Solutions
Build a research operating model people can actually use.
CALYPR helps research programs move from scattered files, spreadsheets, and one-off analysis into a governed system for data access, metadata, workflow execution, and reusable research assets.
Manage Data
DRS registration, transfer, and governed object access.
Manage Compute
Portable TES-style execution across local, cloud, and federated environments.
Integrate Data
FHIR-shaped metadata, validation, and graph-ready context.
Manage Models
Model assets grounded in governed data, provenance, and benchmarks.
Business use cases
Choose the operating problem first. The product decision follows from there.
Launch a governed data program.
Stand up a controlled intake and sharing model for sensitive biomedical datasets without making bucket administration the user experience.
Turn analysis into a repeatable service.
Execute workflows across cloud and HPC environments while keeping the run attached to governed inputs, tracked task state, and durable outputs.
Make metadata usable across teams.
Move clinical, omics, and project context out of spreadsheets and into validated structures that can support governance, discovery, and downstream analytics.
Build a path into model operations.
Tie model work back to the datasets, workflow history, metadata relationships, and benchmark context that produced it instead of treating modeling as a separate silo.
Operating path
What changes when CALYPR becomes the operating layer for research delivery.
Instead of building separate processes for storage, metadata, compute, and downstream packaging, teams get one operating path that carries data and context forward together.
Replace ad hoc file movement with DRS-native registration, scoped remotes, presigned transfer, and collaborator-aware policy boundaries.
Map tabular project information into FHIR-shaped resources and graph relationships that can be validated, reused, and queried.
Run repeatable workflows through a portable execution layer instead of rebuilding task operations around each environment.
Keep data, workflow provenance, benchmark context, and model artifacts inside one governed operating system.
Buying paths
Research programs rarely buy infrastructure all at once. They start with one visible operating failure.
Files arrive through tickets, shared drives, and custom scripts. Teams need a governed way to register, move, resolve, and share large research objects.
Workflows depend on environment-specific glue and tribal knowledge. Teams need portable execution, consistent inputs, and repeatable provenance.
Program context is trapped in spreadsheets and exports. Teams need validated structures that can support governance, search, and graph-style exploration.
Benchmarks, models, and workflow artifacts are drifting away from the governed data they rely on. Teams need one asset lifecycle instead of parallel systems.
What sits underneath
The story is backed by technical capabilities your platform team can verify.
Governed object access
Syfon exposes GA4GH DRS APIs, presigned upload and download URLs, and multipart transfer lifecycle support so data operations have a real service contract behind them.
Version-aware data workflows
Git-DRS stores pointer files in Git, keeps large binaries out of normal history, and connects repositories to scoped remotes for push, pull, hydration, and delete workflows.
Structured metadata and discovery
Forge validates and publishes metadata, CALYPR uses FHIR resource structure for research entities, and GRIP provides graph-oriented query patterns across integrated project data.