Energy Foresight

Stop Unplanned Downtime Before It Starts

Early-warning anomaly detection

Performance-drift recognition

Multi-signal pattern analysis

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

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

Stop Unplanned Downtime Before It Starts

etaONE® dynamically detects and explains emerging risks and performance drift across your entire energy system, so your team can act before deviations turn into cost spikes, SLA breaches, or unplanned outages.

Equipment behavior is continuously compared against expected patterns, so unusual behavior surfaces weeks before it reaches a critical threshold — giving your team time to investigate, adjust, or prevent escalation.
Gradual efficiency loss and recurring deviations become visible while they're still small — before slow degradation turns into persistent waste or a reliability problem.
The platform reasons across combinations of sensor, control, and process data rather than isolated points, uncovering the hidden relationships manual monitoring can't catch.
Every deviation is ranked by operational relevance and linked to the affected signals, timing, and operating context, so engineers spend less time sorting noise and start root-cause analysis already knowing what changed, when, and where.
What You Get

Automated foresight for energy operations

etaONE® creates a physics-based digital twin that knows how your energy system should behave under current conditions. By continuously comparing expected and actual performance, it uncovers hidden inefficiencies and emerging faults early, giving operators time to act before conventional alarms even recognize there's a problem.  

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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.

Replace systems that can't keep up

Catch the dynamic, multi-signal drift that fixed rules and manual tuning were never designed to see.

Extend equipment lifecycle

Detect wear and fouling early to cut unplanned downtime and stretch the working life of chillers, pumps, and cooling assets.

Make complex systems manageable

Turn thousands of interdependent variables into a clear, ranked signal instead of component-by-component firefighting.

Preserve institutional knowledge

The digital twin captures how your specific site behaves, so expertise doesn't walk out the door when a senior engineer leaves.

Always stay in control

Detection and recommendations operate within your defined boundaries — the AI surfaces and advises; your team decides.

De-risk your SLAs and uptime commitments

Early detection of failure precursors reduces the excursions that threaten service-level guarantees.

Protect competitiveness in the AI era

Keep efficiency and reliability on the right side of the line where margin, contracts, and compliance are won or lost.

Improve performance without capital expenditure

More value from existing infrastructure — no new hardware, no rip-and-replace.

Scale from one site to the whole portfolio

Prove value at a single facility, then roll the same detection layer across the fleet.

Turn compliance into a byproduct

Continuous, portfolio-wide visibility feeds ESG and regulatory reporting automatically.

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Use Cases

Foresight built into your operations.

Data centers

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

Large commercial and high-load buildings

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

Manufacturing and automotive

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

Pharmaceuticals and clean environments

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

Storage-Based Load Shifting

Scenario: Battery or other stored energy capacity exists but is not used strategically during peak periods.

Value: Stored energy smooths short spikes and lowers maximum grid demand.

Typical stakeholder: Energy Manager

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. 

Ready for the next step?

See how etaONE® can optimize your facility’s energy systems.

Start with a free feasibility study. We analyze your existing data, estimate your savings and risk-reduction 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.