Optimize Complex Energy Systems

AI Adaptive Energy Control Under Changing Conditions

Optimize interconnected systems

Adapt continuously to changing conditions

Reduce operational effort

For Data center cooling, Manufacturing HVAC, District energy systems , Thermal storage

Trusted by leading data centers, manufacturers, and energy innovators.

Control Complexity

The challenge of operating complex energy systems

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.

Optimize interconnected systems — coordinate cooling, heating, ventilation and electrical infrastructure instead of individual assets
Adapt continuously to changing conditions — respond to weather, loads, production schedules and energy prices
Reduce operational effort — minimize manual tuning, overrides and reactive troubleshooting.
Maintain stable operation — optimize within defined technical and business constraints .
Volatile energy prices increase the cost of inefficient operation and missed flexibility potential
What You Get

System-Level AI Control Built on Digital Twins

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.

Cooling optimization

Coordinate chillers, pumps, cooling towers, free cooling strategies to reduce energy consumption while maintaining required conditions.

Heating and thermal optimization

Improve boilers, heat pumps, heat exchangers and thermal storage operation based on demand and system behavior.

Air handling optimization

Adjust ventilation and airflow, strategies based on actual demand instead of fixed assumptions.

Multi-energy optimization

Renewable generation and flexible demand are integrated into the control strategy based on availability, timing, and operational priorities.

Simple Process

How it works

etalytics follows a structured three-step deployment model.

Platform integration
We connect to existing infrastructure such as SCADA, BMS, PLCs, historians, submeters, utility interfaces, weather data, and relevant tariff or market signals. The standard approach is to use existing data, sensors, meters, and control infrastructure first instead of adding new hardware.
Digital twin setup
We structure data by system, asset, and energy flow, then model the relevant physical and operational relationships. This creates transparency, identifies inefficiencies, validates optimization potential, and can provide virtual measurements such as estimated volume flows when direct measurements are not available.
AI control deployment
Based on the validated system understanding, etalytics deploy optimization logic in open-loop recommendation mode or closed-loop adaptive control. Control actions operate within defined boundaries and include transparency, manual override options, and fallback strategies for mission-critical operations.
Measurable Impact

Operational Improvements That Matter

Lower energy costs

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.

Verified carbon energy savings

Reduce emissions by operating assets more efficiently and shifting operations where lower-carbon energy is available.

Measured by CO2e reduction over a defined period.

Less manual effort

Reduce manual setpoint changes, overrides, and reactive troubleshooting.

Measured by manual intervention rate, override events, and operator time spent on recurring control adjustments.

Lower equipment runtime and wear

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.

Higher stability and supply quality

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.

More intelligent use of flexibility.

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.

Validated business case

Quantify savings potential, technical fit, risk, and implementation effort before scaling.

Measured by expected savings versus solution cost and a clear rollout decision.

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Use Cases and Industries

Where Adaptive Energy Control Delivers Value

Data centers

Optimize cooling plants, free cooling, hydraulic distribution, airflow-related dependencies, and supply temperatures while protecting mission-critical uptime and stability.

Pharmaceuticals and clean environments

Improve HVAC and utility efficiency while maintaining stable environmental conditions, compliance requirements, and operational boundaries.

Chemicals and industrial production

Coordinate cooling, heating, ventilation, thermal utilities, and electrical infrastructure under fluctuating production loads and changing energy prices.

Manufacturing and automotive

Reduce energy waste in process cooling, ventilation, heating, and site-level energy systems with variable production schedules and operating modes.

Large commercial and high-load buildings

Improve performance in complex HVAC environments where demand, occupancy, weather, and operating schedules change continuously.

Ready for the next step?

See what etalytics can unlock at your site.

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

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FAQ

Questions? We’ve got you covered.

What is AI adaptive energy control?

AI adaptive energy control combines operational data, digital twins, and optimization algorithms to continuously improve how energy systems operate while respecting defined constraints.

Is this only about HVAC?

No. HVAC is often a starting point, but etalytics can optimize broader energy systems including cooling, heating, storage, CHP, renewable generation and electrical infrastructure.

Do we need new hardware?

Usually not. Most projects begin with your existing sensors, meters, and control systems. Additional hardware is recommended only when critical measurement is missing.

How long does deployment take?

A focused first implementation can typically go live in roughly three months, depending on system complexity and data availability.

Is it safe for critical infrastructure?

Yes. Deployments begin in recommendation mode and progress to automated control only when you choose. Every action operates within predefined safety limits, with manual override and instant fallback to conventional control.

Does AI replace operator decisions?

No. etalytics is designed to support operators with transparent recommendations and controlled automation within approved operating boundaries.