Train across institutions without moving patient data.
Hospitals can train shared models without pooling patient data. When a reviewer asks how the model was built, your team can provide reproducible, cryptographic evidence.
Training runs inside each institution — patient data never crosses the covered entity's perimeter.
Cross-site training without a single PHI data-sharing agreement — months of legal review collapse into weeks.
Every model version carries attested lineage from data prep through validation, by default.
A model trained across partner sites, with submission evidence, in the first engagement cycle.
The data stays. Only model updates move.
Deploy to each site
Training spins up inside every participating institution — the model comes to the data, so patient records never move.
Train in parallel
Each site trains locally and contributes only model updates, aggregated so no single contribution can be read.
Attest every stage
From data prep to validation, each step records signed lineage automatically — your submission evidence builds as the run proceeds.
Deploy with the record
The model trained on every site's data goes live with the record of how it was built, ready for reviewers instead of assurances.
Multi-hospital medical imaging
Train on the scanner and demographic diversity no single hospital owns — cutting the model bias that sinks radiology and pathology tools in the real world.
EHR early-warning systems
Sepsis and deterioration models that generalize across every health system's population, not just the one they were built in.
Clinical NLP
Turn millions of unstructured notes into structured signal — entity extraction and drug-interaction detection at a scale one site could never reach.
What the auditor sees is what the platform recorded.
No platform can make a covered entity HIPAA compliant — BAAs, access controls, and risk analysis stay yours. What CID removes is the hardest part: because PHI never leaves your environment, training stops being a disclosure you have to justify.
PHI never leaves the covered entity. Training happens in place; only signed model updates move.
Every model version carries attested lineage from data prep through validation — evidence ready for premarket submission.
Remove a patient’s data from the model, not just the database, and keep the record that it happened.
Native connectors with PII scanning at ingestion — clean data prep, attested.
Inside the hospital’s perimeter.
CID runs inside the hospital’s own cloud accounts. Patient data never touches STEAV’s infrastructure — the control plane operates within your perimeter.
Absolute network isolation. PHI remains inside the covered entity's firewall at all times.
Full governance via the health system's own cloud tenancy — with native Epic FHIR and HL7 connectors.
Auditors get evidence, not assertions.
Stop assembling compliance narratives for HIPAA and FDA reviewers. STEAV records every training run as it happens, so submission evidence is a byproduct of building.
First pipeline run in 4–6 weeks. First production federation in 8–12.
We map one clinical workflow and stand up an environment in your cloud.
A signed training record you can hand straight to an auditor.
Live cross-site training producing evidence on every run.