In a strategic move to bolster its vertical AI strategy for asset-intensive industries, HubHead Corp. announced today its acquisition of the assets of DataSeer, Inc. The acquisition adds to HubHead’s portfolio of tools focused on using AI and machine learning to improve asset and maintenance master data and assisting asset-intensive businesses in digitizing data to create digital twins. HubHead’s software improves the effectiveness of our customers’ Enterprise Asset Management (EAM) and CMMS solutions.
As a frontrunner in the application of AI to enhance asset and maintenance master data quality, HubHead is dedicated to collaborating with customers to provide innovative software-as-a-service (SaaS) solutions. AI makes it easier for asset-intensive businesses to ensure their maintenance and operations, and EAM solutions are more efficient, reliable, and prepared for future initiatives.
Greg Dee, CEO of HubHead, emphasized the importance of AI tools to create the asset and maintenance master data foundation needed for operational effectiveness. “At HubHead, we’re driven by the belief that high-quality asset and maintenance data is the cornerstone of EAM effectiveness and is required for effective asset management,” Dee said. “Our strategy focuses on employing AI to enhance the quality and completeness of asset data for our clients. DataSeer is crucial for unlocking the full potential of AI in their industries, enabling critical applications such as digital twins, predictive maintenance, and IoT implementations.”
HubHead has used DataSeer with its NRX AssetHub solution to extract engineering tags from P&IDs to help customers cost-effectively build high-quality EAM/CMMS data. It is used to create digital twins, adopt industry standards like ISO 14224, prepare for operational readiness at new capital projects, enhance asset and maintenance master data prior to migrating or upgrading to new EAM/CMMS solutions, and other applications that create the foundation for operational excellence.
HubHead will offer the DataSeer SaaS solution to engineering firms, system integrators (SIs), EPCs, asset-intensive businesses, and others with a need to scrape P&IDs to extract high-quality actionable asset data.
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#MachineLearning [Source: AI Techpark]