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ReNOVATE AI: Rejuvenating network build and operations through AI

URN C24.0.664
Topics AI (Artificial Intelligence), Autonomous networks, Fault management

Harnessing the power of AI paradigm and generative AI, Telcos can unlock operational efficiency and move towards a sustainable autonomous network leading to enhanced customer experiences

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In the dynamic telecom landscape driven by evolving customer demands, telcos can tailor customized bundles using existing product components and flexible contract terms in order to monetize available resources. By harnessing the power of GenAI, this solution will empower telcos to build bespoke products, bundles, and networks quickly, strengthening their operational agility and automation, ensuring seamless customer journeys from initial onboarding to continuous service delivery of these agile products. This will enable telcos to address emerging demands such as 5G, edge computing, and value-added bundled services through strategic partnerships with other telcos, hyperscalers, and OEM vendors. We also intend to target the challenges in network operations faced by telcos within their brownfield ecosystems. The exponential scale of network events requires an automated approach to address issues like alarm noise, correlating alarms and events, root-cause analysis for the right-sized assurance outcomes. This solution will enable an industry-standard (TMF ODA)-based framework that will leverage AI-OPS to address such requirements satisfactorily with minimum disruption, leading to OPEX optimization and improved customer experience. The solution approach involves implementing a framework for automated analysis of network events for anomaly detection against pre-defined KPIs and feeding corrective actions into the automation framework to enable a closed-loop operation. This solution will also deliver AI-driven assistance to the operations team in NOC for expedited resolution of network incidents and leverage relevant hyperscaler infrastructure for accelerated development and ubiquitous access. With the help of AI, we will also demonstrate use cases to improve energy efficiency by continuously scanning energy usage metrics leading to selective hibernation of under-utilized network elements and movement away from less efficient networks.

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Aira Technologies Inc logo
Amazon Web Services, Inc. logo
BT Group plc logo
Champion
CloudBlue logo
Cloudsense Ltd. logo
Crown Castle logo
Champion
Deutsche Telekom AG logo
Champion
Econet Wireless Zimbabwe logo
Champion
Infosys logo
Spark New Zealand Limited logo
Champion
VIAVI Solutions logo

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