Fimmic, a Finnish medtech company developing Deep Learning AI solutions for digital medical microscopy, announced today that it has closed a €5M investment round to accelerate scaling of its WebMicroscope® AI Cloud for tissue diagnostics.

Led by new investor Ascend Capital Partners, the round brings the Company’s total raised funds in 2017 to €6.6M. Existing investors, including ACME Investments and STO-Rahoitus, also participated this round. 

Fimmic’s WebMicroscope is the first commercial platform that supports pathologists and medical researchers in tissue diagnostics through deep learning AI-based image analysis. 

WebMicroscope aims to improve the speed and accuracy of diagnosis which translates into more precise and personalized patient care. Fimmic’s WebMicroscope was recently nominated as the winner of the Innovation Award for Artificial Intelligence-based Digital Pathology Solution by Frost & Sullivan. 

“Our AI algorithms have been successfully used in various applications ranging from cancer research to drug development projects on Parkinson’s disease and liver diseases,” says Kaisa Helminen, CEO of Fimmic. “The results are extremely promising and our technology has received great interest from various industries and application areas. With this investment we are now able to grow the team, expand our marketing actions and launch our local activities in the US market,” she concludes.

“Artificial Intelligence (AI) holds great potential in several fields of medicine, including tissue diagnostics,” says Monita Mo, CEO of Ascend Capital Partners. “We were impressed about the expertise in the Fimmic team and their proven track record in executing development plans for a commercial product. We are excited to offer our experience and contact network to support Fimmic in their global expansion.” 

Fimmic, founded in 2013, is a spin-off company from the Finnish Institute for Molecular Medicine at the University of Helsinki. The next-generation WebMicroscope AI Platform was launched in spring 2017 and has since been used in a wide range of image analysis applications globally.

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