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