A federated privacy-preserving platform for solving data collaboration challenges. From discovering and evaluating third-party datasets to running data consortia, training advanced AI models, and much more.
Our commitment To pRIVACY
Bitfount envisions a world where powerful data science collaboration can occur without risk to the individual. We believe we have a responsibility to consumers in working to ensure data scientists have the tools to responsibly explore data. Never compromise privacy over quality again.
Mitigate privacy risk according to your organisation's policy and risk postures. No leaky data pipelines to be found.
Raw data never leaves your environment.
Apply granular privacy-preserving policies depending on your level of trust in collaborators.
Access Bitfount's expertise in privacy-enhancing techniques.
Explore tutorials and whitepapers on privacy-enhancing data science based on the latest academic research.
Learn more about how Bitfount enables privacy-enhancing technologies →
The value of data is inseparable from the way it's processed. Bitfount Pods (Processing on Data)™ give data owners control over both which data and which algorithms any given collaboration partner can use.
Link siloed datasets while preserving privacy.
Full compatibility with on-premise data. No cloud migration needed.
Maintain granular, role-based, time-bound control of your data.
Dictate who can access what data and how they can interact with it (including privacy-enhancing controls).
Audit interactions with your Pods.
Learn more: Read about our Pod policies →
