One of our biggest clients that has already extended its team with us is SIEMENS Gamesa RENEWABLE ENERGY.

“Siemens Gamesa is a leading supplier of wind power solutions to customers all over the globe.
A key player and innovative pioneer in the renewable energy sector, we have installed products and technology in more than 90 countries, with a total capacity base of over 84 GW and 25,000 employees.”

Country: Denmark
Field: Industrial Asset Management
Technology: Microservices, AWS, JavaScript .NET, Python, Deep Learning
Keywords: Visual Industrial Assets Inspection, Asset Condition Monitoring, Cloud Based, AI, Data Driven Decision Making, Predictive Maintenance
Business overview: Platform has been designed to improve and digitalize company’s specific processes in domain of asset management, automate manual and repetitive work, optimize costs and predict risks using cutting edge AI technology.
Tech overview: Industrial Assets Management platform was initially designed as a monolithic application developed mainly in .NET technologies. Due to the large scaling requirements and the growing complexity of the business processes and logic, the platform has been migrated into microservices architecture leveraging cloud specific services. Microservices communicate either directly (using REST) or using event-sourcing mechanisms. Services are being packed into Docker containers which are scalable and orchestrated using different cloud specific services. Core platform parts are integrated with the Machine Learning services which are implemented as Serverless functions and services into Docker containers. The persistence storage is mainly the SQL and NoSQL databases as well as cloud specific storage. Primary framework for developing microservices is .NET Core and NodeJS. For the frontend part, we mainly use Angular, React/Redux. The entire platform is can be hosted on Amazon Web Services (AWS) and Microsoft Azure cloud platform.

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