The First Data Infrastructure Built for Healthcare AI.

AI-ready medical imaging and EHR datasets

Harmonized, de-identified, and annotated for research, diagnostics, and clinical applications

Make models work everywhere, instantly

Healthcare data is fragmented across scanners, sites, and formats, forcing teams to spend months collecting data and customizing pipelines before models can deploy at new institutions.

Eos harmonizes data at the source, enabling models to transfer seamlessly and perform reliably everywhere from day one. Our proprietary pipeline accelerates deployment, enhances model performance, and preserves clinical features.

Store less. Lose nothing.

Medical imaging pipelines still rely heavily on JPEG and JPEG-2000, which introduce irreversible information loss and can degrade downstream modeling and clinical fidelity.

Eos provides lossless, modality-aware compression for medical imaging, preserving the full diagnostic and biological signal while significantly reducing file size. Unlike JPEG-based methods, our compression is designed for AI and clinical workflows, ensuring images can be stored, transferred, and reused without compromising accuracy.

The result is lower storage and bandwidth costs, faster data movement, and imaging data that remains fully faithful and model-ready.

Software-defined, AI-native VNA

Eos provides a software-defined, AI-native vendor-neutral archive (VNA) for medical imaging and clinical data.

Data is stored in a lossless, structured format and indexed with rich metadata, making datasets fully queryable across modalities, sites, and time. Instead of pushing data into rigid PACS workflows, teams can programmatically search, retrieve, and organize imaging and clinical records for analytics, ML, and downstream applications.

The result is lower storage overhead, faster access, and a modern data foundation built for healthcare AI, not legacy systems.