Data science for the physical world
Turn your data into useful information and working solutions. We make it happen with mathematics, statistics, machine learning, and software engineering.
Data connects the physical and digital worlds
Data is the language at the interface between the physical and digital worlds. Interpreting that language correctly is crucial for turning data into valuable information and justifiable decisions.
The Digisalix team has decades of experience critically analysing many types of data: sensor feeds from industrial manufacturing processes, camera and LiDAR data in the automotive industry, fault recordings from moving machinery, and scanned documents, to name a few.
Industrial data presents a particular challenge. LLM agents are making digital work faster and easier to replicate, while industrial processes, such as mobile work machines and manufacturing, remain connected to a physical world that operates at its own pace. The data these processes produce can be scarce, difficult to replicate, and rarely public.
That data can become the real bottleneck. For companies that build the right software around it, it can also become a real advantage.
Got data going to waste?
Tell us what you’re sitting on. The first conversation costs nothing.
We find the value in your data
Insight, prediction, and automation
- Find the information that matters We interpret data to determine what useful information it actually contains, and combine the results with the needs of the application. Sometimes that information alone can be enough to save millions.
- Model and tune processes and machines We turn information into models that supervise and tune processes and machines. Combining statistics with physics often provides the best results.
- Forecast what comes next We create forecasting and predictive models for decision-making using statistical modelling and machine learning. Knowing the future would be an actual superpower. Estimating it, together with the known caveats, is a close second best.
- Make complex data accessible to software We use deep learning models to interpret text, images, video, audio, and other sensor data. These are often the first steps required to make the whole system accessible to computer programs and automation.