Meet our Team
Johannes Kunz
Core Competences
- AI Strategy
- Machine Learning
- Visual Data Processing
- Natural Language Processing
- AI Governance
White Papers
With 30 years of experience in management roles on C-Level and management consulting (as a partner in global firms and a freelancer), Johannes has the necessary background to fully understand your business. Additionally, information technology for him was always a key business enabler, so his work always included the questions: "How can IT serve our business better?" and: "How does IT offer us new business opportunities?"
It is no surprise that he has been at the forefront of helping or creating IT driven businesses during those years, ranging from SaaS services to business models that were only possible with IT at the core. And it is equally no surprise that he was using elements of Artificial Intelligence way before the mainstream was getting involved.
Johannes loves technology, but not for technology's sake. The combination of business background and IT curiosity gives him the unique ability to help you answer the above two questions.
But it doen't stop there. Having been in startup situations regularly over the course of his career, he has never shied away from doing the hard work of actually creating solutions, from defining the architecture and developing and testing code himself in most common languages. He is also familiar with most key frameworks currently used in machine learning and with most large language models.
Johannes holds Masters degrees in Business IT and Law from the University of Zurich, and a PhD in Economics from the University of St. Gallen. He has worked on four continents and is fluently trilingual.
Sample Projects
Interaction Evaluation
SaaS project platform: the objective was to evaluate dialogue quality using an AI model to ensure timely intervention and customer care.
Electrical Switch Monitor
Public transportation: using AI-driven vision to monitor old-fashioned electrical relays and also to evaluate potential failures for predictive maintenance.
Hydropower Plant Control
Hydropower plants: create a control and monitoring solution for all plant operations, including predictive maintenance and intrusion monitoring.
IT Operations Automation
Financial Services: develop strategy and business cases to introduce automation and AI into the IT operations environment.
Customer Interaction Evaluation
For a project management SaaS solution where customers were matched with freelancers, a custom AI solution was established with the purpose to improve experiences for all parties. Key purposes were to create an early warning system to help customer service intervene in case of issues:
- Identification of unusual patterns (delays indicating inaction, intense exchanges);
- Flagging of language transgressions on both sides (use of inappropriate language, aggression);
- Matching of final ratings with evaluation of flow and dialogue quality to foster a more honest rating culture;
- Language style matching to improve future matching of freelancers to clients;
The solution was implemented using Python on a LAMP stack, with self-developed machine learning libraries.
Electrical Switch Monitoring
For a public transportation network, the objective was to optimize the monitoring of their legacy electrical switchboards. These decade-old items that are often located in very remote areas are prone to failures and tracking of errors was not possible. The objective was to enable real-time tracking and the recognition of upcoming failures from changed switching behavior. The key elements were:
- Development of specific hardware configuration with custom housings (3D printed) to mount instead of regular switchboard covers;
- Camera control and initial image generation on Raspberry Pi integrated in housing;
- Initial scan of switch layout and labels;
- Identification of switching operations and registration of new positions;
- Identification of irregular switching patterns (delays, other irregularities) to indicate upcoming failures for predictive maintenance;
- Update of central database and cloud solution with last state and observed switching patterns;
The solution was implemented using Python on Raspberry Pi devices, backbone and cloud processing were done using a LAMP stack, using PyTorch, TensorFlow and OpenCV.