Machine learning is becoming a new value creation method and success factor in the digitization of international corporations and SMEs. With AI, correlations can be understood, processes improved and upcoming problems solved with ease. It creates innovative possibilities for processing data and opens up prospects for new products and services – and not just for high-tech IT companies.
Whether in the field of automation of visual quality control, predictive maintenance, applications with complex data sets or object recognition to support maintenance tasks, we help our customers to use machine learning efficiently and to create real added value from their data.
With the help of AI, you get decision support based on complex data.
We offer automated visual quality control of components, process drift detection, predictive maintenance, monitoring and object tracking.
Benefit from the time savings that virtual assistance systems (e. g. through text and speech recognition algorithms for document filing) can bring.
Starting with a potential analysis of your use case, we advise you on the big questions about machine learning. Our experts explain the necessary steps for an effective ML architecture, the following data collection and analysis as well as model training.
Together with us, you can implement your ML use case yourself in just 3 days – from live rapid prototyping of your use case to the first ML-enabled product. Alternatively, we are happy to work out a proof of concept with you.
Every ML application is only as good as the data basis on which it is built. We work with you on the specific technical basics to extract the right data from your systems and machines. Our experts will be pleased to advise you on topics such as suitable sensor technology, sampling rates, data set generation, or statistical Design of Experiments (DoE).
Implementation of the entire use case from A to Z: from requirements, architecture, development and testing to training, integration, operational concept and scaling.
We also offer solutions for object recognition via smartphone for automated reordering in the field, speech recognition, mass deployments of ML models on mobile infrastructure and much more. We are ready to support you.
Of course, Machine Learning on the cloud offers many advantages, especially for model training and analysis models. But besides that, it also needs to be solved “on premise” sometimes. Google Edge ML, Azure IoT edge, Mender.io, SOTEC Edge Stack, custom IoT edge hardware development with ML-on-the-edge inference acceleration.
Any ML application is only as good as the data it is built on. Our experts will be happy to advise you on the use of the right tools/pipelines, on implementation and architecture issues, or set up training models together with you to predict future events from historical data.
This runs under the credo: Seeing is believing! With our three-day hands-on workshop, we introduce you to the basics of the technology and develop a functional prototype together. This approach brings light into the darkness and a clear idea in which direction the future project can go.