Boost your Operational

Leverage the power of data & AI
to control the past, present
and future of your facilities


Business benefits

  • Reduce mantenance costs

  • Save time through efficient processes

  • Increase safety and reliability

showCase: Smart Facility Management

Facility Management,
Energy and Infrastructure
  • Enterprise (France, Germany, Europe)
  • >40 Tsd. Employees
  • >7 Bil.€ Revenue
  • Exists since year 1900
Initial situation
  • Ventilators with motor vibration sensors
  • SCADA system used only for monitoring
  • >3 years of unprocessed vibrational telemetry data & maintenance events data from incident management
  • High maintenance costs
  • Intensive maintenance schedule
  • Outdated warning and alarming system
  • No transparency about system state
  • No feedback about maintenance effects
  • Data integration & quality issues with telemetry data (inconsistencies, sampling rates)
  • Created elastic data lake in AWS
  • Preprocessed and cleaned data using plug&play pipelines
  • Built intelligent forecasting and classification model of incidents
  • Generated partially synthetic data to overcome the rare occurrence of some incidents
  • New predictive maintenance algorithm improves incident detection by 70% as compared to SCADA system
  • Incidents are detected early (up to 4 days ahead of time), allowing time for maintenance
  • Introduced intelligent monitoring based on dynamic alarm thresholds
  • Optimized the maintenance schedule


Out-of-the-box cloud AI service supporting seamless integration into any landscape. Plug&Play approach suitable for business users.

Big-data native
Use state of the art clustering methods to integrate different data sources and derive business critical insights.

Deep Learning to learn (almost) anything
Utilize our cloud advantage to build and train deep learning networks for predictive maintenance.

Methods & Algorithms
Deep Convolutional Networks, LSTMs, Decision trees, Boosted Trees, Random Forests, Kernel based methods

Forecast and predict
Combine parametric and non-parametric (tree- and kernel based) forecasting algorithm to accurately predict system failures.

Plug&Play Transfer Learning
Utilize your data and save on model training time by reusing pre-trained models on different machinery.

How it works Image

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