The real question isn't the price of Polnor, but the cost of going without. You pay for your cloud directly, and Polnor only charges for its added value, with no hidden margin on compute. Rebuilding FHIR ingestion, GDPR anonymization, OMOP and HDS governance in-house ties up scarce teams for months, and a single health-data breach costs $7.42M on average (IBM, Cost of a Data Breach 2025).

Is it safe to entrust your health data?

That's exactly the point, you don't entrust it. That's the health-blind architecture: your data never leaves your cloud, stays in Europe with an HDS-certified host, and the control plane only orchestrates compute without storing any derived data. We never train our models on your data.

Is it complex to set up?

No: the health complexity is already handled. The pipeline is pre-built, you plug in your bucket. From FHIR ingestion to AI-ready cohorts, we're talking weeks, not years.

FHIR · OMOP · AI · sovereign

The health-data platform that never leaves your cloud.

Q: Why not do it in-house?

Your engineers are capable of it, but up to 80% of data scientists' time goes into data preparation (CrowdFlower survey, via Forbes), and health compliance has to be maintained continuously. Polnor frees your teams for what matters: the models, the science.

Ingest FHIR, anonymize (GDPR), structure into OMOP, analyze and train your AI models, in your own cloud, with an HDS-certified host.

Request a demo → See the platform

We keep control.You keep the data.

app.polnor.net / health-prod● health-blind

health_prod › omop › diabetes_cohort.sql

▶ Run-- T2 diabetes cohort · mean blood glucose SELECT person_id, avg(value) AS glucose FROM measurement WHERE concept = 'glucose' AND age > 50 GROUP BY person_id;

results · 12,480 rows0 rows exported ✓

person_id	glucose	n
p_8f3a…	1.42 g/L	36
p_2b71…	1.28 g/L	28
p_c04e…	1.67 g/L	41

FHIR R4 OMOP CDM · OHDSI Apache Iceberg HDS-certified host GDPR · EHDS-ready

$7.42M

average cost of a health-data breach. The most expensive sector, 14 years running.

Source: IBM, Cost of a Data Breach 2025

With Polnor, there's nothing to exfiltrate. Your data never leaves your cloud: our control plane orchestrates processing, but never sees or stores any patient data. Your attack surface isn't ours.

See the health-blind architecture →

What you gain

From data to value, not to the invoice.

The risk avoided

The data doesn't leave your premises: the sector's most expensive breach has nothing to target on Polnor's side. You reduce your attack surface, not your ambition.

The time saved

The FHIR → anonymization → OMOP pipeline is already built. Your data scientists train models instead of flattening FHIR.

Up to 80% of data time goes into preparation, CrowdFlower survey via Forbes.

The budget under control

You pay for your cloud (OVH, Scaleway) directly. Polnor only charges for its added value, with no hidden margin on compute. The money stays with you, just like the data.

The platform

From raw data to model, without switching tools.

Ingestion

Connect your data to the FHIR standard

Patient records, lab results, clinical reports, imported and normalized to FHIR. A $export pull from your server, one clean table per resource.

FHIR connectors + automatic $export pull

One typed table per resource (patients, observations…)

ingestion · fhirbronze

resource	rows	status
Patient	12,480	✓ ready
Observation	1,204,933	✓ ready
Condition	88,210	✓ ready
MedicationRequest	301,774	✓ ready

Anonymization

GDPR de-identification, column by column

What identifies a patient is erased; what serves the science stays. Masking of direct identifiers, stable pseudonyms (linkable to each other), date shifting, age binning.

GDPR-compliant clinical presets, run in your cloud

table · patients

name	ins	birth	dx
Marie Durand	2 85 03…	12/03/1985	E11
Jean Bernard	1 78 11…	30/07/1978	I10
Amina Cherif	2 90 06…	05/06/1990	J45

Structuring

Convert to OMOP, with quality control

"Silver" flattening, conversion to the OMOP CDM (the reference for research worldwide) and automatic clinical quality control, LOINC codes, physiological bounds.

Standardized concept mapping (OHDSI)

omop · mappingsilver → gold

source	→ OMOP concept	std
loinc:2339-0	Glucose [Mass/Vol]	S
icd10:E11	Type 2 diabetes	S
atc:A10BA02	metformin	S

Analytics

Cohorts & SQL, notebooks, feature store

Build cohorts, join lab and clinical data, prepare your features, in SQL or in a notebook, directly on your OMOP tables, in your cloud.

cohort.sql

SELECT person_id, avg(value) glucose
FROM measurement
WHERE concept = 'glucose'
  AND age > 50
GROUP BY person_id;

Artificial intelligence

Train & serve your models, in your cloud

Experiment tracking (MLflow), versioning, API deployment: from cohort to production model, without ever exporting the data.

Training + serving co-located with the data

mlflow · runserved

model	AUC	endpoint
readmission-30d	0.87	/v1/predict
sepsis-early	0.91	/v1/sepsis

Governance & compliance

The traceability healthcare demands, built in.

HDS hosting

Deployed with HDS-certified hosts (OVHcloud, Scaleway). Your cloud, your country.

PHI access log

PHI classification, health-data access log, retention rules. Audit-ready.

EHDS export

Export manifests compliant with the European Health Data Space (EHDS).

Who it's for

Built for those doing AI with health data.

Health AI startups

Ship your model, not your plumbing

Ingestion, anonymization, feature store and serving ready to go. Focus on the algorithm and time-to-model.

Labs & biotech

Your clinical data, in compliance

Cohorts, lab/clinical joins, GDPR de-identification, audit-ready traceability.

Warehouses · CDW

A modern, sovereign clinical data warehouse

FHIR & OMOP, governance, scale, a complete analytics and AI foundation, without lock-in.

The market

An exploding market. A window opening.

The stakes, in figures, for your board as much as your finance leadership.

$187.7B

Global AI in healthcare market by 2030 (+38.5%/yr)

Grand View Research, 2025

$60–110B

Potential annual value of generative AI for pharma and medtech

McKinsey & Company

1.2B+

Real-world patient records already feeding clinical research (RWE)

IQVIA, Real World Evidence

$5.44B

AI diagnostics market by 2030 (+22.5%/yr)

Grand View Research, 2025

Third-party market data, provided as context on the stakes. These are not results achieved by Polnor customers.

Objections

The questions your board is asking.

"It's too expensive."+

The real question isn't the price of Polnor, but the cost of going without. You pay for your cloud directly, and Polnor only charges for its added value, with no hidden margin on compute. On the other side: rebuilding FHIR ingestion, GDPR anonymization, OMOP and HDS governance in-house ties up scarce teams for months, and a single health-data breach costs $7.42M on average (IBM, 2025).

"We don't hand over our health data."+

That's exactly the point, you don't hand it over. That's the health-blind architecture: your data never leaves your cloud, stays in Europe with an HDS-certified host, and our control plane only orchestrates compute without storing any derived data. Encrypted credentials, configurable residency, PHI access log, and we never train our models on your data.

"It's too complex to set up."+

We've already absorbed the health complexity. The pipeline is pre-built: you plug in your bucket, not your team for 18 months. From FHIR ingestion to AI-ready cohorts, we're talking weeks, not years.

"We do it in-house."+

Your engineers are capable of it. But up to 80% of data scientists' time goes into data preparation (CrowdFlower survey, via Forbes), and health compliance has to be maintained continuously: audits, terminologies, traceability. Is that where you want to burn your R&D? Polnor frees your teams for what matters: the models, the science.

"Why not Databricks or a generalist?"+

A generalist made health-compatible isn't built for health: no native FHIR to OMOP, no INS/EMPI, no PHI classification and no compliance designed for Europe, and the cloud stays theirs. With a generalist, you buy back 12 to 18 months of integration; with Polnor, it's the product, and you remain the owner AND operator of your data.

Ready to start?

Deploy Polnor in your cloud.

Book a demo: we start from your data and you leave with a complete FHIR → anonymized → OMOP → analytics → AI flow, in your cloud.

Request a demo → Revisit the platform