Gradient Health for Data Partners.

A Gradient Health data partner is a healthcare organization, imaging provider, health system, or data owner that works with Gradient to make deidentified medical data available for responsible AI development.

Gradient works with organizations that hold valuable medical imaging, EHR, or multimodal clinical data. This may include hospitals, health systems, outpatient imaging centers, research organizations, specialty care providers, and other healthcare data owners.

Gradient works with medical imaging data, EHR data, pathology reports, clinical records, and multimodal medical data. This may include radiology exams, longitudinal patient-level records, imaging metadata, and other clinical information where available and appropriate.

Healthcare organizations partner with Gradient to generate value from deidentified medical data, support the development of better medical AI, and contribute to more representative datasets. Gradient helps reduce the operational, technical, and commercial burden of making data useful for AI development.

Patient privacy is central to the data partner model. Gradient uses deidentification, security controls, and data governance processes designed to protect patient information before data is made available for AI development.

Yes. Data is deidentified before it is made available to AI developers. Gradient’s process is designed to remove all patient-identifiable information while preserving the clinical value needed for responsible AI development.

Yes. Gradient can work with partners that provide imaging data or multimodal data, including EHR datasets that combine imaging with clinical context. This is increasingly important for AI teams building models that need more than single images or isolated records.

Yes. Gradient can support deidentified longitudinal datasets where data is organized around a patient journey over time. This may include multiple exams, reports, records, diagnoses, or clinical events linked to the same deidentified patient.

Multimodal medical data combines different types of healthcare information, such as imaging, EHR data, reports, claims, or other clinical records. For AI developers, multimodal data can provide richer clinical context than a single source.

Gradient helps curate, structure, and make deidentified partner data available to AI developers for approved use cases such as AI training, testing, validation, foundation model development, and regulatory evidence generation.

Gradient aims to minimize the operational burden on data partners. The process is designed around existing systems and workflows, with Gradient supporting the technical, governance, and operational steps needed to make data usable.

Data partners can create a new revenue opportunity from deidentified data while supporting the development of better and more representative medical AI. The details of their revenue share will depend on the type, scale, and usability of the data available.

Gradient supports responsible AI development by helping AI teams access diverse, representative, deidentified medical datasets. By partnering with healthcare organizations, Gradient helps reduce reliance on narrow or unrepresentative datasets that can limit model performance and generalizability.

A strong data partner typically has meaningful data volume, clear data governance, relevant clinical data, and an interest in supporting responsible medical AI development. Partners with longitudinal, multimodal, or diverse datasets are especially valuable.

Timelines depend on the partner organization, data systems, governance requirements, contracting, and technical setup. Gradient should be able to assess fit and outline next steps after an initial conversation.

Healthcare organizations and data owners can complete the data partner inquiry form or contact Gradient Health to discuss their data, goals, and partnership options.