Segmed

Segmed is a vertical data provider focused on medical imaging. Founded by a team of Stanford engineers and physicians, it aggregates de-identified, real-world imaging studies from a network of healthcare providers and makes them accessible for building, training, and validating clinical and diagnostic AI, as well as for pharmaceutical and clinical research.

What they provide

The platform combines a large, growing catalog of imaging data with tooling that compresses the traditionally slow work of preparing medical data. De-identification, standardization, and a cohort builder let teams assemble targeted datasets in days rather than months, with imaging linkable to associated clinical records for richer study designs.

• Segment: Vertical (healthcare) real-world imaging data
• Modalities: Radiology and other medical imaging, plus linked clinical and text data
• Compliance: HIPAA de-identification via independent Expert Determination; ISO 27001 and SOC 2
• Uses: Algorithm development and validation, external control arms, imaging biomarkers

Where it fits in the AI data supply chain

Segmed occupies the domain-specific sourcing layer, solving a bottleneck that generic web or synthetic data cannot: access to compliant, diverse, real patient imaging. Because medical data carries strict privacy and regulatory obligations, its value lies as much in rigorous de-identification and provenance as in volume. Buyers include medical-AI developers, device makers, and life-sciences and pharmaceutical teams that need representative real-world data to train models and demonstrate they generalize across populations and imaging equipment.