Flywheel offers a cloud-native platform that centralizes medical imaging data, providing searchable metadata, automated curation, and scalable compute for AI model training. The system includes role‑based access controls and 21 CFR Part 11 compliance, enabling secure multisite collaboration and regulatory‑ready dataset preparation. It also supports open‑source “Gears” plug‑ins and APIs for custom analysis pipelines.
Funding
$20M 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
Data scientists and researchers spend a large portion of their time locating, organizing, and standardizing medical imaging datasets, which are often siloed across institutions and lack consistent metadata. This hampers efficient collaboration, delays AI model development, and complicates regulatory compliance for clinical trials and device approvals.
Solution
Flywheel provides a cloud-native platform that centralizes medical imaging data, enabling secure discovery, curation, and computation at scale. Integrated tools automate metadata extraction, cohort building, and dataset standardization, reducing manual preprocessing effort. The platform supports extensible, open‑source “Gears” plug‑ins for custom analysis pipelines and AI model training. Built‑in role‑based access controls and 21 CFR Part 11 compliance ensure data privacy and regulatory readiness. Collaborative workspaces allow multisite sharing and real‑time annotation, while professional services offer consulting and training to accelerate adoption. Together, these capabilities transform raw imaging archives into analysis‑ready, AI‑compatible datasets.
Target Audience
Primary users are pharmaceutical and biotech R&D teams, academic and clinical researchers, and medical device developers who need to manage large imaging repositories, collaborate across institutions, and develop AI‑driven biomarkers or regulatory submissions.
Features
- Cohort discovery engine with searchable metadata and advanced query capabilities for rapid dataset identification.
- Automated data curation workflows that standardize DICOM headers, enforce FAIR principles, and de‑silo data across sites.
- Scalable cloud compute environment with containerized “Flywheel Gears” for custom preprocessing, segmentation, and AI model training.
- Secure, role‑based access management and audit trails compliant with 21 CFR Part 11 and HIPAA regulations.
- Multisite collaboration tools including shared workspaces, versioned annotations, and real‑time data synchronization.
- Open API and SDKs (Python, REST) for integration with external analysis tools, electronic health records, and clinical trial systems.
- Professional services team offering workflow consulting, validation support, and on‑site training to streamline implementation.