Save time with an end-to-end automated ML process

The traditional approach, where you spend three to six months building a model, training it, testing it, and operationalising it, maybe longer, is not scalable if you want to achieve results.

- Denis Marshment, previous Global Vice President Data Science Customer Solutions, Worley

Auto Machine learning

AI Insights in Minutes

Traditional machine learning can take months, with weeks spent on ingesting and manually manipulating data. AutoML automates the time-consuming repetitive tasks in the machine learning process.

Unlike other automated ML products on the market, OPUS has an automated end to end pipeline, that includes data ingestion and pre-processing of structured or unstructured data, auto machine learning and ML-Operations.

OPUS’ model wizard allows users to build models in minutes that target specific outcomes such as,

  • Predict when the next failure of undesirable event will occur (see our Time to Failures AI Model Explainer)
  • Predict what a value will be in the future,
  • Deviation from a predicted value (see our Deviation Model Explainer)
  • Identify the root cause of an event,
  • Identify when equipment or process is degrading or not operating correctly,
  • Predict when equipment maintenance is required.

 

Expedite your machine learning process from months to minutes

Learn More About OPUS

Focus on the Insights NOT the code

VROC OPUS allows you to focus on the insights that you can rapidly acquire, rather than the code. With rapid processing and high model accuracy levels, you can focus on the insights obtained to support the business decisions you need to make. The model’s by-products can be used to easily visualise the insights on dashboards, using the platforms inbuilt data visualisation features.

Once the model has been trained the user can automatically operationalize it. The insights will automatically refresh on the dashboard based on the live data which is ingested into DataHUB+. Users can set alerts based on pre-defined thresholds, so they are always informed, anytime, anywhere.

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VROC's End-to-End AutoML Pipeline

VROC's unique end-to-end ML pipeline include AutoML and MLOps capability
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