Flywheel Secures $25M in Equity for Medical Imaging Data Platform
Medical imaging is the heavyweight champ of healthcare data. Over 80% of it lives in pixels, scans, slices, and signals, yet most of the industry still treats it like loose film reels stacked in a forgotten basement. Flywheel shows up and says no, this data deserves infrastructure, discipline, and systems built for adults in the room. The market agreed with a $25M oversubscribed equity round led by Novalis LifeSciences and 8VC, backed by a lineup that reads less like hype and more like proof: NVentures at NVIDIA, Microsoft, Novartis, Intuitive Surgical, Hewlett Packard Enterprise, Beringea, Great North Ventures, iSelect, Gundersen Health System, and Seraph.
The origin story matters. Brian Wandell and Gunnar Schaefer were not chasing decks or demo days. They were solving a real problem at Stanford, building an open system that could capture MRI data, organize it, and let researchers actually trust what they were seeing. When collaborators leaving Stanford asked to take the system with them, the signal was clear. Partnering with Invenshure out of Minneapolis, Flywheel became a company because demand pulled it into existence.
Today the traction speaks in full paragraphs. Flywheel works with 10 of the top 20 global pharmaceutical companies and 10 of the top 20 academic medical centers. In 2025 alone, new business grew 43% YoY, committed revenue climbed 40%, and ARR from pharma and medical device customers jumped 106%. Net revenue retention cleared 110%, which only happens when the platform stops being software and starts becoming infrastructure that teams do not want to live without.
Under the leadership of Matthew A. Michela as CEO and Board Chair Hooman Hakami, Flywheel is leaning into the hard parts of healthcare. Clinical trials. Regulated workflows. AI development that does not fall apart when compliance walks into the room. The launch of Flywheel Validated for 21 CFR Part 11 workflows and deep integrations with Microsoft Azure, NVIDIA MONAI, and Azure Machine Learning are not shiny objects. They are signals to pharma, medtech, and research leaders that this platform understands the cost of getting it wrong.
Imaging data is not just big, it is sensitive, regulated, and central to discovery. Flywheel’s edge is control without friction, collaboration without chaos, and scale without shortcuts. Capital keeps coming back because once imaging data spins correctly, nobody wants to jump off the wheel, and the hum is getting louder across biopharma, medtech, and academic research.