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Leveraging AI, automation and the power of data, the Ericsson Operations Engine is rewriting the rules of network operations. Our customer data-driven insights enable you to analyze, understand, and transform your network like never before, while helping you to reduce costs and time to market for innovative services.

Redefine customer experience in realtime

The Ericsson Operations Engine helps you to deliver a superior customer experience. By combining deep domain expertise with advanced technologies like AI and machine learning, the Ericsson Operations Engine provides the performance, reliability, and flexibility to meet the dynamic needs of consumers and enterprises.

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Ericsson Operation Engine podcast series

Featuring industry experts and engineers managing the next-generation of networks, Ericsson Operations Engine limited podcast series provides a first-hand look into the operations, customer experiences, and collaborative innovation meeting the challenges of tomorrow.

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In 2019, change is coming

The Ericsson Operations Engine is rewriting the rules of network operations through artificial intelligence, automation, and the power of data. It's designed to help operators manage the networks of the future, grow revenue and accelerate service innovation. And that's just the start.
The official launch is set for the Mobile World Congress in February.

Highlights

Swisscom receives highest score ever recorded in Connect test

Thanks to its partnership with Ericsson (NASDAQ: ERIC), Swisscom not only won Switzerland's 2018 connect mobile network test but also received the highest score ever recorded in a test of this type – 973 out of a maximum 1,000 points.

Ericsson pioneers machine learning network design for SoftBank

SoftBank Corp. ("SoftBank"), a leading mobile operator in Japan, has implemented an innovative method for radio access network design from Ericsson (NASDAQ: ERIC), based on machine intelligence. The service groups cells in clusters and takes statistics from cell overlapping and potential to use carrier aggregation between cells into account, thus reducing operational expenditure and improving network performance. Compared to traditional network design methods, it cut the lead time by 40 percent.

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