Takes Synthetic Data Generation to the Next Level has developed a synthetic data platform that generates 100% privacy-safe data, enabling data sharing and collaborations that were previously impossible due to privacy protection

Utrecht, The Netherlands – October 2022 –, a Technical University Delft spin-off, has developed a synthetic data platform that generates anonymized data from real data that can’t be re-engineered to the original privacy-sensitive data. The platform creates synthetic data that looks and behaves just like the underlying real data, making the data suitable for valuable data analysis previously restricted due to privacy protection.

“I’m thrilled about this joint initiative with Delft Enterprises, Technical University Delft, and my fellow co-founders and the funding we get because opens up collaborations and opportunities that were impossible until now,” says Iman Alipour, co-founder and CEO. “Think of Healthcare where general practitioners have valuable patient data that can contribute to new medicine development. Privacy laws prohibit processing such data, but generates synthetic data from actual patient data that can’t be traced back to an individual patient. While preserving the value of the data that helps develop better medicines.”

The global synthetic data generation market accumulated USD 123.3 million in 2021, and market research company Grand View Research expects an annual growth rate of 34.8% from 2022 to 2030, leading to a revenue forecast of USD 1.79 billion by 2030. Technological research company Gartner predicts that by 2025 synthetic data will reduce personal customer data collection, avoiding 70% of privacy violations sanctions.

“This clearly shows the importance and potential of synthetic data,” continues Iman Alipour, “Simply because data is the lifeblood of digital business. But at, we even go further as we believe protecting customers, consumers, citizens, and patients is just as important. And therefore, we focus on Healthcare, Finance, Government, and the Software Industry.”

The platform is patented and applies mathematical principles like differential privacy to generate privacy-safe synthetic data. “Besides secure data, also creates better data than real data,” says Lydia Chen, Technical University Delft associate professor and Technical Advisor at “The ai extension in our company name has true meaning. Because through machine learning, can also generate synthetic data that complements incomplete real data. is like a data tap that turns real data into useful and safe data.”

“Furthermore, is unique because it pushes the boundaries of machine learning into federated learning,” adds Lydia Chen. “Through federated learning, generates more secure and accurate data because can create synthetic data from different sources without bringing them physically together.” is a spin-off from Delft University of Technology and gets full support from Delft Enterprises. “ is a great example of science meeting business and society,” says Lucas van Vliet, dean of the Electrical Engineering, Mathematics, and Computer Science (EEMCS) faculty at TU Delft. “Together with, we have created a tech-driven solution that addresses the social challenge of dealing with privacy-sensitive data.”

Delft Enterprises supports in commercializing the synthetic data solution by providing startup funding and engaging business experts and investors. “We saw the potential of Lydia Chen’s research and therefore linked her to Iman Alipour, who has extensive entrepreneurial experience in data-driven companies,” says Paul Althuis, director of Delft Enterprises. “In doing so, we make sure that that this promising technology can have a real impact in society.”

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