We provide bandwidth management, load balancing, root cause analysis, and fault prediction services utilizing high performance big data analytics technology for the telco industry. Let’s take a tour to see the AI-powered automated network and advanced fault control management system.
It collects real-time data generated from a large number of network devices, diagnoses problems, and visualizes them so that the administrator can easily grasp the current situation.
Using machine learning, we can help you detect anomalous behavior faster and thus preventing failure before it occurs. Protect your information assets from internal and external intrusions and threats through extensive network security policies.
Through service orchestration, network configuration changes are automatically applied according to predefined policies for the ecosystems that consist of computing, storage, and network equipment.
Diagnoze problems with AI technology, suggest improvements and assess possible issues in the future. Learn about network anomalies, automatically identify the anomalies, and notify them to the relevant stakeholders in real time.
In the telco network fields, traffic and configuration complexity continues to grow due to the needs of various business environments. Many companies are trying to solve this problem effectively using real-time network health analysis and proactive anomaly detection.
Advanced in AI and big data technologies foster new ways to improve management and service efficiency for existing networking systems. Furthermore, the 5G era with high-speed and high-bandwidth networking system necessitates the emergence of more intelligent setup, control, management and orchestration technologies.
Mondrian AI develops AI models for infrastructure management, network operation, service orchestration and QC assurance in the telecommunication sector. We help provide more efficient telco network management through autonomous traffic monitoring and optimization of network resources. Furthermore, we develop standardized, AI-powered software systems and decouple the dependency for specific hardware equipment that is commissioned through certain vendors.
Network information generated by thousands of equipment was collected and processed in real-time. Historical anomaly data was learned to provide deep-learning based anomaly prediction system.
The massive data is stored in HDFS and processed through a distributed system that forward messages from one component to the other through a flexible data pipeline. The AI model maximizes operational efficiency by anticipating failure and enable early maintenance before the failure occurs and equipment fails.
Adaptive learning allows you to train an AI model that can detect potential fraud. It learns system misuse such as abnormal behavior of various network communication records, fraudulent phone calls and fraudulent use. It then performs intelligent classification against the ever-changing data stream, and communicates the AI assessment to the stakeholders in the most efficient manner.