Bitfount for Trusted Research Environments & Secure Data Environments

Federate safely

Bitfount integrates seamlessly with Trusted Research Environments (TRE) or Secure Data Environments (SDE) to ensure governance requirements are met without limiting data utility. Easy to integrate, with strong support for all Five Safes.

Build in privacy by design

A Privacy-Enhancing Backbone for Federated Data Infrastructure

Broad selection of built-in PETs

Built in support for a range of privacy-enhancing technologies including:

  • Federated Learning
  • Federated Execution
  • Private SQL
  • Differential Privacy
  • Secure Multi-Party Computation (Secure Aggregation)

Easily mix and match to achieve the desired privacy guarantees.

Go beyond data access with usage controls

Full access to data is unnecessary, and fully-manual disclosure control doesn't scale. Bitfount's role-based usage controls allow you to minimise data exposure while meeting research needs and retaining full a full audit trail of access requests and analyses performed.

Built in pseudonymisation tools

Before connecting your data, apply optional pseudonymisation transformations such as redacting, replacing or encrypting names, dates, phone numbers, addresses and other personally identifiable information (PII)

Connect to modern and legacy systems

Bitfount supports all standard tabular and imagining data formats out of the box, as well as relational databases, DICOM images and some EHR systems. Plugin architecture enables easy integration with legacy or proprietary systems and data formats.

Create a Federated Data Network

Distribute analyses to be run across multiple federated environments in order to see the big picture and increase statistical power. Bitfount acts as a unifying connective tissue to unlock interoperability across disparate technical infrastructures.

Privacy-preserving AI and data science

In addition to support for standard statistical analyses and regressions, Bitfount has built-in support for training and deploying the latest AI/ML algorithms to drive innovative use-cases.

Single system, multiple interfaces

Interact with the Bitfount platform via code using the python SDK, or via the no-code interface of the Bitfount desktop application. The online Bitfount Hub also provides an always-available control centre for your federated network.

Bitfount and the Five Safes

Safe Data

Bitfount's process for connecting datasets and assigning privacy-preserving policies ensure researchers only have access to the appropriate data and cannot reasonably re-identify patients or citizens. Raw data is never accessible, and built-in pseudonymisation can be applied.


Safe Projects

Data controllers have complete authority over who executes against what data for which purposes. Researchers are unable to perform use cases which are not in the scope of the projects you've approved for them.

Safe People

Bitfount's privacy-enhancing technologies (PET) and access controls minimise the chances of unauthorised or unsafe data usage by researchers. Integration with the TRE's identity provider enables strong authentication.


Safe Settings

Bitfount's built in privacy-, governance- and security features provide additional layers of safety to the TRE/SDE facility's own infrastructure.

Safe Outputs

Usage controls constrain the nature of permissible analysis outputs. For additional peace of mind, enforce manual disclosure controls to allow manual inspection of outputs prior to their release.


Get started

Towards a federated network of connected TREs
Get started or book a demo to learn more.