Trusted Research Environments
Seamless federated analytics between TREs, SDEs and external researchers
Analyse data across TREs, SDEs, and clean rooms while complying with governance protocols and maximising data utility.
Explore TRE case studies
A federated network of Trusted Research Environments to enable safe analytics
Bridging AI, data & governance: The FAIR TREATMENT project on adolescent mental health
Bitfount platform
Easy IT integration
Install in seconds via desktop app (available for Windows and Mac) or Python SDK
No-code workflow
Intuitive workflow for use by anyone from physicians to research teams to data scientists
Powerful data governance & IP protection
Built-in governance features ensure you’re always in control of how your data is used and by whom
Deep imaging capabilities
Efficiently analyse 2D or 3D medical images. No de-identification or pseudonymisation required
Integrate your EMR
Connect your Electronic Medical Record (EMR) system for deeper cross-silo analysis
Model agnostic
Use commercial, academic or open-source models. No vendor lock-in
Supported image formats
Supported EHR systems
Supported model frameworks
Frequently asked questions
Can Bitfount access my data?
No, Bitfount’s zero-trust architecture ensures Bitfount never receives data or analysis results. Analysis results are transferred between data custodians and data scientists end-to-end encrypted using encryption keys held by each party and not accessible to Bitfount. Read more here.
What will my Information Governance team think of this?
Information Governance and Legal teams love Bitfount since it removes the need for complex Data Sharing Agreements (DSA) and Material Transfer Agreements (MTA), and massively simplifies Data Protection Impact Assessments (DPIA). Bitfount is also fully GDPR, HIPAA and ISO27001 compliant. Visit our online Trust Centre here.
Do I need to be able to code?
No. Our desktop application has been designed to be operated without requiring any coding knowledge. This includes connecting datasets, joining projects, running tasks and accessing analysis results. Data scientists and algorithm developers can choose to interact with Bitfount via our python SDK.
Are there any hardware requirements?
There aren’t any specific requirements, however AI analysis at scale can be compute-intensive and will run more efficiently, especially for image analysis, if you have access to a machine (physical or virtual) with a GPU. Suitable devices include any Apple silicon model, or a Windows or Linux machine with an Nvidia GPU. Not sure if you have the right setup? Reach out to us at support@bitfount.com for guidance.
Any more questions?
Contact our team for tailored guidance or more details about your use case.
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