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XVision gets € 1 million in a new round of funding

In 2022, it consolidates its presence in Western Europe and aims for the USA

XVision, the medical platform based on artificial intelligence algorithms that develop products to support radiologists in the analysis and interpretation of medical images, gets one million euros in a round of seed funding, with the contribution of bValue as Lead Investor and seven more Romanian investors: GapMinder, RocaX, Cleverage, Growceanu, Cristian Pop as angel investor and Poland: ResQMed and Marek Dziubinski.

This is the second round of financing obtained by XVision. The company has attracted a total of 1.5 million euros so far.

The amount will be directed to expanding the current team of ​​business development, AI, software development, and imaging specialists, to expanding the company to Western Europe, followed by the expansion to the United States, starting in 2023. The platform is operational in over 60 private hospitals and clinics and in three other European countries: Hungary, Slovakia, and Poland.

XVision is a MedTech company founded in 2018 by a multidisciplinary team from Timișoara, formed of Ștefan Iarca – CEO, Cristian Avramescu – CTO, Bogdan Bercean – Head of AI and Andrei Tenescu – Head of DevOps, who share a great passion for artificial intelligence and optimizing medical processes.

Since 2019, XVision has been Techcelerator alumni, the first accelerator in Romania that allocates funds for the development of companies in the acceleration phase, aiming for Romanian technology startups. Using its acceleration program, Techcelerator has invested and contributed both to the consolidation of XVision’s business processes, as well as to the support and expansion of the company.  

“This round is extremely important from a strategic point of view. XVision is at a point where the product has proven its practicality, so it’s time to start expanding beyond Central and Eastern Europe, an area we are familiar with. Thus, we will use the funds both to accelerate our access to Western European markets, as well as to develop existing and new products”, said Ștefan Iarca, Co-founder & CEO of XVision.

The company aims to become a complex solution for medical imaging, by adding new products to the existing portfolio, which would preserve the current differentiator: the complexity of the solution developed and its accuracy.

After about two years of testing and development, two products resulted: a software program dedicated to chest X-rays and another created for faster and more accurate analysis of chest CT scans (computed tomography). The research conducted by XVision has shown that in recent years there has been an increase in the number and complexity of medical images taken. 

As technology is becoming increasingly prevalent, the demand for complex images such as CT and MRI is constantly growing, but they are also more difficult to interpret. Moreover, the number of radiologists trained to analyze and interpret such medical images has stagnated in recent years, both in Romania and globally.

In addition, the internal studies run by the company show that Xvision helps save 25% of the time it takes to analyze a chest X-ray and up to 30% of the time it takes to analyze lung CT scans, which leads to higher efficiency in the correct diagnosis of some important diseases

XVision is now the first Artificial Intelligence software implemented by a chain of private clinics – Regina Maria – is used internationally in over 60 clinics and hospitals, and analyzes over 26,000 chest X-rays and 10,000 lung CTs per month.

About XVision

XVision is a MedTech startup founded in 2018 by a multidisciplinary team from Timișoara, who share a great passion for artificial intelligence and optimizing medical processes. XVision uses artificial intelligence algorithms to analyze medical images, to assist radiologists in the diagnostic process. Utilizing the platform developed by XVision, medical imaging benefits from the technological advantage provided by artificial intelligence, and doctors enjoy a faster and more efficient analysis.

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