Das Vypno-Team
© Vypno

Vypno: “In Five Years, We Would Like to Be a Leader in Generative AI and Synthetic Data.”

Machine learning only functions with a sufficient amount of data. But obtaining that poses a real challenge for many companies: it is too costly and time consuming. Vypno’s software solution aims to make it faster and more affordable. The Munich startup aims to feed deep learning algorithms with its virtually generated image data. An interview with the founding team.

Who are you and what do you do? Please introduce yourselves!

Our founding team at Vypno includes Maximilian Jakasovic, 33, CEO, who already discovered his entrepreneurial spirit during his bachelor studies in computer science when he founded his first company, Appetise GmbH.

While studying computer science, he met one of the Vypno co-founders, Alejandro Rueda, 32, who before going to university completed professional training as a film and computer animator, which gave him initial experience in the working world. During his studies, he specialized in image processing using machine learning. He is responsible for computer vision and deep learning in our team and also supports us with his expertise in design.

Another member and co-founder of Vypno is Yang Li, 33, who impresses with more than ten years of experience in the fields of scientific and engineering simulation, where she worked both as a developer and manager. Yang studied mathematics and has a PhD in computer science. With her comprehensive knowledge of many years, she is responsible for team management and product development. Maximilian and Yang met while Yang was working as a degree thesis supervisor, and during that time she advised Maxi on his master’s thesis.

The last member of our team is Nitesh Narayan, 35, who also has a PhD in computer science. With his wealth of experience in all facets of software development, he supports our team in designing and developing software applications.

Large amounts of data generated quickly for deep learning

What problem does your startup solve?

One of the biggest problems in machine learning is that there is often too little or unsuitable data available for deep learning and that manual acquisition and editing are very expensive and time consuming. Our technology makes it possible to quickly generate and identify image data in seconds, which significantly reduces the amount of work and costs involved.

But that’s nothing out of the box!

The combination of generative AI with synthetic data in the manner it is used in our technology is unique and gives our clients significant cost savings.

Was there a point when you nearly failed?

Because we are a very international team, it’s most particularly the residence and work permits for our individual members that constantly cause difficulties.

Where would you like to be in one year, and where in five years?

In one year, we would like to be fully financed, and in five years, we would like to be one of the leaders in generative AI and synthetic data.

Munich, the German Silicon Valley

What do you think about Munich as a startup location?

Munich as the German Silicon Valley provides excellent opportunities for young companies. Thanks to the Garching research campus, we constantly encounter new, innovative ideas, and cooperation with our partners allows us to interact with a broad spectrum of advisors and companies.

Quick exit or staying power?

We’re not thinking about an exit at the moment. The top priority for us is developing a product that lives up to our customers’ high standards.