Optimize Complex Energy Systems

See your energy demand before it costs you

Driver-based demand forecasting

Early peak-risk detection

Weather- and schedule-aware modeling

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

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

Detect anomalies before they become critical.

Peaks are expensive. We help you avoid them.

etaONE predicts future demand peaks and enables action before they lead to higher grid charges, procurement costs, or capacity contraints.

Forecast models learn from your historical consumption and the operational and external inputs that drive it, so your team anticipates expected load instead of reacting to what already happened.
Forecasted load curves highlight the intervals where demand is likely to exceed expected thresholds, giving you time to flatten, shift, or prepare before a peak affects cost or capacity.
Weather, production, and occupancy schedules are factored in as load drivers, so forecasts reflect the real activity behind your energy use rather than a generic curve.
Actual consumption is continuously compared against forecast to surface deviations early, while forward demand visibility gives energy teams a structured basis for short- and mid-term procurement and planning decisions.
What you get

System-Level AI Control Built on Digital Twins

The solution can be introduced step by step, starting with a focused use case and scaling across additional systems, assets, or sites oncethe business case is validated.

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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.
For engineering and company leaders

Outcomes your team and your business can measure.

Replace planning that can't keep up

Model weather, production, and occupancy together instead of comparing them by hand in spreadsheets.

Flatten and shift load intelligently

Use forward demand visibility to act on peaks before they happen, using thermal inertia, storage, and flexible operation.

Make complex demand manageable

Turn many interacting load drivers into a clear, forward-looking signal of what to expect and when.

Separate signal from noise

Distinguish a normal load swing from a preventable peak before it hits.

Always stay in control

Forecasts and recommendationsoperate within your defined boundaries; the AI surfaces and advises, your teamdecides.

Cut peak-driven energy costs

Reduce exposure to demand charges and unfavorable intervals by seeing peaks before they occur.

Strengthen procurement decisions

Base short- and mid-term energybuying on structured forecasts instead of outdated assumptions.

Improve planning without capital expenditure

More value from existinginfrastructure, with no new hardware and no rip-and-replace.

Scale from one site to the whole portfolio

Prove value at a singlefacility, then roll the same forecasting layer across the fleet

Turn flexibility into a financial lever

Shift load, avoid peaks, andcapture favorable tariffs where market signals allow.

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Use Cases and Industries

Industries Using Our Load Forecasting Solutions

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.

Large commercial and high-load buildings

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

Why etalytics

Because efficiency software should do more than show dashboards.

etaONE® turns your operational data into a live digital twin of your energy system and uses AI to continuously identify the best operating strategy for your site. The result is lower energy cost, earlier detection of performance drift, and better operational decisions with less manual work – without replacing your existing infrastructure.

System-level optimization, not siloed fixes

etalytics optimizes across cooling, heating, ventilation, electrical infrastructure, storage, CHP, and microgrids.

Digital twin foundation

Physical and data-driven models make complex system behavior transparent and provide the basis for reliable optimization. 

AI operators can trust

Recommendations and control actions are explainable, bounded, and validated against real operating behavior. 

Built for critical infrastructure

The solution supports fallback strategies, manual override options, and operation within defined safety and reliability boundaries.

Existing-infrastructure-first approach

Projects usually start with available sensors, meters, data sources, and control points, with additional hardware recommended only where core measurements are missing, or model accuracy would materially improve. 

Business-case driven delivery

etalytics focuses on optimization scopes where expected savings and operational value exceed solution cost and create a validated business case. 

Fast path to value

A focused first implementation can often be completed in roughly three months once access, data, and customer-side decisions are available, depending on project scope and customer readiness. 

Energy Foresight

See what etaONE® forecasts for your facility.

Start with a free feasibility study. We analyze your existing data, estimate your peak-reduction and planning potential, and show you the path — no system changes, no obligation..

Trusted by operators across data centers and industry

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FAQ

Questions? We’ve got you covered.

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.