The startup offers a cloud-based research data management platform that automates workflows for biomedical research, enabling collaborative studies and machine learning applications. This platform enhances data scalability and analysis, facilitating multicenter clinical trials and accelerating the pace of scientific discoveries.
Funding
$131.1M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Biomedical research often suffers from fragmented data silos, inconsistent data formats, and manual workflows, hindering collaboration and slowing down the development of AI models and scientific discoveries. The process of finding, curating, and organizing medical imaging data can consume a significant amount of researchers' time.
Solution
Flywheel offers a cloud-based platform designed to streamline medical imaging data management and analysis, enabling researchers to accelerate discoveries and develop AI-driven solutions. The platform provides tools to securely discover, manage, curate, and compute large amounts of imaging data, both within an organization and with external collaborators. By automating time-consuming processes and standardizing datasets, Flywheel allows scientists and researchers to focus on analysis and innovation. The platform facilitates multicenter collaboration, streamlines enterprise imaging workflows, and supports the development of analysis-ready datasets for AI training.
Target Audience
The primary target audience includes pharmaceutical and biotech researchers, clinical researchers, AI developers, and healthcare organizations involved in medical imaging research and development.
Features
- Centralized data repository for medical imaging data with secure access controls
- Automated data curation and standardization pipelines to ensure data quality and consistency
- Tools for cohort discovery, project validation, and complex analysis
- Support for multisite collaboration with secure data sharing capabilities
- Integration with AI development tools for building and training medical imaging algorithms
- Extensible architecture with open-source plugins (Gears) for custom workflows
- Compliant with relevant data privacy and security regulations