Reducing the global burden of disease through the world's most comprehensive Healthcare Map.
Komodo Health is a premier healthcare technology company that has pioneered the 'Healthcare Map,' a massive, de-identified longitudinal data engine tracking the patient journeys of over 330 million individuals in the United States. In 2026, Komodo Health continues to lead the market by integrating generative AI and predictive modeling directly into its Sentinel and Prism environments. Its technical architecture is built on a massive-scale data warehouse that ingests clinical, claims, lab, and pharmacy data to provide a 360-degree view of healthcare encounters. The platform allows life sciences companies, payers, and providers to identify care gaps, optimize clinical trial recruitment by locating specific patient phenotypes, and enhance commercial strategies through precise provider targeting. By utilizing advanced 'Linkage Logic,' Komodo ensures data integrity and privacy while enabling complex cross-dataset analysis. As the industry moves toward precision medicine, Komodo Health's ability to provide granular, real-time insights into rare disease populations and therapy outcomes positions it as the essential infrastructure for data-driven healthcare decision-making.
A foundational data engine mapping 330M+ de-identified patient lives with longitudinal consistency across payers.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
A cloud-based developer environment for running complex analytics and machine learning models on proprietary data.
An intuitive visualization tool for exploring market trends, patient cohorts, and treatment patterns without SQL knowledge.
A Medical Affairs tool designed to identify and engage Key Opinion Leaders (KOLs) based on clinical influence.
An automated alerting system that identifies 'trigger events' such as a new patient diagnosis or treatment change.
Proprietary tokenization technology that links disparate datasets (claims, lab results, EHR) at the patient level while remaining de-identified.
AI-driven algorithms that identify patients likely to have a rare disease before a formal diagnosis is recorded.
Identifying patients with undiagnosed or misdiagnosed rare conditions to improve therapy uptake.
Registry Updated:2/7/2026
Deploy field teams to provide educational resources to those identified providers.
Choosing trial sites with high concentrations of eligible patients to reduce recruitment timelines.
Demonstrating the value of a new drug to payers for formulary placement.