientific research. At its core, the work addresses a fundamental challenge in automated laboratories: the need for continuous quality control without human oversight. By developing a system that can detect experimental anomalies in real-time, we have eliminated a task that traditionally required experienced human operators.