Research environments
Seamless federation between TREs, SDEs and third-parties
Distribute analysis across Trusted Research Environments, Secure Data Environments and Data Clean Rooms while ensuring governance requirements are met without restricting data utility
A federated network of Trusted Research Environments to enable safe analytics
By acting as the link within the Trusted Research Environment’s ecosystem, Bitfount enabled secure analyses by training and deploying of AI models.
key features and benefits
Secure, on-premise data analysis made easy
Certifiably secure
HIPAA & GDPR compliant and ISO27001 certified
No data leaves
No data anonymisation required
Diverse data support
Analyse imaging, tabular, and unstructured data
No-code app
No-code desktop app and scalable SDK
Medical AI network
Access a network of medical AI models
CAPABILITIES
Relevant platform capabilities for research environments
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.
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