We're thrilled to announce the launch of our open beta product, a distributed data science platform making it possible for data custodians and data scientists to collaborate on performing privacy-preserving data analysis and ML without transferring or revealing raw data. From private SQL analysis to federated machine learning and evaluation, we are working tirelessly to help data scientists and custodians safely harness the potential value of data collaboration. We're debuting the beta at Big Data LDN, where our CEO, Blaise, will speak about how the techniques powering Bitfount’s open beta product can enable privacy-preserving data collaboration on sensitive datasets such as patient, financial, or other protected data categories.
Unlocking the value of data for the benefit of humankind has always been core to Bitfount’s vision, and for the first time today, anyone can sign up to contribute to and benefit from the Bitfount community and vision. We look forward to seeing what our community builds!
While Bitfount’s platform is currently leveraged to ensure the safety of data analysis in healthcare and financial-services contexts, our open beta offering is built for general purpose use across any industries or sectors wishing to collaborate to analyse or build models in association with sensitive data. We aim to power any such type of collaboration, from internal data access controls to data consortia in which several providers pool data in order to enable data scientists to safely train and evaluate accurate models. This flexibility is possible because rather than transferring data to data scientists as is currently commonplace, we enable data scientists to send algorithms to data according to usage-based access controls set by data custodians. Using this model, several healthcare and research institutions are able, for example, to collaborate on digital biomarker development, diagnostic models, and clinical trial patient recruitment in a way they wouldn’t have been able to before.
Unlike competing solutions, our open beta product utilises a zero-trust security model and a novel message-based architecture that makes it much easier and faster for IT teams to deploy than other federated solutions. As opposed to platforms which prioritise the ease of use for either data custodians or data scientists, Bitfount places an emphasis on providing compelling features for both sides of any collaboration. We hope to empower data scientists to leverage familiar tools and receive the insights they need while never putting underlying data at risk. For data custodians, the platform provides a suite of functionality to put any information governance team at ease including full audit history, granular usage-based access controls, and a configurable cryptographic privacy layer including techniques such as differential privacy and secure multi-party computation (SMPC) for additional privacy guarantees.
By opening our product to data custodians and data scientists around the world, we aim to help others reduce the friction we’ve experienced ourselves in accessing sensitive data. A process that used to take months or years can now be reduced to weeks with the help of the technical guarantees our platform provides.
We'd love for you to join us and provide your feedback! Sign up now.
Meet Blaise and find out what it's like to be the CEO and Co-Founder at Bitfount
Blaise explains how federated learning and zero-trust are compatible concepts.