Building in-house costs $300K–$500K/year and 6–12 months. We're a fraction of that, ready on day one.
For individuals evaluating datasets and exploring the catalog.
For ML engineers and data scientists building biomedical AI models.
For pharma, biotech, and health systems with bespoke data needs.
Yes. Every dataset tagged "Commercial" comes with a cleared commercial license. Research-only datasets require academic or non-commercial use.
Parquet (default, ML-ready), JSON/JSONL, and CSV. HuggingFace Datasets format available on Builder and Enterprise.
Yes. Provenance reports include source institution, curation methodology, known limitations, and audit trail — meeting FDA data governance requirements for AI/ML submissions.
3–10× cost savings vs. hiring in-house ($300K–$500K/yr). 6–12 months faster. We handle license clearing, schema normalization, quality scoring, and provenance documentation you can't easily produce internally.
Start with the free Explorer plan. Upgrade when you're ready to ship.