EMERALDS undertakes the development of an Extreme Scale Urban Mobility Data Analytics as a Service Toolset comprising of reusable tools capable of collecting, processing, analysing and visualizing synchronous and asynchronous batch or stream datasets from multiple heterogeneous resources meantime performing data, AI/ML and DevOps tasks across distributed computing resources covering the entirety of the Computing Continuum. In this direction, a testbed and proof-of-concept environment for the tools, methods, algorithms and software solutions developed in WP3 and WP4, with dedicated DevOps, security and data governance and visual analytics solutions from WP2, is facilitated through the acclaimed CARTO geospatial analytics cloud-native platform. This interaction captures drastically the dynamics of a software development and engineering process in the light of the extreme characteristics of modern mobility data analytics from multiple heterogeneous types of data sources. As a technology integration procedure, the activities within T2.2 pinpoint the as-a service value chain interdependencies in a pragmatic scale of contemporary data science innovation amidst the evolving disruptive data economy ecosystem. D2.4 entitled “Demonstration of integrated services (EMERALDS) v1”is of type “OTHER”, thereby, in addition to the explanations in the text supported by tables and figures, it includes a multitude of technical hyperlinks to other sources. These hyperlinks direct readers to relevant images, code snippets, software code in repositories (such as the central EMERALDS repo) and additional resources, enhancing the overall understanding and engagement with the content. The deliverable presents the initial incorporation of the tools developed in EMERALDS within the CARTO platform. The collaboration has driven significant innovations within CARTO, leveraging advanced AI and ML algorithms created by EMERALDS to enhance geospatial analysis capabilities, bringing to light the best of both worlds juxtaposing the academic and research world with the industry perspectives. As a result, EMERALDS advancements have led to the development of different components and products in the CARTO platform. Moreover, the competencies of novel standards in storing and encoding geospatial data in vector tiles are explored, laying the ground for EMERALDS standardization outputs. Key standards investigated include the MapboxVectorTiles and GeoParquet standards, with a thorough assessment of their potential in visualising extreme scale geospatial data.