The mastermind and main driving force behind Robovision. With a background as applied physics engineer (specialized in image processing), he built up a strong reputation building custom machine vision and robotics solutions in the first years of our existence. Our Robovision AI software is what it is today due in large part to Jonathan building machine vision applications the “hard way”. Today, he passionately leads our company to new heights everyday.
When Tim joined the company, Robovision became Robovision AI. He obtained a PhD in Computer Science Engineering at Ghent University completing his doctoral thesis in 2013 on machine learning at the Reservoir Lab. The chief architect of Robovision and with a deep understanding of both data science and software development, he enthusiastically leads the company on a technical level.
BUILDING THE FUTURE TOGETHER
Our Team members
We’re a team of physicists, mathematicians, engineers, creatives, optimists and makers that are dedicated to our mission of simplifying AI. We value openness, radical candor, childlike enthusiasm and solution driven attitudes.
A step by step road to scalable AI solutions
Robot performance before Robovision (2012)
We started building the foundation of Robovision AI in 2013 when working on two projects in the package handling and agriculture industries.
Adaptation required coding
Even though classical machine vision approaches were powerful enough, it took a machine vision expert more than a day to program and tune a new variety. Furthermore, every new application required a new development cycle.
Natural product = large variance
The applications we had to build had a larger product variance than previous challenges. We started building a data driven framework that could be re-used independent of the application and simplify the process for rapid adaptability to new varieties.
Teach machines by showing examples
Birth of RVAI 1.0 – An AI platform where an operator with basic IT skills is able to reprogram the machines without any machine vision or AI expertise. Simple tooling to indicate where the robots to grasp or pick something from the conveyor belt.
Same Robovision software, different application
Instead of building custom solutions for each, we opted to build tooling that we could apply to both challenges. For us there is no difference in how we apply our software, it is the data that makes it the application.
From training to production environments
Today we apply the same mindset and continue to seek ways to simplify building and scaling Machine Vision AI solutions. We are passionate about democratizing AI and enabling people and business across the globe with the transformative power of these technologies.