Manage Models¶

Manage Models gives research organizations a way to carry governed data, workflow history, and benchmark context into model-driven work instead of treating models as a separate lifecycle with separate controls.

This is the most forward-looking product area, but it is not hand-wavy. The current platform already supports versioned data pointers, FHIR-based provenance context, workflow execution history, and graph-oriented relationships between files, studies, subjects, and derived outputs.

Who It Helps¶

• Prepare research organizations for model-centric operating patterns.
• Keep model work connected to governed data and reproducible execution.
• Give benchmark and evaluation context a place in the system story.
• Extend the platform from data and workflow operations into reusable model assets.

What Customers Get¶

• A model-facing product layer that inherits the rest of the CALYPR foundation.
• A cleaner path from analysis outputs into model operations.
• Better continuity between datasets, workflows, and model assets.
• Room to grow model packaging and governance without changing the platform story.

Current Foundation¶

• Versioned and scoped data references from the governed data layer.
• Workflow provenance from the compute layer.
• Metadata relationships that can tie model artifacts back to studies, specimens, observations, and generated files.
• A graph-friendly context for evaluating and comparing model outputs against the data and processes that produced them.

Why Buyers Care¶

Model operations are usually introduced after data and workflow systems are already fragmented. Manage Models keeps that future work attached to the same governed data, metadata, and execution model from the start, which is the only realistic way to make model assets auditable in biomedical settings.