Train across hospitals. The data never leaves the institution.
Reach diagnostic-grade accuracy on data from every partner site — without a single raw-PHI sharing agreement. Months of legal review collapse into weeks, and your models scale across institutions as fast as you can sign a pilot.
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 proof moves.
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 proven 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.
Ship with proof
Deploy a model trained on every site's data, and hand reviewers verifiable evidence 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 proved.
PHI never leaves the covered entity. Training happens in place; only cryptographically proven model updates move.
Every model version carries attested lineage from data prep through validation — evidence ready for premarket submission.
Prove a patient's data was removed from the model, not just the database. Verifiable unlearning.
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 produces immutable, verifiable proofs of every training run in real time — submission evidence as 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.