Speed to Value in Asset Performance with Azure AI: A case study on EPAM and Baker Hughes
Companies like Baker Hughes encounter lagging time-to-value issues because of challenges in data processing, integration of SAP S/4Hana environments and in the processing of unstructured text files, thus requiring intensive training on asset strategy for non-reliability engineers. Working with EPAM, and leveraging AI tools, Baker Hughes is driving new features and functionality for Cordant Asset Strategy software, offering nimble functionality to swiftly deliver and demonstrate value to all potential users regardless of their technical background. This has resulted in the transformation of enterprise asset management efficiency, in smarter, faster data integration and actionable business insights for improved asset performance strategy.
Key learnings:
- Implement Generative AI tools to enhance asset strategy decisions and operations.
- Leverage advanced Azure AI toolsets to streamline processes and enhance asset strategy efficiency.
- Streamline data processing using Azure Data Factory in SAP S/4Hana environments.
- Advantages of integrating computer vision for accurate analysis and management of Piping & Instrumentation Documentation.
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