Save time with an end-to-end automated 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

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,
  • Predict what a value will be in the future,
  • 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 with OPUS.

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Product Features

Why our customers choose VROC

Produce AI models in minutes with no code AI icon

Rapid Modelling

Models can be built in minutes and automatically deployed straight into your live environment. No limitation on the number of models or data volume.

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AI Model Wizard

Our simple step-by-step model wizard makes AI modelling easy, no programming or coding required.

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Detailed Predictions

Drill-down insights highlight the root cause along with contributing factors and time to failure. Model confidence rating automatically calculated.

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Unlimited AI Models

No limit on the number of AI models that you can build. Test theories rapidly and scale rapidly

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Auto AI

Focus on the insights not the algorithms

VROC OPUS allows you to focus on the insights that you can rapidly acquire, rather than the algorithm and 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 DataHub4.0. Users can set alerts based on pre-defined thresholds, so they are always informed, anytime, anywhere.

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End-to-end auto AI pipeline

OPUS No code AI diagram

Our client’s success is our success

“Trying to scale machine learning models across thousands and thousands of failure modes on a plant, is probably not practical in the traditional approach to data science, where you can spend three to six months building a model, training it testing and operationalising it, maybe longer.”

Global Vice President, Data Science Customer Solutions, Worley.

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Get started with VROC today

Ready to embark on a pilot project or roll-out the innovation enterprise wide? Perhaps you need assistance integrating your systems or accessing your data? We have a solution to help you as you progress through your digital transformation.