"In a conventional way, we would form a team to look at the problem, and it would take weeks to fix that problem… technically you couldn’t get this particular decision to be made, as fast as that."
- Head of Offshore Operations
OPUS: An artistic work, especially on a large scale
OPUS’ automated end-to-end AI pipeline enables engineers, asset operators and SMEs to build AI models without any programming knowledge or experience. AI models can be built in minutes to target specific outcomes, providing real-time predictive insights, forecasts and alerts.
OPUS's unique holistic approach to analysing time-series data across the entire plant, rather than just individual pieces of equipment, means the no code AI platform can detect minute anomalies, with accurate predictions often days-to-weeks in advance. Customer teams can act on these insights, plan interventions, implement predictive maintenance and optimize operations.
OPUS can be used to form a baseline for new assets and optimize settings from the very beginning. This can be used by the asset owner to build accountability, support warranty and performance claims, and to postpone first planned shutdowns.
Implement AI predictive maintenance with OPUS. The advanced analytics provides alerts for equipment and process degradation, allowing for planned early interventions, scheduling of correct personnel and spare parts. Reduce your maintenance spend with OPUS.
Implement advanced analytics with OPUS to target specific outcomes, including asset lifespan extension, comparison of identical processes, reduction of energy usage, forecasting, optimisation of processes, reduction in flaring or emissions.
Forecast a future value, such as what a value will be at a set point in time, perhaps 24 hours, 7days, or 14 days in advance. Users can produce no-code AI models for an output, such as a future production level, or a future demand on their process or services. With future insights businesses can decide how they respond, scaling up or down or planning a necessary intervention to improve the outcome.
OPUS can assist companies create an energy baseline at an enterprise level, as well as provide insights which can be used to establish energy policies, inform targets setting, along with on-going essential insights to identify significant energy usage, opportunities for optimization and continual improvement at a granular actionable level.
Businesses can improve sustainability and net-zero carbon endeavours with AI insights. OPUS continually analyses all available data, providing insights to help companies prevent environmental incidents such as flaring and contamination, along with emission reduction. Build dashboards to monitor and report on sustainability targets and achievements, and detect areas for continual improvement.
OPUS's unique holistic analysis of your operational data, allows for detailed root cause analysis. Detect the root cause of an alarm, predicted fault or historical incident down to the individual component or sensor level. This level of detailed analysis provides critical insight for early intervention and future failure avoidance.
Models can be built in minutes and automatically deployed straight into your live environment. No limitation on the number of models or data volume.
Our simple step-by-step model wizard makes AI modelling easy, no programming or coding required.
Drill-down insights highlight the potential root cause and time to failure. Model confidence rating automatically calculated.
Start delivering on-going business value within four weeks from data ingestion
OPUS is uniquely designed to easily handle large volumes of time-series data, with a wide range of use cases across many different process industries. Some of these include Oil and Gas, Mining and Resources, Water or Power Utilities.
OPUS can be used as a standalone product, integrating with your existing process or data historian hosted on your public cloud or on-premise data centre, or OPUS can be used alongside DataHUB4.0 – VROC’s enterprise data historian. See the diagram below for how the VROC products integrate together, so you can achieve more from your data.
Download the product sheet to learn more about OPUS’s flexible hosting and integration features.
Whether you’re launching your first pilot or scaling AI across your enterprise, VROC’s end-to-end platform and expert team can help you unlock data, optimise performance, and accelerate results.
Interested in a demo of one of our data solution products?
DataHUB4.0 is our enterprise data historian solution, OPUS is our Auto AI platform and OASIS is our remote control solution for Smart Cities and Facilities.
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Complete the form below and we’ll connect you with the right VROC expert to discuss your project. Whether you’re launching a pilot, scaling AI across your enterprise, or integrating complex systems, we’ll help you turn your data into actionable insights—fast, efficiently, and with confidence.
The efficient deployment, continuous retraining of models with live data and monitoring of model accuracy falls under the categorisation called MLOps. As businesses have hundreds and even.
Learn more about DataHUB+, VROC's enterprise data historian and visualization platform. Complete the form to download the product sheet.
Learn how OASIS unifies your systems, streams real-time data, and gives you full control of your smart facility—remotely and efficiently. Complete the form to access the product sheet.
Discover how OPUS, VROC’s no-code Industrial AI platform, turns your operational data into actionable insights. Complete the form below to access the product sheet and learn how you can predict failures, optimise processes, and accelerate AI adoption across your facility.
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