Bitfount for Trusted research environments

Trust, embedded

Bitfount integrates seamlessly with your TRE to ensure its governance requirements are met, without limiting data utility. Unlock distributed innovation in your field by embedding Bitfount within your TRE architecture.

Bitfount - Federated Analytics and Machine Learning Platform

Bitfount and The Five Safes Framework

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.


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

Data controllers dictate who has access to what data, ensuring only approved researchers can execute against datasets for approved use cases.


Safe Settings

Given the federated nature of Bitfount's platform, researchers can only access data remotely if they've authenticated according to the TRE's requirements. Bitfount supports Single Sign-On as standard and can work with you to ensure authentication meets your needs.


Safe Outputs

Bitfount's built-in privacy-enhancing technology controls minimise privacy leakage, ensuring researchers only see what you want them to see. Choose from Metrics Only, View Only, or Differential Privacy controls for maximum flexibility.


Use Cases for Trusted Research Environments

Privacy-Preserving Data Science

Deploy features to enable talented AI/ML researchers to safely leverage data beyond basic use cases.

Usage Controls, Beyond Access

Set granular use case-level rules against datasets, depending on the datasets and the researcher accessing them.

Federated TRE Network

Link decentralised TREs such that results can be output to a results-only TRE. Researchers see no raw data.