Bitfount, the federated AI platform transforming clinical research collaboration, has secured £6 million in Series A funding to scale its privacy-preserving network across healthcare systems globally. Parkwalk Advisors, Ahren Innovation Capital, Pace Ventures, Foresight Group, and Portfolio Ventures participated in the round.
Bitfount removes the data-sharing roadblock that has long held back clinical research. The most valuable insights come from combining datasets across multiple institutions, yet strict privacy regulations and competitive concerns make sharing impossible. This forces researchers to work with incomplete pictures, slowing drug development and limiting patient access to breakthrough treatments. Bitfount’s federated AI platform solves this by bringing algorithms to the data, not data to algorithms.
Healthcare providers and pharmaceutical companies can collaborate to improve clinical research without ever sharing raw patient data. The platform works across both electronic health records (EHR) and medical imaging data – a unique capability that sets it apart from platforms limited to text-based analysis alone. It streamlines trial lifecycles by accelerating patient recruitment, reducing screen failure rates, and enabling data-driven site feasibility assessments – all while maintaining complete data sovereignty. AI model development is similarly accelerated.
The funding comes as the UK government unveils unprecedented support for clinical research through its 10 Year Health Plan, announced in June 2025. The plan aims to slash commercial trial set-up times from 250 days to 150 days or less by March 2026 and position the UK as a global destination for clinical trials. However, achieving these ambitious targets requires addressing fundamental infrastructure challenges – precisely what Bitfount’s federated AI platform delivers by enabling secure collaboration without the data-sharing bottlenecks that have historically slowed UK clinical research.
Co-founded with Dr Naaman Tammuz, the platform’s no-code desktop application can be deployed across any healthcare setting – from major hospital systems to small community clinics – creating a distributed network that preserves local data control while enabling global collaboration. This approach directly addresses the £80 billion AI for Healthcare and Life Sciences market, where data privacy concerns have historically limited AI adoption.
Early pilot implementations demonstrate significant impact across multiple therapeutic areas. In a validation study conducted with Moorfields Eye Hospital for a trial in Dry Age-Related Macular Degeneration (Dry AMD), the team demonstrated a reduction in screen failure rates from 60% for traditional EHR-based searches alone, to just 14% when EHR search was combined with AI-based OCT image analysis, while still identifying over 600 eligible patients at that single hospital. The platform enables pharmaceutical companies and clinical research organisations to identify suitable patients and optimal trial sites without accessing underlying patient records.
