DURHAM, N.C. and AMSTERDAM, Netherlands, June 15, 2026: Gradient Health, a leading healthcare data platform for medical AI development, today announced the expansion beyond imaging to support multimodal healthcare data.

The announcement, made on the opening day of HLTH.Europe in Amsterdam, marks a major expansion of Gradient Health’s role in the medical AI ecosystem. Already trusted by more than 200 medical AI companies, from early creation through testing, evaluation, and regulatory submissions, Gradient Health is now extending Atlas to help developers access richer, more contextual data for building, evaluating, and validating medical AI models.

Atlas currently gives AI developers access to more than 20 million medical imaging studies, including radiology reports and longitudinal datasets that can show the same patient’s scans across multiple time points. With this expansion, Gradient Health is adding support for additional data types, including EHR data, pathology results, and cardia data such as ECG.
These new data types will be introduced progressively through Atlas, with the goal to give AI developers a scalable, responsible, and searchable infrastructure for accessing multimodal healthcare data as availability grows.

The expansion reflects a broader shift in medical AI as the field moves from narrow single-point solutions toward broader foundation models and more advanced clinical AI systems, developers increasingly need access to data that reflects the complexity of real-world care. Imaging remains essential, but many clinically valuable AI applications require additional context, including clinical notes, patient history, laboratory data, pathology results, and other structured or unstructured clinical information.

Gradient Health’s multimodal expansion is designed to support that transition.

“Imaging is already one of the strongest applications for medical AI,” said Pranav Rajpurkar, PhD, Associate Professor at Harvard Medical School and Co-Founder of a2z Radiology AI. “By adding multimodal context, Gradient can help developers build more useful, representative, and generalizable systems, while addressing one of the field’s biggest data access challenges.”

“Medical AI is moving fast, but the next generation of models will only be as good as the data behind them,” said Josh Miller, CEO of Gradient Health. “Imaging has been our foundation, and it remains central to what we do, but healthcare is multimodal by nature, a scan rarely tells the whole story on its own. By expanding Atlas to support multimodal data, we are helping AI developers build systems with richer clinical context, while giving healthcare organizations a secure and responsible way to contribute to innovation. Better data means better AI, and better AI should mean better access to advanced care for more patients.”

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