In May 2024, Vybe Energy deployed its AI-driven chiller optimization platform at Oklahoma Panhandle State University (OPSU). Through September 2024, the results demonstrated clear and measurable impact.

Key Outcomes (May–Sept 2024)

~27–33% reduction in chiller energy use compared to a business-as-usual baseline.

Five-figure avoided electricity costs within the first operating season.

Early fault detection, including identification of a temperature sensor discrepancy and an unexpected chiller shutdown — helping prevent larger operational issues.

What Drove the Savings

The platform dynamically adjusted chilled water setpoints every 15 minutes based on real-time weather and load conditions. Instead of running at a fixed setpoint (e.g., 42°F), the system continuously optimized for the lowest possible kW consumption while maintaining performance.

Even in this early phase, the pilot demonstrated that AI-based optimization can generate significant savings from existing infrastructure — without equipment replacement.