Book Demo
Book Demo
Energy Foresight
Detect anomalies early. Prevent failures.
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.
Identify risks early.
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.
Detect Hidden Issues Before They Disrupt Operations
Emerging faults, control issues, and abnormal operating conditions are identified early, helping teams prevent performance losses, unnecessary energy waste, and unexpected downtime.
Stop Performance Drift Before It Becomes Costly
Gradual efficiency losses become visible before they lead to higher energy costs, equipment wear, or persistent operational problems.
Reveal the Hidden Drivers Behind Energy Waste
The platform analyzes relationships across sensors, controls, and process data instead of evaluating individual signals in isolation. Teams uncover the root causes of inefficiency faster, enabling more informed operational decisions and targeted improvements.
Prioritize Deviations by Impact
Detected deviations are automatically ranked based on their potential operational and energy impact. Engineers spend less time investigating low-priority alerts and can focus on the issues with the greatest impact on efficiency, reliability, and costs.
Gain Time to Prevent Operational Problems
The system identifies emerging abnormal patterns before they exceed critical operating thresholds. Early visibility gives teams more time to investigate, adjust operating conditions, and avoid costly incidents or unnecessary downtime.
Understand What Changed — and Why
Every detected deviation is linked to the affected signals, operating conditions, and timeline. Engineers can quickly understand what changed, where it happened, and where to begin root-cause analysis, reducing investigation time and accelerating corrective action.
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 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.
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
Proven impact
Trusted by leading operators worldwide
Equinix, Merck, and others achieve up to 50% cooling energy savings with etalytics. Explore our case studies.
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Data Center
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Equinix
Real results in live, mission-critical infrastructure.
"With the help of etalytics' expertise, we are implementing AI-based operational optimization of the cooling systems at the Frankfurt site [...]. We are thus supporting a highly innovative approach that can serve as a blueprint for an entire industry."
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
FAQ
Questions? We’ve got you covered.
Start with a free feasibility study
Ready to improve your facility's energy efficiency?
Discover where your biggest savings potential lies. Our experts analyze your energy system, identify opportunities, and show you the path to lower costs, emissions and resilient operations – with AI you can trust.
We empower industries to make complex energy systems and operations more intelligent, efficient, and resilient — with AI and digital twins that operators can trust.
