Briya named a finalist in the 2026 Fierce AI Innovation Awards. The 2026 Fierce AI Innovation Awards have named Briya a finalist in the AI Innovation in Data Interoperability category. The Fierce AI Innovation Awards recognize organizations that move beyond simple AI pilots and deliver measurable results. A panel of industry leaders and expert judges evaluates each entry. They consider five criteria: innovation, impact, execution, scalability, and industry relevance. This recognition highlights Briya AIRE, a clinical-grade AI research environment. AIRE helps researchers turn questions into research-ready evidence using natural language. Briya joins Benchling AI, IMO Health, and Innovaccer as a finalist in the category. Fierce Life Sciences presents the awards as part of Questex's healthcare and life sciences portfolio. Fierce Life Sciences also publishes Fierce Biotech, Fierce Pharma, and Fierce Healthcare. Through these publications, events, and awards, Fierce provides news and analysis for healthcare, biotechnology, and pharmaceutical professionals. Why is healthcare data hard to use for research? Healthcare data is fragmented across EHRs, clinical research systems, public datasets, enterprise platforms, and unstructured medical documents. It is one of the world's most valuable resources for advancing medical research, yet much of it sits in systems that were never designed to work together. Data interoperability involves more than moving information between systems. Researchers must also connect, harmonize, and understand the data. Moreover, they need to trace each result back to its source and prepare the data for scientifically valid analysis. Before researchers can generate real-world evidence or build patient cohorts, they often spend months locating data, navigating privacy requirements, harmonizing different formats, defining study populations, and preparing information for analysis. These barriers make research slower, more expensive, and less accessible to smaller organizations. How does Briya AIRE make healthcare data research-ready? Briya AIRE was built to address these challenges. AIRE enables researchers to move from a question to research-ready evidence using natural language. Its suite of epidemiologist-designed AI agents helps researchers define study populations, explore and analyze healthcare data, build patient cohorts and comparison groups, and create transparent, reproducible reports. AIRE provides a federated research layer across complex healthcare data, meaning analysis runs where the data lives rather than requiring patient records to be moved or centralized. That layer spans structured records as well as the valuable information found in physician notes, pathology reports, and other clinical free text. Every study population and analysis remains transparent and inspectable, allowing researchers to understand how results were generated and reproduce their work. By connecting fragmented data and automating the most time-consuming stages of research, AIRE enables scientists and healthcare professionals to move through the research lifecycle with greater speed and confidence, from epidemiological studies to clinical trial feasibility assessments. For individual researchers and students, Briya also offers a free version of AIRE with access to public health datasets such as the Behavioral Risk Factor Surveillance System (BRFSS). These datasets have long been available online, but downloading them, querying them, and harmonizing fields that change from year to year can take a researcher weeks. In AIRE, the same work can be done in minutes using just natural language.

Modular Medical has launched a strategic pilot with IMO Health to develop a system that identifies diabetes patients who may benefit from insulin pump therapy directly within electronic health records. The pilot combines clinician-guided phenotypes with IMO Health's terminology identifiers to help doctors easily find patients likely to benefit from Modular Medical's Pivot tubeless patch pump. The collaboration aims to surface multiple-daily-injection patients who exhibit characteristics associated with insulin pump hesitancy or prior pump failure. IMO Health will translate clinical characteristics into validated terminology value sets that capture physician intent when documenting symptoms and diagnoses. Modular Medical will pilot this initiative with a large-scale diabetes centre as part of preparations for the expected fourth quarter commercial launch of the Pivot pump. The pilot will establish a scalable framework for multi-site deployment across diverse health-system environments.

IMO Health has launched direct access to its Clinical Knowledge Graph, enabling healthcare organisations and developers to build AI systems using clinically accurate data. The graph provides a semantic layer that anchors AI reasoning in consistent clinical truth, addressing a common failure point in enterprise healthcare AI. Built on terminology used by over 90% of US clinicians and present in 97% of patient encounters, the knowledge graph processes 12 billion terminology search transactions annually across 4,500+ provider organisations. It reflects real-world documentation patterns rather than static code sets. Developers can now integrate this clinical context through a GraphQL API and MCP Server tools. The system supports applications including ambient documentation, clinical decision support, revenue cycle automation and population health analytics. The graph is maintained by over 50 clinical informaticists and coding experts.