An autonomous humanoid RL training fleet manager built end-to-end on UiPath Maestro BPMN. AI agents analyze anomalies, humans approve critical gates, RPA robots execute — all governed by BPMN.
Teams burn thousands of dollars on cloud GPU instances (AWS, GCP, AMD) that sit completely idle after training finishes.
RL runs silently diverge or collapse for hours — reward flatlines, gradients vanish — before anyone notices.
No unified system for anomaly triage, human-in-the-loop approvals, and auditable write-back to cloud registries.
Click "Run Pipeline" to simulate 8 real training anomalies being triaged by AI agents