Aligned medical imaging intelligence for the teams building health AI.
BodyMaps is the intelligence layer underneath medical imaging AI. We turn fragmented clinical imaging into model-ready evidence — paired with reports, regions, and longitudinal context — and use the same foundation for the algorithms and agentic systems we build with our partners.
Health AI is data-bound. Real medical imaging is hard to get.
Foundation-model labs and hyperscalers building health AI run into the same wall: high-quality, de-identified, expertly-annotated medical imaging — paired with the reports, regions, and longitudinal context that make it learnable — is scarce, slow, and operationally expensive to produce.
Multimodal medical imaging, made trainable.
We deliver de-identified imaging volumes paired with structured reports, expert annotations, region grounding, and longitudinal links — the agreement region between modalities, made trainable. Datasets are versioned, evaluated, and shipped with the provenance frontier labs expect.
The team and tooling to actually do this.
Our founders have spent careers in medical imaging AI, with peer-reviewed publications and shipped systems behind them. Backed by expert radiologist annotators, an in-house de-identification stack, synthetic data generators, and auto-labeling with active learning — we curate at the scale and quality frontier models require.
Operators across the platform’s five layers.
Foundation-model teams, research labs, and clinical partners come to us when one-off datasets or a labeling marketplace won’t cut it. We’re operators with publication track records and shipped clinical AI systems across the platform’s full stack.
Founders with deep medical imaging AI track records.
Years of peer-reviewed publications, shipped clinical AI systems, and direct radiology-AI experience — the judgment to build across the platform’s five layers, and the relationships to source the data behind them.
A real platform, not a labeling marketplace.
In-house de-identification, expert radiologist annotation with QA, synthetic generation, multimodal alignment, and a shared evaluation harness — applied across the platform’s stack, not contracted out. Scale without sacrificing ground truth.
A platform that compounds.
Today we ship custom imaging cohorts. Tomorrow, the same foundation powers our multimodal models and agentic workflows — same schemas, same evaluation, same provenance. Each layer makes the next stronger.