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Optimize interconnected systems
Adapt continuously to changing conditions
Reduce operational effort












































etalytics continuously learns how your energy systems behave and optimizes cooling, heating, ventilation and industrial infrastructure in changing conditions, reducing energy costs and emissions while maintaining operational stability.
etalytics connects operational data across your energy infrastructure, creates system-level transparency with digital twins, and deploys AI-driven optimization that operators can understand and trust. etalytics coordinates the full system with indefined operating boundaries to improve efficiency, resilience, and sustainability.
Coordinate chillers, pumps, cooling towers, free cooling strategies to reduce energy consumption while maintaining required conditions.
Improve boilers, heat pumps, heat exchangers and thermal storage operation based on demand and system behavior.
Adjust ventilation and airflow, strategies based on actual demand instead of fixed assumptions.
Renewable generation and flexible demand are integrated into the control strategy based on availability, timing, and operational priorities.
etalytics follows a structured three-step deployment model.
Reduce total energy input and cost across the optimized scope.
Measured by normalized kWh or MWh consumption, energy cost in EUR or USD, and savings compared with an agreed baseline.
Reduce emissions by operating assets more efficiently and shifting operations where lower-carbon energy is available.
Measured by CO2e reduction over a defined period.
Reduce manual setpoint changes, overrides, and reactive troubleshooting.
Measured by manual intervention rate, override events, and operator time spent on recurring control adjustments.
Avoid unnecessary operation and prioritize efficient modes such as free cooling, optimized part-load operation, and coordinated asset use.
Measured by runtime hours, start-stop cycles, and utilization of active versus passive or more efficient modes.
Maintain temperatures, pressures, humidity, airflow, or other operating parameters within defined boundaries.
Measured by deviation from target ranges and percentage of time within operating limits.
Use thermal inertia, storage, on-site generation, and price signals where relevant.
Measured by shifted load, avoided peak demand, use of favorable tariffs, or demand response participation.
Quantify savings potential, technical fit, risk, and implementation effort before scaling.
Measured by expected savings versus solution cost and a clear rollout decision.

Start with a feasibility assessment. We analyze your existing infrastructure, identify optimization opportunities, and define a practical path toward AI-supported energy control.
Trusted by operators across data centers and industry








