Unstructured Data Digitalization

An end-to-end digital solution designed to execute a series of facility engineering workflows for large volumes of data. Powered by human-in-the-loop machine learning to achieve objectives in a significantly shorter timeframe.


When you cut to the chase, Industry 4.0, digital transformations, digital twins and predictive maintenance all deliver the same thing: Real time data driven decisions. It enables facility teams to:

Consider maintenance. Most of the talk is centered on predictive analytics for sensor data. The issue is that if the algorithm predicts some equipment will fail two weeks from now, an engineer will also want:

  • Calibration records to confirm it’s the equipment and not the sensor that’s failing
  • Failure records to help diagnose the probable cause of the failure
  • Equipment specifications to determine which parts, tools and people are needed for the fix
  • System configuration to determine if any auxiliary equipment can be maintained at the same time

However, this information may be locked in scanned engineering drawings and documents like FMEA that use specialized terminology.

Powerful real time data driven decisions should connect and siloed text, image, time series, and structured data.

  • Need to access text and image data, and connect it with other data
  • Problems include scanned documents, specialized terminology and siloed data

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