Machine Learning

RADCOM extends collaboration with Rakuten Mobile

Expanding collaboration to include advanced AI-powered end-to-end network analytics to maintain efficient network operations and network automation

RADCOM Ltd. (Nasdaq: RDCM) today announced it has renewed its multi-year collaboration with Rakuten Mobile Inc. The company will continue to provide current solution offerings, and the collaboration will include advanced artificial intelligence (AI)– powered analytics such as anomaly detection and automated root cause analysis. These AI-driven use cases help proactively identify and prevent degradations, enabling Rakuten Mobile to maintain quality of service and drive efficient network operations and network automation monitoring.

Rami Amit, chief technology officer of RADCOM, commented, “We are excited to sign this renewed contract with Rakuten Mobile as our close partnership continues. Our advanced, innovative assurance solution allows Rakuten Mobile to leverage the power of AI/ML insights to gain end-to-end visibility across their network and drive automation to ensure unparalleled focus on service quality, fast detection of potential issues, and efficient network operations.”

“RADCOM has been a reliable partner for Rakuten Mobile, and we’re excited to expand on our collaboration to include AI-driven service and network analytics critical for monitoring our customer experiences in real-time,” said Hiroshi Takeshita, deputy chief technology officer and head of network operations at Rakuten Mobile.

RADCOM ACE applies advanced AI/machine learning (ML) -based analytics to data collected and analyzed from the radio access network (RAN) to the core for automated assurance. It automates telco-specific workflows while providing a range of use cases to multiple teams to drive quality and improve operation efficiencies. For the network operations centers (NOCs), it includes anomaly detection across various services, such as roaming, Voice over Long-Term Evolution (VoLTE), and video streaming, to detect and alert teams about anomalies quickly. Core engineers gain alerts to trace analytics to investigate degradations. RAN teams can utilize the power of automated root cause analysis, which classifies the problems so specific teams can handle issues related to their expertise, thus saving valuable time and resources.   

As a cloud-native solution that includes our container-based cTap for efficient load-balancing and traffic management, RADCOM ACE is automated and modular. An automated Continuous Development/Continuous Integration (CI/CD) software development pipeline enables the solution to be continually updated and tested with no downtime, ensuring services are monitored 24/7 and mobile customers receive top-quality services.

Explore AITechPark for the latest advancements in AI, IOT, Cybersecurity, AITech News, and insightful updates from industry experts!

Related posts

Mark Sokol Joins the FiberSense Board as a Director

PR Newswire

ECGenius System to be Featured at AF Symposium 2023

PR Newswire

SolarWinds Announces Launch of SolarWinds Observability

Business Wire