Applied Machine Intelligence

Machine intelligence raises deep scientific, engineering and societal challenges. We focus on identifying and defining solutions to these challenges.

Our research group

Our aim is to look beyond the pure algorithmic aspects of machine learning and to develop machine intelligence applications that start transforming people’s lives with technology. We focus our research on areas where the deep expertise of our group members allows us to develop solutions with measurable real-world impact.

Service portfolio

Our research is focused on getting machine learning into production systems. and to do so in a responsible and sustainable way. We operate at the forefront of Machine Learning Engineering (MLE). Based on our expertise, we work together with you on scaling, testing, data modelling and other major MLE specific aspects such as operations and maintenance. When we build these applications, we measure success based on business relevant metrics. Members of our team have been responsible for launching some of the largest Natural Language Processing applications to date in the U.S banking sector, and their work has been covered by NBC Universal, SRF, The Economist and the Handelszeitung. 

Launching Smart Applications 

We cooperate with industry, academic research groups and non-profit organisations to build applications that can offer novel functionalities or expand beyond existing capabilities based on machine learning. 

The following domains represent our current focus and are complemented by applications we developed in other ML areas such as computer vision and inference.  

Smart Text Applications 

Smart text applications are aimed at making the interaction with information in textual form more efficient and rewarding. The applications range from the identification of key values in important documents, to automated curation, transformation and storage of documents in all forms. The systems we develop with our cooperation partners automate partial aspects and reduce processing time by up to 80%. They follow the principles of intelligence amplification (IA) and empower humans, instead of aiming for the pipe dream of an AI lawyer or AI doctor. We currently work with some of Switzerland’s leading start-ups in legal-tech and HR-tech on building smart text applications.  

Search & Recommendation Systems 

Search and recommendation systems are key areas where advances in Machine Learning have unlocked enormous potential. Search not only has the potential to increase the efficiency of information-rich workflows, but also to make users happier. Improving search in an e-commerce context can lead to better conversion rates and customer satisfaction. We support our cooperation partners in the realisation of search solutions and recommendation systems that unlock the potential of internal information and enable them to launch data market focused solutions. 

Accelerating Research for Social Good 

We apply the power of ML based automation and information extraction to accelerate and expand research in the social domain. Our work ranges from scaling the collection of required data on public and private sources, to the automated transformation, extraction and interpretation of information. We develop innovative tools for clinical intervention in psychology, for example to support burnout detection, and investigate how smart technologies can be applied to support diversity in job ads. Such projects allow us to support social institutions, non-profit organisations and public administration to benefit from innovation and to get the most out of the digital age. 

Research Cooperation 

We target different types of collaborations with partners from industry, public administration and academia to make innovation happen and do our part of pulling Switzerland into the future.  

Different forms of collaboration are possible: 

  • Third-party funded research cooperation based on public research programs 

  • Contract research where we consult, advise and run workshops 

  • Support and collaboration with start-ups 

  • Student projects / bachelor theses relating to MLE. 

We are happy to help you identify the best suited way to fund research cooperation.  


Machine Learning in Production 

Building production-grade, enterprise-ready systems that are based on machine learning comes with very specific requirements and challenges in terms of maintenance, testing, scaling and requirements engineering. We have extensive experience regarding these aspects and have been responsible for the design and launch of massive machine learning based systems in banking, manufacturing and e-commerce spaces. 

Augmented Intelligence 

Automated learning and data analysis play an increasing role in offering innovative services and products. We offer our know-how in various fields of artificial intelligence and examine how such technologies can be embedded in existing workflows. How can humans work most effectively with artificial intelligence? In what way can their respective skills complete one another? User-interface design, information modelling, explainability and trust are just a few examples of areas of interest for different sectors such as finance, legal or public administration. 

AI for Social Impact 

We design and develop innovative tools to support the resolution of social and community challenges using the new digital technologies. Our expertise lies in the field of innovative methods for the area of mental health, providing a new generation of tool support for health practitioners and thus working on the clinical intervention of the future. 

Fairness and Digital Ethics 

Digital ethics, with regards to machine learning, become increasingly relevant. If the training data is biased, this can have an impact on the resulting models and lead to unfair decisions being made by the system. We develop methods to measure fairness, in text data, and to apply digital methods to social and community problems.   

  • BurnoutWords
    In this project, detecting the burnout syndrome with the power of natural language processing allows to prepare for the future's digital methods in psychology.
  • Diversifier-NLP
    How job ads are written defines who is applying to them. Using inclusive language is necessary to attract diverse talents.
  • Virtual Research Assistant
    A virtual research assistant based on artificial intelligence (AI) and focused on medical insurance law allows lawyers to find relevant information up to ten times faster and more precisely than ever.


The easiest way to receive some advice or to get started with a research project is to reach out to us directly by e-mail. We are eager to interact with industry and non-profit organisations, and love working with and enabling SMEs and start-ups.