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The transformative role of cloud computing and AI is accelerating in asset-intensive industries as collaborations across solution-provider ecosystems expand. ARC Advisory Group finds that the essential role of platforms for optimal industrial data fabrics is exemplified by recent developments from AWS (Amazon Web Services) and Hexagon.
AWS and Hexagon have partnered to enable the rapid adoption of industry-specific Enterprise Asset Management (EAM) solutions tailored for asset-intensive sectors, including energy, utilities, manufacturing, and transportation, delivering highly secure, AI-driven insights and process improvements
To realize the full potential of AI, industrial data fabrics require platforms that not only optimize insights for specialized use cases but also de-silo data-centric workflows. Such platform-based optimization fosters greater cross-functional collaboration and provides deeper, more scalable, and more secure insights.
The growing volume and variety of real-time data from utilities’ operations and maintenance activities create opportunities for improved management. This data includes text, numerical sensor readings, and visual media from sources such as drones and cameras. Effectively managing this data has spurred rapid development of new platforms.
In the past, limited computational resources hindered scalable and cost-effective deployments of these capabilities. Creating digital twins from spatial data demands significant computational power, which increases with model size and data complexity—both of which are growing exponentially. Storage and access requirements are also challenging, as files can range from gigabytes to terabytes or even petabytes. Additionally, data capture teams and construction professionals are often in different locations, requiring remote collaboration with access to these massive datasets for visualization and analysis.
As part of its AWS partnership strategy, Hexagon leverages Amazon Bedrock Data Automation to create specialized AI solutions. This includes the launch of HxGN Alix, an AI assistant for Enterprise Asset Management built on Amazon Bedrock.
HxGN Alix is among the enhancements introduced in Hexagon’s latest EAM release, HxGN EAM 12.2. It is designed to provide step-by-step guidance for managing assets, creating work orders, and generating reports. By supporting both foundational and advanced EAM use cases, it enables users to be more self-sufficient. It also allows end users to generate new code in languages such as Python, JavaScript, and Java, with security protocols in place to protect sensitive data.
Many EAM workflows and asset models depend on Geospatial Information Systems (GIS) and digital twins—an area where Hexagon’s HxDR plays a pivotal role.
Hexagon's HxDR: Digital Reality Visualization on AWS Cloud
HxDR uses sensor data—airborne, ground, and mobile—such as LiDAR and photogrammetry to create digital representations of physical locations. These “digital twins” support project design and 3D visualization while addressing the computational and storage demands of creating such models. For example, a handheld imaging laser scanner like the BLK2GO can produce large files (averaging 5 GB) that are uploaded to Amazon S3. HxDR then uses these files and AWS services to create integrated views, enabling remote collaboration.
AWS provides the collaboration-enabling infrastructure needed to manage the complexities of industrial data fabrics. Its tools for building platforms and storage services, combined with elastic compute cloud capabilities, allow resources to be allocated on demand—eliminating the need for local resource pools or lengthy approval processes.
In conclusion, the partnership between AWS and Hexagon illustrates key trends in optimizing platforms that support industrial data fabrics. Their initiatives—and similar efforts—are enabling Enterprise Asset Management and Digital Twin benefits to be realized in deeper ways, driving digital transformation, improving operational efficiency, enhancing safety and reliability, and reducing costs.