Industrial data utilization for a competitive advantage

Increase the accuracy and speed of advanced analytics with OPUS. Data specialists can build AI models and use in-built data science tools within the platform, deploying the models directly into the live environment. Our end-to-end pipeline makes model operationalization easy, removing the many barriers that normally exist , which reduce the efficiency and accuracy of machine learning and data science.

OPUS automates the creation of machine learning and artificial intelligence models. Users can build no-code models of their problem statement or process in minutes using our 5 step model wizard. By using OPUS, businesses can now scale machine learning, democratizing the use of data throughout their organisation for improved business decisions.

Discover a scalable data historian that is built for industrial businesses with large volumes of time-series and process data. Businesses can now easily capture, store, access and analyse all their data. Meaning one place for all your operational data, across the entire enterprise.

For companies that want a reliable, scalable solution, DataHUB4.0 has been built using distributed micro-services framework, meaning its faster and more reliable without the complex hardware and infrastructure that is used by traditional data historians.

Integrate real-time operational data and AI predictions with your 3D plant visualisation for remote monitoring and operations. Teams no longer need to work in the 'dark'. By integrating all current and future performance insights , businesses can optimize their maintenance planning and scheduling to improve asset integrity and reliability.

Businesses can integrate financial and operational data for accurate ESG and carbon accounting. In addition businesses can use the AI tools for critical insights to reduce emissions, through the reduction of energy consumption, energy waste, flaring and through the optimization of processes.

Businesses can now easily build and operationalize models within minutes using OPUS' end-to-end AI pipeline. Monitor and manage thousands of models easily, and receive alerts when models predict negative future outcomes (equipment failures, high energy consumption, reduction in production), so you can act more decisively to improve business outcomes.

With an end-to-end AI pipeline, businesses can now scale machine learning for a competitive advantage.

Optimize complex processes and target specific problem statements with artificial intelligence. Reliability engineers and optimization teams can build no-code AI models of their problem statements within minutes, receiving critical insights to help reduce costs, unleash hidden value or improve sustainability. OPUS uncovers unexpected correlations and contributing factors that traditional data analysis can easily overlook, with a unique approach which holistically analyses all available data across your entire facility or plant.

Improve asset reliability, reduce maintenance expenditure and stop unplanned shut-downs with AI insights. Businesses can easily implement predictive maintenance, using insights generated by AI models, pinpointing the root cause of the future failure. With these predictive insights, businesses can accurately order spares and schedule personnel, and reduce the cost spent on reactive and preventative maintenance.

Integrate and connect disparate systems and infrastructure into one platform for improved remote operations. Increase the efficiency and accuracy of your remote operations with a reliable platform that has up-to-the-minute data connectivity. Get a more accurate picture of your entire operations with our Web-SCADA solution.