Where SECUVA™ shows up.
Three operating models. One platform.
Whether you are the health network setting policy, the research institute consuming data, or the AI vendor receiving it - the SECUVA™ agent meets every stakeholder in the chain with the same guarantees and the same audit trail.
Every AI vendor wants your data. Legal keeps saying no.
Stand up one data-sharing policy that satisfies legal, IT, and clinicians - then meet it on every export, every modality, every vendor.
- Centralised export policy across PACS, EMR, LIS and research stores
- Patient identity never serialised to an external network call
- Signed audit trail exportable for OAIC, HREC, and board review
The cohort you need is sitting in a PACS. HREC says you can have it.
Close the gap between ethics approval and a clean, queryable dataset. The de-identification step turns from a project into a pipeline.
- Cohort-grade de-identification across imaging, clinical text, and genomics
- HREC-ready documentation generated alongside every export
- Population-level controls applied before data leaves the agent
Stop waiting on hospital IT. Start getting clean data.
The number-one reason AI vendors stall in health networks is data access. SECUVA removes the bottleneck without putting raw PHI on your infrastructure.
- Hospital ships de-identified data direct to your endpoint
- Per-pipeline policy enforced at the source - your scope of data never grows
- Procurement and security review move in weeks, not quarters
One agent.
Every clinical data type.
Each modality hides patient identity in its own surfaces - pixel overlays in imaging, label images in pathology, report headers in cardiology, sample IDs in genomics. SECUVA™ handles all of them with one platform and one audit trail.
Radiology
Third-party radiology AI keeps coming up in strategy meetings. Legal keeps saying no because images leave the network with patient identifiers still attached.
Pathology
The whole-slide image is de-identified. The macro label image and LIMS barcode often are not - and both can re-identify a patient.
Cardiology
The waveform is clean. The report header is not. Cardiology AI partnerships stall on the same patient-identifier exposure as imaging.
Genomics
Variant calls are stripped. The genome is not. Sample IDs, family-link metadata, and rare-variant re-identification risk all need handling before release.
Clinics & Allied Health
Small practices are expected to meet the same Privacy Act obligations as large health networks - usually without a privacy team or dedicated IT.
Three situations where
SECUVA™ fits exactly.
Most teams arrive here from one of three places. If your situation reads like any of these, you already know which deep page to start with.
Your AI vendor pilot has stalled in legal.
The hospital wants to ship a radiology AI pilot. Legal is six months in on the data-sharing agreement and counting. The problem isn't the contract - it's the lack of a defensible de-identification posture to anchor it to.
Your HREC-approved cohort has nowhere to land.
The ethics committee approved the study. The PACS export script from 2022 isn't HREC-grade. A cohort that should take days to assemble is taking months because de-identification is still treated as a manual project rather than infrastructure.
Your AI product can't get past hospital security review.
Your model works. The clinicians want it. Procurement still won't approve because deployment would require raw PHI on your infrastructure. SECUVA keeps your scope of data limited to exactly what your model needs - and nothing more.
Compliance,
end-to-end.
SECUVA™ was designed around Australian healthcare law and regulatory expectations from day one - not retrofitted from a US or EU baseline. The Privacy Act, OAIC guidance, and clinical interoperability standards are the engineering brief, not a checklist.
Same agent.
Same audit trail. Every modality.
You do not need a different vendor for each clinical surface. SECUVA™ ships one on-prem agent that handles every data type, governed by one policy engine, recorded in one tamper-evident ledger - whether you started with radiology, expand into genomics, or light up a clinical-AI partnership next quarter.
Most customers begin with a single modality - radiology being the most common entry point - and add others as their data-sharing program matures. The agent, the policy framework, and the audit ledger do not change. New modalities switch on inside the same deployment.
One agent, every modality
The same on-prem agent handles DICOM, HL7, FHIR, VCF and free-text clinical notes. One deployment - every clinical data type covered.
Same governance posture
Policy engine, RBAC, mutually authenticated channels and audit ledger are identical across every solution. No surface-by-surface patchwork.
Single tamper-evident ledger
Every transformation - across every modality, every recipient, every pipeline - lands in one independently verifiable ledger.