We monitor beehive health by analyzing in-hive audio with a custom ML pipeline. Our model achieved 98%+ test accuracy, including 94% recall for detecting critical queen-less colonies. We are now scaling up our dataset, and focusing on improving the model’s generalization to avoid overfitting.