As the world grows, concerns over pollution and climate change are forcing businesses to redesign how they produce and use energy. A notable approach for achieving this objective is through informing end users of their power usage patterns. Learn how IBM’s anomaly detection solution for energy and utilities helps companies increase energy efficiency leveraging a personalized AI paradigm and to calculate ESG metrics related to energy consumption.
Energy and process manufacturers are looking for mechanisms to predict asset breakdowns well before actual asset failure. Learn how Flutura’s solution, Cerebra, addresses these challenges by using a strong data foundation, collecting and processing data from a variety of assets at scale. Cerebra employs AI/ML models along with scalable AWS services to mitigate unplanned downtime, optimize asset performance, and improve asset reliability.
Optimizing Energy Footprint with Edge Analytics and Artificial Intelligence of Things with Bosch Phantom
Energy and asset monitoring is becoming an essential part of business. Organizational strategies include environmental, social, and governance (ESG) criteria in its framework to decrease energy consumption and, at the same time, boost efficiency. Learn how Bosch is solving this problem with the help of edge analytics, machine learning, and core Internet of Things (IoT) components provided by AWS, and how Bosch Phantom helps to extract information using a non-intrusive approach.
AWS Partners represent a variety of geographies, backgrounds, and interests. With a network so widespread, AWS collaborates with businesses that excel in providing value-added services to customers from varied industries, including healthcare and life sciences, travel and hospitality, financial services, energy and utilities, media and entertainment, automotive, education, and more. Our industry-focused approach leverages specialized expertise and purpose-built solutions to help partners transform with AWS and solve the challenges facing various markets.
While utilities have historically been rich with data from customers, programs, and assets, many organizations often manage data in siloes. Source data can also be disorganized, with deficiencies in defined quality assurance and quality control processes. Learn how utilities are successfully embracing Accenture’s data-led transformation (DLT) and leveraging accelerators powered by AWS to reach their business objectives and meet regulatory obligations.
Procure-to-pay automation often creates data silos which cause new problems and inefficiencies. Businesses need to break down data silos for a complete picture of spending and saving enterprise-wide. It’s time to reimagine the procure-to-pay process with a data-driven and fact-based approach. Learn how Genpact and AWS helped a Fortune 500 energy giant transform its procure-to-pay business, delivering savings of over $100 million in the first year alone.
Wipro moved Schneider Electric’s crucial on-premises SAP system onto AWS, completely re-architecting the system for the cloud, changing the operating system, upgrading databases, and migrating terabytes of data to AWS. The partner and customer both sought a goal larger than reducing the physical data center footprint: they aimed to improve digital supply chain operations and enhance the performance of Schneider Electric’s industrial automation business.
AWS is committed to supporting the global energy industry in safely meeting the energy demands of the world today, while accelerating the industry’s transition to a more balanced and sustainable energy future. The new AWS Energy Competency Program differentiates highly specialized partners who have demonstrated technical expertise and repeat customer success. These AWS Partners enable energy producers to build and operate assets efficiently and safely, while working to transition to a lower carbon world.
Re-Architecting the Application Journey to Cloud-Native Using an AWS Services-Based API Factory Model and Jump-Start Kit
A Tech Mahindra customer had a vision for cloud adoption and API development in a multi-cloud environment. They wanted to transition all appropriate old and new applications to an event-driven architecture while moving away from trigger-based synchronization of data between the different systems. Learn about the key aspects of Tech Mahindra’s API Factory Model and how it was used for re-architecting the customer’s on-premises application to a cloud-native application.