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Data-driven operational efficiency

Use equipment telemetry and state-of-the-art predictive deep learning models to reduce waste, equipment failures and increase raw material utilization
Increase yeild and decrease costs by forecasting quality deterioration, catalyst depletion, failures, downtimes and overall process degradation.
  • Chemicals
  • Oil and gas
  • Metals and mining
  • Pulp and paper
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datarythmics effimly
Cloud system for process manufacturing forecasting
  • Model library
    Extensive deep learning models library for fast roll-out. You only need to provide historical data, and we'll train the best possible model for the task.
  • Interpretability
    effimly estimates input factors impact, both quantitatively (how much each factors impact the forecast) and qualitatively (value is too high, too low, too volatile, and more).
  • Fast deployment
    Online data transfer is secure and easy to setup with effimly SDK. We'll do the rest, including API and dashboard.
  • Subscription
    When the system is ready, you only pay for what is really used. Subscription fee scales with number of input data streams used and data frequency.
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Tilda Publishing
How It Works
Risk-free, ready-to-use forecasting system in 2 months with effimly
~ 3 weeks / free
Problem and data assessment
~ 4 weeks / fixed costs
Modeling
~ 2 weeks / free
Deployment
subscription
Operational
Contact us
Custom services we provide
  • Root cause analysis
    Data-driven
    We analyze historical telemetry to uncover main sources of equipment failures or inefficiencies and provide actionable insights to improve equipment performance.
    Contact us
  • GIS
    Satellite, aerial, LIDAR
    We analyze and build data products out of vector, raster (satellite and aerial imagery) and point cloud (LIDAR) GIS data to bring operational efficiency into mining and forestry industries.
    Contact us
  • Consulting and training
    Online or onsite
    We provide training and consulting services on how to start and manage data-driven projects and improve institutional readiness to machine learning adoption.

    Together with AI Today.
    Contact us
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Tilda