Run the study across every sponsor, without ever pooling their data.
Sovereign by design: hosted on OVHcloud, infrastructure qualified SecNumCloud 3.2 and HDS-certified. You operate multi-sponsor studies where no one will hand over raw patient data, and rightly so. Polnor runs the same protocol inside each sponsor's own cloud and lets you compare aggregate results. You are the operator, not the custodian.
One protocol, three sponsors, no data ever pooled.
A multi-site study for three sponsors who will not share raw data. You define the cohort once, the same standardized pipeline runs in each environment, and only aggregate counts come back. Not a single patient row leaves any sponsor's cloud.
| site | eligible n | event rate | contributes |
|---|---|---|---|
| Sponsor A | 12,480 | 3.0% | counts only |
| Sponsor B | 9,215 | 2.7% | counts only |
| Sponsor C | 15,902 | 3.4% | counts only |
| pooled estimate | 37,597 | 3.1% | ref |
Illustrative interface and figures, shown to explain the workflow. Not results from a Polnor customer.
Everything up to the cohort is automated.
By the time your team writes that query, the hard part is done: the platform has already ingested, de-identified, standardized and quality-checked your data. You start where the question starts.
Standardized in every environment, so results are comparable
The same automated pipeline runs identically in each sponsor's cloud: FHIR ingestion, GDPR de-identification with the same presets, OMOP conversion and quality control. Because every site is prepared the same way, the aggregate numbers you compare actually mean the same thing.
| source | → OMOP concept | std |
|---|---|---|
| atc:X | ingredient X | S |
| icd10:I26 | Pulmonary embolism | S |
| loinc:718-7 | Hemoglobin | S |
The platform does the plumbing. Your team runs the study.
The repetitive, compliance-heavy work runs itself in every environment, so your study team spends its time on protocol and interpretation, not on reconciling three incompatible datasets.
Nothing to exfiltrate, because you never hold the data.
Each sponsor's environment is isolated: their data never mixes with another's and is never pooled. Every access is logged, PHI is classified, and export follows EHDS-aligned manifests. Because the control plane is health-blind and data stays in each sponsor's SecNumCloud/HDS cloud, there is nothing on your side to leak.
One protocol, every sponsor, no data pooled.
30 minutes: we run the pipeline across a mock multi-sponsor study and show how the same standardized logic executes in each environment while only aggregates come back.