Intelligent applications harness industry’s first use of neural networking to empower operators with greater network performance, efficiency and speed to market
Fujitsu’s AI-powered network applications leverage unique neural network modeling plus pre-trained ML models with inherent networking expertise to vastly improve efficiency. With a software architecture compatible with large language model (LLM) technology and generative AI, the applications provide continuous learning and unleash self-healing multivendor networks. This allows greater network automation to reduce problem resolution times, eliminate repetitive tasks, and enable operations to make faster, more accurate decisions.
Fujitsu’s new collection of intelligent network applications helps MNOs quickly investigate network problems and service disruptions. Virtuora IA applies real-time inference to develop a precise analysis of problems, creating multivendor, multidomain ML models that use a neural network to reveal contextual network insights. With the ability to adapt to evolving network behavior, this intelligence translates into proactive action including automated notification processes and remediation. In a recent trial, a Tier 1 MNO was able to sort and understand data from hundreds of thousands of network nodes and end points, reducing thousands of network anomalies into root causes and their locations within minutes.
“Our innovative new AI-powered network applications are part of an expanding portfolio of intelligent software solutions designed to help network operators realize light-touch operations for greater agility, lower TCO and unrivalled performance,” said Greg Manganello, senior vice president of the network software and integration business unit at Fujitsu. “We have combined decades of network operations experience with our extensive AI research to deliver immediate business value within a trusted multivendor network management ecosystem.”
With this new collection of Virtuora Intelligent Applications, Fujitsu is delivering AI-powered applications focused on power savings and network optimization, as well as automated incremental deployment and rollback.
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