Everything we do focuses on one question:
How do we make complex technologies usable for SMEs
— safe, effective and people-centered?
Our research focuses on specific applications — not on buzzwords.
We are researching how AI models not only generate texts, but also understand, evaluate and automatically initiate business processes and comprehensively assist the user.
A particular focus is on data protection, the secure use of sensitive information and the legal structure in accordance with the EU AI Act.
Our goal: Despite strict data protection requirements, the functionality of AI assistants should not suffer — it is precisely this that creates the best work results in a secure environment.
Containerized architectures should enable us to research scalable, secure and flexible solutions that can be operated locally, in the cloud, or in a hybrid way.
A central research goal is to make containerized AI applications in private cloud environments on shared hardware compliant and securely operable.
In doing so, we lower the barriers to entry for AI technology in SMEs — without sacrificing control or IT sovereignty.
We are convinced that the future of process modelling and automation combined with AI will also take place in the metaverse and in immersive digital spaces.
That is why we are already researching how interactive, visually tangible processes and smart assistance systems can be integrated into AR/VR worlds — for training, simulations and collaborative optimization.
Our research has a clear goal: making automation applicable to everyone.
To do this, we are researching radical simplifications and intuitive interfaces through low-code and no-code platforms — supported by AI, which understands what is meant instead of just processing rules.
In addition to technical development, we are also constantly researching the economic success factors of new technologies.
In particular, this includes:
Market and target group acceptance of new tools
Differences in requirements by sector and company size
The actual needs of employees and managers
Because no matter how good a technology is, it remains ineffective if it is not accepted, understood and used.
That is why we combine technological research with real market research — for solutions that are not only possible but also successful.
For us, research is much more than theory:
Together with our customers, we develop practical solutions that make future-oriented technologies such as AI and Metaverse comprehensively usable.
Below, we will show you our structured project process, which ensures that innovation is always based on solid research, proven methods and entrepreneurial added value.
We define clear research goals and determine the practical benefits for our medium-sized customers. At the same time, we examine the current state of the art, record organizational requirements and take data protection and legal aspects into account from the outset.
Based on these analyses, we develop initial prototypes with which we specifically test feasibility, performance and safety. Through these proof-of-concept approaches, we gain early feedback in order to optimally adapt our AI applications to the metaverse.
We involve pilot customers, internal teams and subject matter experts in the test phase to collect targeted feedback. For example, we use KPIs to measure both the efficiency of our AI models and acceptance to ensure that our solutions offer real added value to users.
Based on these findings, we optimize our AI models and expand the metaverse scenarios so that they work smoothly in different environments — whether cloud-based or on-premise. In doing so, we integrate security mechanisms and ensure that all data protection requirements are met.
Finally, we document all results, methods and best practices in a comprehensible form. At the same time, we create business and financing plans to clearly demonstrate the added value of our research. In this way, we create a solid basis for seamless transfer into everyday business life.
