An industrial operation has many moving parts. However, the traditional way of monitoring industrial operations is limited.

Many industrial businesses are collecting data from their operational systems but don't know what to do with it. They’re they’re driving blind by not making data-driven decisions. Failure to draw insights from operational data limits the understanding of the cause-effect relationships that govern productivity and downtime.

We use data to to bring systematic problems to light, so that operational staff can make operational improvements. We’ve developed custom machine learning models to extract wisdom by fusing multiple sources of operational data. These models enrich the raw data by fusing information originating from different data modalities. With the combination of each source of (e.g. vision + tabular data) to provide more value than each individual source of data on its own.

We apply machine learning to find meaningful patterns that are embedded within your data. We develop tailored algorithms are developed to consume data from multiple sources (e.g. machines, enterprise systems, vehicles, or robots), and distill the gist of your operations numerically.

Our machine learning solutions improve visibility of complex industrial workflows by condensing raw process data into meaningful representations.

From this numerical representation, we can draw inferences to illuminate hidden patterns in your operational workflows that influence business outcomes; wait times (productivity), resource utilisation (return on assets). Beyond that, our machine learning can be integrated into your products to differentiate your end-products capabilities from those of competitors.

We treat all pieces of software, sensors, equipment, robots as producers and consumers of information. Our data process automation solutions are “bolt-on” enablement technologies that bridge automation islands (e.g. different tools, vendors) to make your data more valuable and actionable.

Want to learn how we operate? Take a look at the stages of our process here.

Final Thoughts

There's a there's an economic imperative to make industrial systems smarter; without properly leveraging data, industry is driving blind. Streaming data provides visibility and highlights areas that need attention.