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Flywheel

AI-driven medical imaging data management and analysis platform.

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What is Flywheel?

Flywheel is a cloud-based platform for managing, organising, and analysing medical imaging data. It automates the workflow of collecting imaging files from multiple sources, standardising them, and preparing them for research or AI model development. The platform is designed for researchers, clinicians, and AI developers who work with large volumes of imaging data across multiple sites. Flywheel handles the technical burden of data organisation, security, and compliance, allowing teams to focus on analysis and discovery rather than infrastructure.

Key features

Data management

automated ingestion, organisation, and standardisation of medical imaging files from various sources

Data discovery

searchable catalogue and indexing of imaging datasets with filtering and query tools

Data curation

tools to prepare analysis-ready datasets through classification, standardisation, and quality checks

Collaboration

secure sharing and joint analysis across multiple research sites and organisations

AI model support

infrastructure for developing, testing, and preparing medical imaging AI models for regulatory submissions

Integration

connects with existing research tools, DICOM systems, and third-party applications through APIs and plugins

Pros & cons

Advantages

  • Reduces time spent on data organisation and preparation, freeing researchers for analysis work
  • Scales to handle large imaging datasets without requiring substantial local hardware investment
  • Provides secure, compliant data management suitable for regulated research and clinical environments
  • helps multisite collaboration by centralising data and providing standardised access controls

Limitations

  • Pricing information is not publicly detailed; costs likely scale with data volume and team size, requiring direct contact for quotes
  • Implementation and integration with existing systems may require technical support and training
  • Platform is specialised for medical imaging; not suitable for general-purpose data management outside this domain

Use cases

Organising imaging data from clinical trials across multiple hospital sites

Preparing standardised datasets for training and validating medical imaging AI models

Managing longitudinal imaging studies where data needs to be tracked and analysed over time

Supporting regulatory submissions by maintaining audit trails and compliance documentation for imaging data

Enabling collaborative research between academic institutions without requiring researchers to manage infrastructure

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Pricing

Custom/Enterprise

Contact for pricing

Pricing based on data volume, number of users, and deployment requirements; no public pricing available

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