RecordsKnow when your FHIR data breaks — before it reaches production.
Records runs next to your FHIR server. It validates your data continuously, catches drift before it reaches production, and produces auditable proof for every release.
Built for FHIR platform teams, hospital IT, and health data integration leads.
The problem no FHIR server solves
FHIR implementations pass validation on day one. Then they drift.
No Proof of Quality
You hope your data is compliant, but you can't prove it to auditors or partners.
A terminology server update changes 200 codings. Nobody notices for 3 weeks.
Upgrades Break Things Silently
Updating your FHIR server or validator is scary because you don't know what might break.
HAPI Validator v6.3 → v6.4 produces different results for identical resources.
Environments Drift Apart
Dev works, Staging is okay, Prod is failing. Nobody knows why.
Dev validates with R4@1.4.0, Prod runs R4@1.5.0 — different constraints, silent failures.
How it works
Three steps. No migration required.
Connect
Point at your FHIR endpoint.
Read-only via GET/HEAD — nothing changes in your infrastructure.
Validate
Run profiles, terminologies, and custom rules.
Every run produces a deterministic PASS / WARN / FAIL signal.
Evidence
Compare, detect drift, produce proof.
Reproducible evidence for audits, releases, and handovers.
Records is not a server. It observes yours.
Zero interference. Engineered for strict healthcare compliance and data privacy.
Read-only
GET/HEAD only. No write operations to your infrastructure.
No PHI stored
Only IDs, metadata, and validation outputs. No clinical payloads.
No authority
Produces evidence signals. Never blocks deployments or applies policy.
Vendor-neutral
Works with any FHIR R4/R5 server. No platform lock-in.
EU-based infrastructure
Hosted securely in Frankfurt. Fully GDPR compliant with strict data sovereignty.
On-prem available
Deploy within your own VPC or bare-metal infrastructure for maximum control.
When You Use Records
Five concrete scenarios where Records produces the evidence you need.
Validate before every IG update, server upgrade, or mapping change hits production
Compare current validation state against your baseline — catch new errors the moment they appear
Drill down from high-level metrics to specific JSON resources and pinpoint the exact errors
Produce auditable proof of validation state for vendor deliveries and system migrations
Diff validation results across environments and servers to find alignment gaps
Your FHIR server stores data. Who validates it?
We'll connect Records to your FHIR server and run a validation — live, in 30 minutes. No slides, no sandbox.