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Achieve Network Automation with Real-Time and Big Data Analytics 

Mavenir AI and Analytics solutions help address operator challenges of ensuring end-to-end network visibility, enabling an open network, increasing efficiencies, and achieving closed-loop automation through advanced machine learning algorithms that are designed to analyze and derive inferences from vast amounts of unstructured data.

Gain Actionable Insights with Network Intelligence and EdgeAI

With the cloudification of mobile networks, it becomes essential to automate operational processes utilizing real-time and big data analytics based on advanced Machine Learning algorithms. Mavenir’s AI & Analytics platform delivers extensive insights that are mandatory for Webscale network automation, slice management, security, and many other use cases defined for Industry 4.0 applications (EdgeAI), RAN intelligence, network optimization, predictive maintenance, business intelligence, and security. The Artificial Intelligence/Machine Learning (AI/ML) algorithms are defined with Mavenir’s deep telecom domain expertise while keeping the interfaces standards compliant and the platform open for collaborative innovation.

Mavenir’s next-generation Operations Support System (ngOSS) solution enables CSPs to orchestrate, automate, and efficiently operate existing legacy 4G network infrastructures along with 5G components. The end-to-end, cloud-native, automation framework is standards-based, AI/ML-driven, and vendor-agnostic to drive intelligent network operations.

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AI & Analytics

AI and machine learning in mobile network infrastructure is expected to lower costs and speed new revenue generating service offerings.


Achieve Closed-Loop Automation with an Open and Extensible AI and Analytics Solution

Mavenir’s open and standards compliant interfaces offer flexibility in picking machine learning framework for various AI application development. The vendor agnostic AI/ML with open interfaces and architecture provide an incrementally upgradable and extensible platform that can collate 3GPP, O-RAN, and cloud-native philosophies. Analytics built on a cloud-native platform and enhanced by artificial intelligence and machine learning is encapsulated in Mavenir’s AI and Analytics product portfolio including EdgeAI applications. Massive amounts of data are the fuel for any meaningful AI/ML engine. Mavenir leverages end-to-end telco domain specific data and Analytics systems to deliver intelligence & insights necessary for closed loop automation.

Gain and End-to-End View of the Network Through Unified Analytics & AI/ML

The Analytics solution aggregates data from all segments of the network, such as RAN, Packet Core, IMS, Messaging, Transport, Platform and Devices. This provides the ability to correlate metrics and events across all nodes to create an end-to-end view of the network, flow, or a slice. The algorithms can turn this end-to-end insight into tangible inferences and actionable commands to automate network operations. The solution is based on all open interfaces and APIs allowing it to work with any vendor’s network functions.

Non-RT RAN Intelligent Controller

Mavenir’s non-RT RAN Intelligent Controller (RIC) is a containerized application that uses advanced machine learning algorithms to optimize network performance and train ML models using long term RAN data for dynamic and adaptive policy and control.

EdgeAI

Mavenir’s EdgeAI solution set provides real-time inference capability, such as intelligent video analytics for object detection, facial recognition and other use cases, and the necessary acceleration for mass scale adoption of AR/VR applications and ultra-low latency processing of time-critical sensor feeds from massive number of Industrial IoT devices.

Near-RT RAN Intelligent Controller

Mavenir’s near-RT RAN Intelligent Controller (RIC) is a containerized application that hosts trained AI/ML applications to infer and control O-RAN elements in near-real time.

Network Data Analytics Function (NWDAF)

New data analytics function for 5G networks, NWDAF uses AI/ML algorithms based on the requirements of the consuming network function to make intelligent decisions, improve network performance, maintain high availability, and optimize the network resource.

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