Built on Scientific Excellence

The company's origins date back to a research project four years ago, when the founding team was working at Elisa Corporation, a leading mobile network operator, to investigate the changes that 5G technology would bring to the use of mobile data. It was then that the idea of AI edge computing devices was born.

Supersight combines real-world engineering with cutting-edge scientific expertise.

Our team includes researchers and engineers whose work has been published in internationally recognized scientific journals, including publications within the Nature portfolio and leading peer-reviewed artificial intelligence and computer vision journals. This research background helps us develop privacy-preserving AI systems that are both scientifically rigorous and practical for large-scale deployment.

Beyond internal expertise, Supersight actively collaborates with leading universities and research institutions. Our AI model has been developed on the European fastest supercomputer. Together with the University of Helsinki, we have conducted research into privacy-preserving people flow analytics and the utilisation of built environments. We are also expanding our research collaboration with the Technical University of Munich (TUM) to explore new applications of privacy-first edge AI in intelligent environments and public spaces.

Dr. Matteo Allaix

Co-founder and CTO

Dr. Matteo Allaix leads Supersight’s technology and research activities. His work focuses on privacy-preserving protocols, distributed systems, secure data storage, and trustworthy computing. His research experience forms a key foundation of Supersight’s privacy-first architecture.

Oksana Havryliuk

Co-founder

Oksana Havryliuk has published research in machine learning and data science, including work published in Scientific Reports, part of the Nature Portfolio. Her experience has contributed to Supersight’s data-driven approach to real-world AI systems.

Muhammad Shaher Yar

AI Research Contributor

Muhammad Shaher Yar played an important role in building the foundations of Supersight’s AI technology. His research has been published in Nature Cardiovascular Research, reflecting a strong background in advanced machine learning and applied artificial intelligence.

 

Saad Abdullah

Machine Learning Engineer

Saad Abdullah is a member of Supersight's technology team, contributing to the development of computer vision models and edge AI systems. His research has been published in peer-reviewed international journals, including recent work on advanced deep learning methods for visual recognition and image analysis. His expertise supports the continuous improvement of Supersight's AI models, accuracy, and real-world deployment capabilities.

Research in Practice

At Supersight, scientific advances are translated into deployable technologies that enable privacy-first, energy-efficient, and scalable AI systems operating directly in the physical world.

Our research interests include:

• Privacy-preserving artificial intelligence
• Edge AI and distributed computing
• Intelligent environments and building intelligence
• Human mobility and people flow analytics
• Sustainable and resource-efficient digital infrastructure
• Future embodied and real-world AI systems

By combining scientific research with large-scale real-world deployments, Supersight aims to bridge the gap between academic innovation and practical intelligent infrastructure.