Who we are
We are a software consultancy specialized on machine learning, data analytics, and generative AI. Our mission is to help our clients leverage their data and make better decisions. With an academic background in machine learning, we focus on complex projects that create sustainable value.
Data Engineering
Data Engineering is the often underestimated foundation of any data science project. By optimizing data ingestion and storage, we get the right data to the right places.
Data Analytics
The right analytics approach is central to the success of any use case. We offer expertise in state-of-the-art algorithms for (semi-)supervised and unsupervised machine learning.
Generative AI
Generative AI technology is rapidly evolving. From model fine-tuning to prompt engineering to agent ensembles, we stay at the forefront of current developments - so our clients don't have to.
Knowledge Retrieval
By leveraging advanced strategies, such as knowledge graphs, query augmentation, hybrid search, or multi-layer retrieval, we discover the hidden treasures in even the most complex knowledge bases.
Decision Support Systems
Any data-driven insight is only as good as the decision it leads to. We advise our clients on how to integrate data science into their business processes.
AI Strategy
Machine learning and generative AI open the door to a vast range of novel business cases. We support our clients in navigating these technologies and using them to expand their business model.
Why us?
1
The 10 year principle
We believe that creating long-term value for our clients is the most sustainable business model. So instead of delivering half-baked solutions to secure follow-up projects, we focus on high-impact co-creation from day one. To show that we are serious about this, we offer 10 years of free support with every delivered project.
2
Ambition
Solving complex problems is what drives us. Especially creating software that works for the next 10 years and is easily maintainable. This is why we spend a lot of time understanding the use case and mapping out possible future extensions. We then develop a landscape of modular abstractions, which becomes the backbone of any software we build.
3
Scientific mindset
When developing a solution, we follow the scientific method: Together with all stakeholders we identify hypotheses and their interdependencies, which are then continually tracked, evaluated, and adjusted. To facilitate this, we build a measurement framework around every solution. The result is thoroughly optimized software with transparent performance.