We provide industrial data solutions. Our solutions are structured in a staged process to enable you to extract wisdom from your operational data.

1. Data Discovery Process

We begin with a data discovery process to learn about the nature and quality of the data in your industrial organisation.

We perform a data quality check on excerpts of your data to identify key characteristics and gain an understanding of whether this data is suitable for analytics. This is because machine learning and analytics is constrained by the quality and volume of your data; the saying goes “garbage in, garbage out”.

This data discovery will enable you to determine a pathway towards predictive modeling.

2. Value Map

After data discovery, the next stage is the generation of a value map. We model the relationships between your production workflows across your value stream.

We can then dynamise this map by overlaying real-time information streaming from your applications and devices. This can incorporate heterogeneous data sources (systems, sensors, machines, or softwares). We treat all of these heterogeneous data sources (“nodes”) in an industrial enterprise as producers and consumers of information.

3. Predictive Modelling

Once your data is mapped out in an accessible format, we develop tailored analytical models to extract insights from your raw data. We train these models to find hidden patterns, and extract useful information from volumes of raw data.

4. Feedback Loop

We can then feed this newfound information back into your operation. Our "change vector" technology can provide adaptive guidance according to desired and actual operating conditions.

Industrial Data Solutions

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. We work with you as an extension of your team to extract wisdom from your operational processes.