AI platform identifying undiagnosed patients in rare and complex conditions
Pangaea Data builds AI software to surface untreated patients (undiagnosed, misdiagnosed, or uncontrolled) within healthcare and pharma systems, focusing on hard-to-diagnose conditions where clinical detection gaps can reach 90% of the population. The tech stack (Python, FastAPI, Next.js, Azure, Kubernetes) and active projects (AI model microservice deployment, healthcare AI module integration, ML/NLP productization) reveal an engineering-first approach to clinical AI. Hiring velocity is decelerating despite 17 open roles, with marketing and research functions scaling alongside engineering—a pattern typical of companies moving from R&D validation into commercialization.
Notable leadership hires: Sales Director
Pangaea Data operates a clinical AI platform that mimics manual clinician workflows to identify patient populations missed by existing diagnostic and coding processes. The company serves healthcare providers and pharmaceutical companies seeking to find and enroll untreated patients into screening and trials. Based in South San Francisco with a London presence, Pangaea was founded in 2017 and remains privately held with 11–50 employees. The product is designed for explainability and minimal disruption to clinical IT systems, with infrastructure managed across Azure and AWS. Current focus spans regulatory pathway preparation, market access strategy, and backend integration work to support a product roadmap centered on scalable AI deployment.
Python, FastAPI, Next.js, Kubernetes, Docker, Azure, AWS, Terraform, and Node.js form the core stack. The engineering footprint emphasizes containerization and infrastructure-as-code automation.
South San Francisco, California, with a secondary office in London. The company actively hires in both the United States and United Kingdom.
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