Research flourishes when ideas flow naturally into evidence, and each discovery builds on the last. AIR·MS has been created to bring this vision to life —a platform where data, analysis, and collaboration converge effortlessly, providing Mount Sinai with a single environment in which complex research can be conducted with clarity, efficiency, and speed.
At its core, AIR·MS combines clinical records, imaging, signals, and other research data in one unified system designed for both scale and performance. Large datasets reside in memory, allowing analyses to be performed interactively and iteratively. By supporting both relational and graph-based approaches, AIR·MS captures the richness of clinical and biological relationships, enabling researchers to explore questions in a manner that more closely reflects the real world.
As the platform has matured, usability has emerged as a defining strength. The introduction of Data2Evidence represents a step change in how researchers engage with AIR·MS. It allows users to progress from research questions to structured, verifiable results through intuitive workflows that promote exploration, validation, and iteration. Analyses that once required considerable technical intervention can now be performed directly, enabling researchers to focus on insight rather than mechanics.
Complementing this, a conversational assistant provides a natural interface for understanding the data that exists within AIR·MS and how different sources may be combined. Users can navigate the platform with confidence and collaborate seamlessly across disciplines, fostering a richer research experience. Advanced analysis is transformed into a natural extension of the researcher’s thinking, rather than a separate technical exercise.
Another strength of AIR·MS lies in its treatment of data. Datasets deposited within the platform are standardized according to the Observational Medical Outcomes Partnership common data model, ensuring they are ready for reuse, integration, and extension. Clinical data from the Mount Sinai Data Warehouse sits alongside digital pathology metadata, electrocardiogram waveforms, and other modalities, with additional sources continuously added. Contributions gain longevity and reach, allowing researchers to build upon existing work and generate insights that span specialties.
For those who contribute, the benefits are tangible. Data within AIR·MS is secure, well governed, and immediately available for future studies. It facilitates collaboration, strengthens provenance, and provides a firm foundation for high-quality publications and funding opportunities. The time and care invested in collecting and curating data is rewarded through enduring scientific value and broader impact.
Looking ahead, the ambition is clear: by December 2026, AIR·MS aims to support a community of one thousand users, attracted by the platform’s elegance, utility, and reliability. It will be the space where researchers choose to begin their work —not because they must, but because it is the natural and sensible starting point.
AIR·MS does not seek to impress through noise or complexity. Its strength lies in its quiet confidence, in the seamless integration of data and tools, and in the way it supports the highest standards of research at Mount Sinai. It is a platform built not for today alone, but for discovery that endures.
