Clinical trials
Collaborate on sensitive data using AI across distributed sources, without moving it.
Leverage AI to identify high-performing trial sites and eligible patients faster—without moving sensitive health data.

Transform site feasibility and patient recruitment with objective data from sites. Click to learn more.

Find the right patient for the right trial and slash your screen failure rates. Click to learn more.

Put your models to work by distributing them on-premise to the Bitfount network. Click to learn more.
Match patients to trial criteria within hospital systems using federated queries and AI on imaging and EHR data, boosting recruitment speed and reducing screen failure rates, without sharing raw data.
Simulate inclusion criteria and optimize endpoints using federated analytics across diverse datasets without ever moving sensitive patient data.
Evaluate potential trial sites’ patient populations and data availability via federated queries that keep all data under local control.
Identify optimal sites based on real, distributed patient and performance data, ensuring every selection decision is data-driven and privacy-preserving.
Move imaging and EHR data from sites to sponsors or CROs through Bitfount’s governed data-transfer workflows, ensuring full traceability, encryption, and regulatory compliance at every step.
Build, validate, and deploy machine learning models directly on distributed datasets using federated learning to maintain confidentiality and fairness.
Conduct longitudinal safety and efficacy studies across multiple data custodians while preserving each organization’s data privacy.
Validate predictive models on external cohorts through federated evaluation to ensure generalizability. No sensitive data ever leaves its source.

Easy IT integration
Install in seconds via desktop app (available for Windows and Mac) or Python SDK
No-code workflow
Intuitive workflow for use by anyone from physicians to research teams to data scientists
Powerful data governance & IP protection
Built-in governance features ensure you’re always in control of how your data is used and by whom
Deep imaging capabilities
Efficiently analyse 2D or 3D medical images. No de-identification or pseudonymisation required
Integrate your EMR
Connect your Electronic Medical Record (EMR) system for deeper cross-silo analysis
Model agnostic
Use commercial, academic or open-source models. No vendor lock-in










No, Bitfount’s zero-trust architecture ensures Bitfount never receives data or analysis results. Analysis results are transferred between data custodians and data scientists end-to-end encrypted using encryption keys held by each party and not accessible to Bitfount. Read more here.
Information Governance and Legal teams love Bitfount since it removes the need for complex Data Sharing Agreements (DSA) and Material Transfer Agreements (MTA), and massively simplifies Data Protection Impact Assessments (DPIA). Bitfount is also fully GDPR, HIPAA and ISO27001 compliant. Visit our online Trust Centre here.
No. Our desktop application has been designed to be operated without requiring any coding knowledge. This includes connecting datasets, joining projects, running tasks and accessing analysis results. Data scientists and algorithm developers can choose to interact with Bitfount via our python SDK.
There aren’t any specific requirements, however AI analysis at scale can be compute-intensive and will run more efficiently, especially for image analysis, if you have access to a machine (physical or virtual) with a GPU. Suitable devices include any Apple silicon model, or a Windows or Linux machine with an Nvidia GPU. Not sure if you have the right setup? Reach out to us at support@bitfount.com for guidance.
Contact our team for tailored guidance or more details about your use case.