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Medtech startup See-Mode Technologies bags USD 7 million from SGInnovate, others

See-Mode claims to be first in developing software for automated analysis and reporting of vascular ultrasound scans, approved by the Singapore health authorities.

Founders of See-Mode Technology. Photo courtesy of SeeMode.

Singapore-based See-Mode Technologies on Thursday announced that it has raised USD 7 million in a Series A round led by MassMutual Ventures Southeast Asia. Blackbird Ventures, Cocoon Capital, SGInnovate, Entrepreneur First, and a group of angel investors also pitched in.

With the new funding, See-Mode wants to bring its AI-powered early stroke detection software into the Europe and US next year. It seeks to double the team size, especially for research and development, engineering, sales, and business development. The company is looking to partner with more research institutions globally to gather more scientific evidence.

See-Mode claims to be first in developing software for automated analysis and reporting of vascular ultrasound scans, called Augmented Vascular Analysis (AVA), which has been approved by the Singapore Health Science Authority (HSA) and is commercially available in hospitals. At present, See-Mode is pending regulatory approval for AVA in other regions, including Europe and the US.

“Tackling stroke is no small feat, and we are extremely lucky to be working with an outstanding group of clinicians from leading research institutions globally to further validate our products,” said co-founder Dr. Milad Mohammadzadeh.

See-Mode is adding more image interpretation and reporting capabilities to AVA and is expanding its capabilities to new clinical use cases. The company has been building other new products, to detect vulnerable plaque using machine learning, and to identify high-risk blood flow using computational modelling.

Founded in 2017 by Mohammadzadeh and Sadaf Monajemi, See-Mode aims to improve the analysis of routinely collected medical images such as ultrasound, CT, or MRI scans by using AI, computer vision, and computational modelling. It allows clinicians to obtain critical stroke risk factors that may not be accessible in current clinical practice and helps doctors to efficiently decide on the optimal treatment for patients, improving patient care and outcomes, without the need for additional tests.

Back in 2019, the company raised USD 1 million in a seed funding round, led by Cocoon Capital.