EnergyTwin Features

Energy Twin is an AI solution for energy savings and predicting energy consumption

Energy Twin Preview

Energy Twin is a machine learning solution for energy consumption analysis, designed to identify problems and reveal the potential for future energy consumption savings and optimization.

ET Features & benefits

Anomaly detection

  • AI supervises data in real-time for you
  • A systematic approach regardless of the portfolio size
  • Prioritization by  avoidable energy estimate

Energy savings quantification

  • M&V baseline modeling
  • Peak demand prediction
  • Tailored KPIs for identifying energy saving opportunities

AI simple

  • You do not need to write a single line of code
  • You do not have to be a mathematical modeling expert
  • Smooth integration with SkySpark and other platforms

Features & pricing

Tech specs



SkySpark is a universal analytical platform for identifying issues, faults, deviations, and anomalies.

  • Full integration of SkySpark features (rules, KPIs, tailored views, reports, etc.) and easy to use interface
  • Are you new to SkySpark? We can provide hosting (SaaS) or deliver a SkySpark license with Energy Twin installed
  • Two Energy Twin extensions for SkySpark are available at StackHub:

Other platforms

Energy Twin solution can be integrated into any other open platform using open API.

  • Integration to various platforms and software tools such as
    • SCADA – Supervisory Control and Data Acquisition 
    • EMIS – Energy Management Information Systems
    • Custom data platforms
  • Examples of integrations:

Our services

Custom Energy Twin enhancements

We can provide you with custom enhancements, namely:

  • Custom views based on ET model
  • Reports based on ET model
  • Tailored Sparks and KPIs based on ET 

Machine learning 
applications in SkySpark

We will help you with custom ML application in the following steps:

  • Assessment of statistical properties based on your data (using R)
  • Model structure design
  • Custom ML application design and implementation in SkySpark and other platforms

Case Studies

These case studies accurately illustrate the possible practical benefits of machine learning for HVAC operation. Thanks to ET, a significant potential for energy savings was found and fully exploited during subsequent modifications of the building management system resulting in successful savings in energy consumption and building operation costs.

What our clients say