Care Intel exists to solve a fundamental problem in modern healthcare: critical clinical, biomedical, and market intelligence remains fragmented, opaque, and disconnected. Decisions that impact patient outcomes, clinical research, and healthcare economics are too often made using incomplete or siloed data.
We built Care Intel to change that reality — by unifying the world’s most important healthcare datasets into a single, transparent intelligence layer powered by a clinical knowledge graph.
Our mission is to enable faster, smarter, and more confident healthcare decisions by transforming complex clinical and biomedical data into connected, actionable intelligence.
We believe healthcare intelligence should not be locked inside black-box systems. It should be explainable, traceable, and grounded in real clinical and scientific evidence.
Care Intel’s platform is built on a simple but powerful principle: healthcare data is inherently relational.
Diseases relate to symptoms. Symptoms relate to diagnostics. Diagnostics relate to treatments. Treatments relate to outcomes, providers, facilities, and clinical research.
Instead of forcing these relationships into flat tables or keyword searches, Care Intel models healthcare as it actually exists — as a living network of clinical and biological knowledge.
Care Intel is designed for organizations that operate at the intersection of clinical care, biomedical research, and healthcare markets.
Our customers include healthcare providers seeking visibility into performance and network dynamics, life sciences companies optimizing clinical development and market access, and payers and public health organizations analyzing population-level trends.
We are committed to accuracy, interoperability, and continuous evolution. As new data sources emerge and clinical knowledge advances, Care Intel is architected to grow — without rework, without reinvention, and without sacrificing trust.
We do not simply aggregate data. We curate, normalize, and connect it — so every insight can be traced back to its clinical or scientific foundation.