Blindly restarting a crashing JVM service during an OutOfMemoryError (OOME) makes it harder to identify root causes. OOM errors can lead to downtime and customer loss. A proposed AI-driven solution uses telemetry data to predict potential OOMs, allowing for automated remediation before incidents escalate, thus enhancing operational efficiency.