Researchers
Accelerate discovery through secure data collaboration
Analyze, share, and innovate across institutions with Bitfount’s federated data and AI platform, advancing discovery without compromising privacy or governance.
Use cases
Al/ML model development
Accelerate discovery through privacy-preserving AI
Train and deploy AI models directly on distributed research datasets using federated learning. Unlock insights without compromising confidentiality.
Build collaborative consortia
Advance science through secure collaboration
Form multi-institutional research consortia that analyze shared questions across protected datasets, all without moving or exposing raw data.
Federate between TREs
Connect Trusted Research Environments securely
Link multiple TREs using Bitfount’s federated compute layer, enabling cross-environment analysis and model training while preserving each TRE’s governance controls.
Bitfount platform
No-code desktop application
Easy to install on Windows or Mac
Deep imaging capabilities
Analyse OCT, FAF, CF, SLO images and more
Integrate your EMR
Connect your EMR data for deeper analysis
Model agnostic
Use any model provider with Bitfount
Certifiably secure
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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