Contact Us - Supersight

Built on Scientific Excellence

The company's origins trace back to a research project conducted while the founding team was working at Elisa Corporation, a leading mobile network operator, investigating how 5G technology would transform the use of mobile data. It was during this work 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 recognised 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, research institutions, and international education programmes. Our AI models have been developed using the LUMI supercomputer, one of Europe's most powerful computing infrastructures. Together with the University of Helsinki, we have conducted research into privacy-preserving people flow analytics and the utilisation of built environments. We are expanding our collaboration with the Technical University of Munich (TUM), one of Europe's leading engineering universities, to explore new applications of privacy-first edge AI in intelligent environments and public spaces.

Supersight is also an Associate Partner of the Erasmus Mundus Joint Master's Degree Programme in Engineering of Data-intensive Intelligent Software Systems (EDISS), one of Europe's leading international master's programmes in software engineering and artificial intelligence. Through this collaboration, a master's thesis was completed on mobile AI inference and edge computing technologies, contributing to the evaluation of privacy-preserving computer vision workloads on consumer smartphone hardware and supporting the development of Supersight's edge AI platform.

In 2026, Supersight entered into a strategic partnership with Haaga-Helia University of Applied Sciences to support research, teaching, and innovation around real-world AI infrastructure, edge computing, and computer vision systems. Through this collaboration, students and researchers gain hands-on experience with production-grade AI deployments in operational environments.

These collaborations enable Supersight to combine academic research, industrial deployment experience, and next-generation engineering talent in the development of privacy-first AI systems. They also support our mission to build energy-efficient AI solutions that reduce reliance on cloud infrastructure and new hardware by bringing intelligence directly to the edge.

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.

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.

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.

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.