AI-Driven Cooling and Refrigeration Optimization Reduces energy-related operating costs and GHG emissions 20-40%

What is CESS (Chiller Energy Saving System)?

CESS (Chiller Energy Saving System) reduces cooling and refrigeration energy use by 20-40%. Our patented AI/Machine-Learning technology dynamically manages large centralized cooling systems using their own native controls through its standard interface, for a non-disruptive implementation. In a typical commercial property, cooling is approximately 40% of the total energy consumption; and 20-40% savings would lead to a substantial reduction in total energy use, costs and GHG emissions.

CESS consists of a series of customized software-driven algorithms implemented on a Programmable Logic Controller (PLC) panel that determines and optimally adjusts the functioning of various chiller system components (chillers, fans, pumps, air handling units, variable frequency drives (VFDs) and cooling towers).

Key features
  • Patented Technology

  • 20 to 40% reductions in cooling-related energy, costs and greenhouse gas (GHG) emissions with 1 to 3 year payback

  • relies on native chiller system controls consistent with manufacturer specifications; therefore, there is no impact on manufacturer warranty

  • OEM backs with a performance guarantee

  • Implementation is completely non-disruptive to present-state operations

  • Capable of remote monitoring and troubleshooting

  • Flexible interface for easy connection to any building management or building automation system (BMS/BAS) and human-machine interface (HMI)

  • Diagnostics provide automated response and corrective action suggestions.


Your BMS or BAS generally has the capability to specify various chiller setpoints, but it does not automatically adjust or optimize the set points in response to changing weather conditions or user requirements continuously and dynamically modifies operating parameters to obtain optimum efficiency without operator intervention. CESS does not replace you BMS or BAS; makes it smarter.