TEL AVIV, Israel – August 5, 2021 − RADCOM Ltd. (Nasdaq: RDCM) today unveiled a new Artificial Intelligence (AI) solution as part of its automated 5G assurance product – RADCOM ACE. Using Machine Learning (ML), RADCOM ACE can analyze large volumes of data to automatically detect anomalies, enabling operators to deliver a superior 5G customer experience while ensuring network operational efficiency. In addition, this AI/ML-based anomaly detection provides a foundation for predictive analytics, offering considerable benefits to operators for future network automation, advanced troubleshooting, and VIP service assurance.   

“Operating a network has always been complex. But with massive data growth and multiple layers of network technology, 5G networks are even more complex. Moreover, with pressure on engineering resources, many operators are already stretched and face significant challenges in managing their network operations,” said Rami Amit, RADCOM’s Chief Technology Officer and Head of Product. “RADCOM ACE with our innovative AI solution automatically analyzes millions of data sessions in real-time and can reveal underlying network faults not otherwise quickly identified in 5G networks. As a result, this would save operators valuable engineering resources and frees them to spend more time optimizing their services while reducing mean time to resolution.”

By automating assurance with AI, operators can substantially reduce the cost and time from traditional, labor-intensive methods such as manual network monitoring and transition to a more proactive approach to enhancing the customer experience. Thus, preventing network degradations before they affect a significant number of subscribers and generating real-time network intelligence drives service orchestration and closed-loop network automation. Furthermore, operators can achieve smart network resource planning with AI-based prediction engines and minimize the possibility of substantial network outages to ensure a consistent user experience.

RADCOM ACE enables operators to analyze billions of transactions to find patterns and relationships in their network. This information automatically helps set and continuously adapt Key Performance Indicators (KPIs) and thresholds for service usage and quality, enabling the operator to monitor a significant number of KPIs without the need for manual intervention while saving substantial resources. For example, when an anomaly occurs or the service drops below a predicted threshold level, a pre-set alarm will be automatically triggered and sent to the operator’s network orchestration, Business Support Systems, or Operations Support Systems, alerting the operator of the issue and activating closed-loop automation. These automated processes will enable operators to manage their networks more effectively, deal with the increasing 5G complexities and allow the dynamic management of network resources.

RADCOM ACE’s new innovative AI solution offers operators several vital benefits: 

• Proactively identify performance issues across all services.
• Analyze vast amounts of data generated by the network, which no human can do.
• Solve complex pattern recognition problems and identify patterns over time and across different data sources.
• Optimize the customers’ quality of experience and overall quality of service in the most efficient way, accumulating experience over time and enabling an intelligence data feed to reduce manual actions.

Some of the AI-driven use cases enabled by our AI solution:

• Automate 5G network troubleshooting: use advanced AI-driven insights such as automated anomaly detection to pinpoint and resolve critical customer-affecting issues rapidly. 
• Smartly monitor VIP customers and premium services: protect important revenue streams by automatically monitoring and optimizing premium services and VIP customer groups on public/private networks and 5G network slicing. 
• Improve the customer experience: utilize AI/ML to gain insights into network encrypted traffic, allowing operators to understand the customer’s Quality of Experience (QoE) for services such as video streaming and AR/VR.
• Manage network resources automatically: utilize predictive analytics to set dynamic baselines for trends and network usage to optimize network performance and prevent future degradations.   

As more operators rollout standalone 5G services, deploy network slicing and implement public/private networks, RADCOM ACE is expected to become vital for automatically detecting and resolving network issues. This automated approach to service assurance may help operators overcome the challenges of operating complex, multi-vendor 5G networks at scale and ensure the quality of new revenue-generating 5G services.