We drive intelligent innovation. For a better tomorrow. We are Ainovate.


Responsible AI for your needs.

We are convinced that data-driven applications fundamentally improve processes. Our strategies and models are always based on the principle that data should be used securely and conscientiously. In this way, we develop customized AI applications that position companies for the future and drive innovation.







Our values

We keep our values high and your forecast errors low.

Our values reflect who we are and what we want to achieve as a company. With our mission in mind, we are not only continuously working on exciting projects, but also on ourselves. Through trust, authenticity and transparency, both internally and externally, we create an open corporate culture that invites development and creativity. Through our work, we strive to be a role model that embodies how global challenges can be overcome sustainably with data science and artificial intelligence. We are proud to represent these values as a company and to make a meaningful contribution to a future worth living.


The human being in the center.

We are aware that artificial intelligence is changing our world. That is why we are actively committed to ensuring that AI applications are based on ethical principles that put people at the center. AI can only be responsible if it is based on clear ethical guidelines and human values. Education is an important part of our mission. We are therefore committed to educating the public about the opportunities and effects of AI technologies.


A definition of artificial intelligence is not yet available. Last but not least, it does not seem possible, as artificial intelligence is based on concepts that are not yet sufficiently well understood, such as the human brain, intelligence and human consciousness.
The greatest scientific advance to date in the field of AI is the transfer of the neuronal brain structure to the computer level. Thanks to the computing power available today, it is now possible to feed machines with large amounts of data and use neuron-based algorithms to solve problems that come surprisingly close to a fantasy movie (Chat GPT, Siri or Alexa).
What is still missing for machine consciousness and what constitutes it in the first place remains unclear. Although there are mind games such as the Turing Test, which tests the functionality of AI against a human, it cannot be a test of consciousness. The biggest criticism of the Turing Test is that it measures the susceptibility of a human to deception rather than the functionality of the machine.
In addition to classic prediction algorithms such as neural networks from the field of deep learning, reinforcement learning has established itself as another branch of AI with the availability of computing power. Reinforcement learning allows an actor (machine/robot) to learn desired actions in a measurable environment (game or reality). The quality of the actions or problems caused by wrong decisions are evaluated during the learning process using the so-called reward/penalty function. If the experiment is allowed to learn long enough with a well thought-out reward/penalty function, i.e. if the process is iterated and the actions that were punished or rewarded in which environment are saved, an AI can be trained. For example, board game algorithms or autonomous driving have been developed in this way.
Reinforcement learning and the drive for reward are seen by critics as a potential dystopia for AI, as it could show no mercy in a possible resource competition with humans in the event of careless or even uncontrolled training.
We cannot answer the question of whether machines are capable of imitating or acquiring human consciousness. If the theory that human consciousness and emotions arise through ad-hoc information processing and short-term predictions of environmental conditions is correct, a solution to this question may not be too far off. This is precisely the point where machines are already superior to the human brain due to their immense computing capacity. In particular, the AI field of predictive modeling has undergone advanced research, its areas of application are limitless and, thanks to Ainovate, it is more accessible to you than ever before.

Our Team

The drive behind our mission.

Motivated by big visions, pioneering spirit and passion – every day, with every line of code and every data set from which innovation emerges.

Maximilian Schneider

Managing Director

Dr. Kay Stankov

Head Of Data Science & AI

Franziska Pilz

Administration & Project Management

Leonard Grebe

Data Science & AI

Johannes Kleinschmidt

Intern Data Science

Prof. Dr. Julia Zwank

Subject Matter Expert

Lis Qosja


Dr. Philip Neudert

Subject Matter Expert

Carlos Lopez Granado

Data Science & AI

Elena Stahl

Communication Manager

Prof. Dr. Jonas Vogt

Subject Matter Expert

Jendrik Worlitz

Event Manager

Hannah Zimmer

Marketing Manager


Would you like to find out more about us and our mission? We cordially invite you to a non-binding discussion and look forward to exchanging ideas with you.