Data Science Consulting

The gradual integration of your own data sensors from web, mobile and IoT applications as well as the parallel connection of third-party data sources help you to implement learning agents with machine and deep learning algorithms.

Supervised, unsupervised and reinforcement learning methods enable you, predictively and automatically, to maintain your products, your means of production and the affected business processes. Our P.E.A.S. (Performance - Environment - Actuators - Sensors) Framework is the basis for the productive design of AI applications. Together with you, we define and implement which business objective the agent should achieve (performance), in which environment this can be achieved (environment), which action option is required in a dynamic environment (actuators) and which data is required for this (sensors).

Interactive User Experience Nutzererlebnisse 

Understanding objects and their properties in photographs is a domain of Artificial Intelligence. Smartphone users generate billions of photos per day around the world, representing your brand in milieus and specific contexts. Applications such as Google Lens already recognize the objects in these photos and automatically enrich them with search engine information, for example.

The automated evaluation of the context in which your brand is captured opens up enormous potential for your brand and customer development. In addition, the real-time positioning of your brand in user-generated content becomes even more important. As a result, this symbiosis of your own brand content and user-generated content influences your brand strategy and thus the positive user experience of your customers.