Data partnerships

Activate first-party data without the data sharing headache

Build data partnerships securely with cohort matching, lookalike discovery, and aggregated metrics, all without any partner’s PII or commercially sensitive data leaving their firewall.

Use cases

Patient pre-screening

Research consortia

Unite research networks without sharing data

Empower multi-institutional collaborations to analyze and share insights securely using federated analytics—ensuring every partner retains full data control.

Patient pre-screening

Cross-sector partnerships

Collaborate across industries, safely and efficiently

Enable secure data exchange and analysis between healthcare, life sciences, and technology partners with built-in privacy protection and auditability.

Patient pre-screening

Internal data collaboration

Break down silos, without breaking compliance

Connect internal datasets across departments or subsidiaries to unlock insights through federated compute while maintaining strict governance boundaries.

Patient pre-screening

AI/ML model development

Build powerful models from distributed data

Develop and refine AI models across multiple data sources using federated learning, preserving privacy while maximizing performance and representativeness.

Patient pre-screening

Dataset evaluation

Understand dataset value before sharing access

Run secure exploratory analyses on external or internal datasets to assess utility and quality. No exposure of raw or sensitive data required.

Patient pre-screening

Model evaluation

Validate models securely across collaborators

Test model performance across diverse partner datasets without transferring or centralizing data, ensuring robust and compliant validation.

Patient pre-screening

Model training

Train models where the data lives

Leverage federated training to learn from distributed datasets, ensuring sensitive data never leaves its source while achieving state-of-the-art accuracy.

Explore data partnership 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

Download

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.

Still have questions?

Our team are here to help

Contact us

Simple. Flexible. Fast.
Built for secure collaboration