

Unified Multimodal Datastore
Genomcore UMD is a high-performance datastore designed to manage and interlink diverse biomedical data types—from genomics and clinical records to time-series and imaging—offering unmatched interoperability, observability, and structure.

UMD provides fine-grained, structured storage for the diverse types of data that define precision medicine. Whether it's genomics, time-series, or clinical values, each dataset is managed in a format ready for real-world healthcare use.

From ready-to-use records to fully custom templates, UMD gives you complete control over how you structure and relate biomedical information—tailored to your workflows, compliant by design.
Store general files and attach relevant metadata
Collect structured inputs from patients or end-users
Manage medical imaging files and associated metadata
Display structured results and interpretations
Use standardized terminology codes
Link clinical data to individual profiles securely
Group multimodal data into project-specific records
Track outputs and parameters from analysis applications
Define your own record types with tailored fields, behaviors, and relationships using our visual templating system.


Use the same schema across multiple projects or workflows
Define attributes and logic that fit your real-life processes
Connect records through ontology-based relationships
Native support for HL7, FHIR, OMOP, and other standards
UMD simplifies how biomedical data is handled at scale, offering native support for distributed file systems, seamless integrations, and real-time interoperability with other tools and platforms.
Upload and manage large binary files (BLOBs) with embedded viewers, restricted sharing, and unified access through an emulated file browser.
Instantly find experiments with shared genomic variants, speeding up analysis, and uncovering key insights faster.
UMD is fully integrated with the Genomcore ecosystem—connect your datasets with analytical apps, reporting modules, or external platforms effortlessly.





