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Private Company

Total funding raised: $2M

Overview

Segmed operates a technology-enabled data platform that aggregates and provides structured, de-identified medical imaging data from a diverse, global network of over 2,800 healthcare sites, encompassing more than 150 million imaging studies. The company serves pharmaceutical, medical device, and AI developers by offering fit-for-purpose datasets for R&D, algorithm training, and regulatory validation, with its data having contributed to over 45 FDA-cleared products. As a private, revenue-generating platform company, Segmed addresses critical bottlenecks in medical AI development by ensuring data diversity, quality, and regulatory compliance, positioning itself as a key infrastructure provider in the growing real-world data ecosystem.

AI / Machine Learning

Technology Platform

Proprietary self-serve platform (Openda) for aggregating, de-identifying, structuring, and providing query-based access to millions of regulatory-grade, multimodal medical imaging studies and associated data from a global network of healthcare providers.

Funding History

1
Total raised:$2M
Seed$2M

Opportunities

The massive growth in AI/ML for medical imaging and the regulatory acceptance of real-world evidence create a large, expanding market for high-quality, regulatory-grade data.
Partnerships with large tech-life science firms (e.g., Verily) provide significant channels for scaling distribution and embedding Segmed's data into broader research workflows.

Risk Factors

The business model depends on continuously scaling a network of healthcare data partners amid potential regulatory hurdles and competitive pressure.
Any failure in data de-identification or security could lead to catastrophic reputational and legal damage.
Intensifying competition from other data aggregators and internal hospital AI initiatives poses a market threat.

Competitive Landscape

Segmed competes with other medical imaging data brokers (e.g., Flywheel, MD.ai partners), large contract research organizations (CROs) with data divisions, and direct collaborations between AI developers and hospital systems. Its differentiation lies in its self-serve platform focus, emphasis on regulatory-grade data for product clearance, and its large, diverse, and instantly queryable dataset.