Our team utilizes a deep type of neural network called Convolutional Neural Network for image processing domains. This makes sure that visual input data is efficiently processed. This aligns with graphic intense business needs such as Simulation processing. Our systems can then improve their own.

By integrating Deep Machine Learning we facilitate powerful problem solving. We use powerful learn-by-example techniques that extract meaningful features from data to facilitate optimizations on the pre- and post-processing side of your business interfaces. This also ensures better use of computer resources. Our team better integrates AI techniques in your overall product lifecycle management. In this way, we allow connecting neural networks / Machine Learning models with new upcoming product use cases, which is a must for smart products. Such an enhanced engineering process is also referred to as AI adoption.

But why is Deep Learning suitable for your business? A CNN improves its own performance in optimizing business-specific outputs on the basis of its own previous experience. They do this by building upon Neural networks which are highly adaptable to data and learn any hidden mathematical functions between the data and the outcome.