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Johannes Kunz
Grundlegende Kompetenzen
- KI-Strategie
- Machine Learning
- Visual Data Processing
- Natural Language Processing
- KI-Governance
White Papers
Mit 30 Jahren Erfahrung in Führungspositionen auf C-Level und in der Unternehmensberatung (als Partner in globalen Unternehmen und als Freiberufler) verfügt Johannes über den notwendigen Hintergrund, um Ihr Unternehmen in Gänze zu überblicken und zu verstehen. Darüber hinaus war die Informationstechnologie für ihn immer ein wichtiger Geschäftsbereich, sodass seine Arbeit stets die folgenden Fragen umfasste: “How can IT serve our business better?” and: “Wie eröffnet uns die IT neue Geschäftsmöglichkeiten?“
Es ist keine Überraschung, dass er in diesen Jahren eine Vorreiterrolle bei der Unterstützung oder Gründung von IT-gesteuerten Unternehmen gespielt hat, die von SaaS-Diensten bis hin zu Geschäftsmodellen reichten, die nur mit IT als Kernstück möglich waren. Und ebenso nutzte er Elemente der künstlichen Intelligenz schon lange bevor sie Mainstream wurden.
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 doesn’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 Master’s 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.
Referenzprojekte
Interaktionsbewertung
SaaS-Projektplattform: Das Ziel war es, die Dialogqualität mithilfe eines KI-Modells zu bewerten, um rechtzeitige Interventionen und Kundenbetreuung zu gewährleisten.
Elektrischer Schaltermonitor
Öffentliche Verkehrsmittel: Einsatz KI-gesteuerter Bildverarbeitung, um altmodische elektrische Relais zu überwachen und auch potenzielle Ausfälle für die vorausschauende Wartung zu bewerten.
Wasserkraftwerkssteuerung
Wasserkraftwerke: Erstellung einer Steuerungs- und Überwachungslösung für alle Anlagenoperationen, einschließlich vorausschauender Wartung und Eindringlingsüberwachung.
IT-Betriebsautomatisierung
Finanzdienstleistungen: Strategie und Business Cases entwickeln, um Automatisierung und KI in die IT-Betriebsumgebung einzuführen.
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.
Chatbot for Legal Environments
An AI-supported RAG-Chatbot developed for legal and administrative workflows. Designed to support caseworkers in navigating complex regulations – currently focused on German Social Welfare – the system provides fast, contextual access to relevant legal information and assists in decision-making for applications and case management. The modular architecture allows seamless expansion into additional legal domains and regulatory frameworks.
Mit Eliza reden
This is a faithful representation of the 1966 Eliza version created by Joseph Weizenbaum. It was reproduced by Anthony Hay in C++ based on the original 1965 code and updated by behavior transcripts of the final version.
Note: The paper version emulates Joseph Weizenbaum’s original 1966 ELIZA as it ran on the CTSS time-sharing system (IBM 7094) at MIT, accessed via an IBM Selectric-based hardcopy terminal. On CTSS the question mark served as the line-delete (line-kill) control character, so it could not appear in typed input — and the DOCTOR script accordingly produced no question marks. They are therefore suppressed here, on both sides of the conversation. The green “terminal” version enables question marks instead; it represents a glowing CRT display of a kind that did not exist for ELIZA in 1966 and evokes a later era of computing.
Play Chess like 1997 (Deep Blue Style)
Here’s our simulation of Deep Blue. You can play against Stockfish (able to run on a laptop today with similar strength compared to Deep Blue). Bonus: you can replay the legendary 1997 rematch where Deep Blue won against Garry Kasparov.