About Us

We are an innovative IT company based in Graz, Austria and focus on image data management and automated image analysis applications.

We work with customers from Life Sciences, Healthcare and Industry for whom we are developing the IKOSA® platform. This platform consists of the IKOSA PORTAL, a multi-user system to store, manage and annotate big image data, and IKOSA PRISMA, which offers deep learning based modules for automated image analysis. Existing modules can be used on-demand, or individual customer-specific modules are tailored with IKOSA PRIME.

Company History

​After several years in research at Austrian and international universities, physicist and entrepreneur DDr. Michael Mayrhofer-Reinhartshuber and computer scientist Dr. Philipp Kainz founded KML VISION in Graz, Austria in 2016. The team decided to use their passion for leading-edge technologies like computer vision, artificial intelligence and cloud computing to provide solutions for automated image analysis to companies and universities. In the beginning, the team worked on individual software projects regarding these topics for several customers in academia and industry. Based on this experience, the idea of IKOSA® was born in 2017.

Since then KML VISION is realizing IKOSA®, a multi-user platform for images having various origins, formats and resolutions together with an intuitive utilization of advanced tools for automated analysis to extract accurate, validated information. In this way the team of KML VISION is on the track to fulfill their mission of offering easy access to modern, high quality image data management and fast, automated image analysis applications, in order to eliminate repetitive and tedious manual tasks in the best possible way.

Dr. Philipp Kainz, MSc

Founder, CEO

​​Philipp Kainz studied Health Care Engineering and eHealth at Graz University of Applied Sciences. In 2016, he received his PhD from the Medical University of Graz and did his PostDoc on Deep Learning in Medical Image Analysis with the Ludwig Boltzmann Institute for Clinical-Forensic Imaging in Graz. His main motivation and responsibilities are accelerating the transfer from technological breakthroughs to business cases and creating value by providing state-of-the-art technology based on Artificial Intelligence.


Founder, ​DIRECTOR ​SALES & Business Development

Michael Mayrhofer-Reinhartshuber studied Technical Physics at Graz University of Technology. In 2014, he received his PhD in Experimental Physics and in 2015, he received his PhD in Medical Sciences from ​the Medical University of Graz. After collecting international experience in Australia and Spain, he worked for a social media start-up and founded his first company in Graz. His main motivation is to let Life Sciences benefit from recent achievements in information technology in order to significantly contribute to a faster and more effective way of research, development and production.


Andreas Esterer

Software Developer

Giannenta Milio

Sales & Marketing

Jakob Hatzl

Director Software Engineering

Johanna Egger

Software Developer

Michael Weißensteiner

Computer Vision / Machine Learning Engineer

Oscar Palomo

Software Developer

Polina Vinogradova

UI/UX Designer

Thomas Ebner

Computer Vision / Machine Learning Engineer


At KML VISION, you will be working on exciting projects in an open and trustful environment. The team consists of highly motivated people who strive to create the best possible result for our customers.

​​​We are focusing on reducing the time until new achievements in digital image analysis can be used by anyone in an intuitive way.

We are currently looking for the following positions:

​Interested? Submit your CV to career@kmlvision.com.

If there is no open position for you at the moment, we are also happy to receive your unsolicited application.


We are looking for an authentic character with excellent communication skills and the willingness to act internationally.

38,5 h // fulltime


We are looking for a creative person who loves the challenge of presenting a high-tech topic in multiple media.

20 h // part-time

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