The Key Exploitable Results of the FAIR-EASE project provide a transformative approach to multidisciplinary environmental research by integrating distributed data discovery, access, and processing services into a seamless and FAIR-compliant ecosystem. Designed to benefit scientists, policymakers, research infrastructures, and industry stakeholders, these results include tools, real-world pilots and advanced environmental processing services that enhance data interoperability, visualisation, and analytics. FAIR-EASE fosters cross-disciplinary collaboration by bridging Earth system, biodiversity, and environmental sciences, ensuring that data from diverse sources—ranging from satellite observations to in-situ measurements and omics experiments—are more easily discoverable, accessible, and reusable. Through its strong alignment with EOSC, the project advances Open Science by implementing FAIR principles across multiple research domains, enabling high-performance computing, machine learning applications, and real-world use cases in areas such as climate change, food security, and environmental monitoring.