Training data for medical AI

The data layer
medical AI is missing.

High-quality, clinically validated, demographically representative training data — plus the team to clean, enhance, and augment the data you already have. So you can focus on building safer, more impactful models.

  • MultimodalEHR · imaging · biosignals · omics
  • Regulator-readyHIPAA · IRB · EU AI Act
  • Expert-labeledClinicians, not crowd-workers
What we deliver

Two ways we close your data gap.

Frontier models can recite a drug's chemistry yet fail to complete an EHR note or triage a complex case the way a clinician would. The missing ingredient is clinically grounded human signal at scale — delivered, or repaired, to spec.

01 High-quality clinical training data

Curated, expert-labeled, bias-audited, and delivered with the provenance and demographic coverage your regulators will accept.

  • Labeled by practicing clinicians — quality bounded to clinical standards
  • Demographically representative across skin tone, sex, age, and physiology
  • Multimodal: EHR, imaging, omics, and waveform data
  • Provenance + consent documentation for every record
02 Dataset remediation & enhancement

We take the messy, narrow, mislabeled data you already hold and clean, augment, and rebalance it into something a model can safely train on.

  • Audit of demographic coverage, label quality, and edge-case failure modes
  • Versioned, enhanced datasets + validation reports your team owns
  • Edge-case and adversarial generation grounded in real clinical workflows
  • Expert-in-the-loop evaluation and benchmarking for production models
  • EHR
  • Imaging
  • Biosignals & waveform
  • Omics
Trust, safety & compliance

Handling clinical data is a trust exercise.

Our operating model is designed around that from day one — so the data you train on is defensible to your regulators.

HIPAA-aligned pipelines

De-identification and access controls across every workflow.

Provenance & consent

Documented consent chains and source traceability for every record delivered.

Secure data access

Data-residency and privacy compliance for international customers and datasets.

Expert oversight

Independent clinical and regulatory advisors review dataset design and validation.

Honest limitations

We document what the data cannot do — not just what it can.

Healthcare-only focus

One vertical, clinical depth. We don't moonlight in a dozen others.

Tell us the data gap you're trying to close.

Share the clinical use case you're building toward and where you are in the regulatory pathway. In weeks, you can fill a data gap — or get an independent read on where your data and model stand against clinical and regulatory expectations.

Talk to us → hello@carmenta.io