VoIP Call Quality- AI
Industry
Telecommunications
Project
Call Quality Monitoring using AI
Client
Texas-based IoT product company
Our Role
Solution Provider
Technologies
Python, Pandas, Numpy, Fastapi, Uvicorn, Pydantic, Scikitlearn, Scipy
The Challenge
To ensure flawless VoIP quality amidst dynamic network conditions. The ReplyPoint device faces a relentless task: every two minutes, it must execute a VoIP quality check, scrutinizing latency, packet loss, jitter, and hop analysis. This demands unwavering precision and adaptability, navigating through fluctuating network landscapes to maintain seamless communication.
The Solution
CloudTern developed two microservices: one for managing VOIP and another for monitoring Mos score frequency. Leveraging AI algorithms, these services precisely detect network disruptions, whether they affect individual users or multiple locations, and meticulously document their occurrence and duration. This data provides crucial insights into network health, facilitating proactive maintenance and optimization efforts.
With the ability to swiftly pinpoint issues, the AI-powered system ensures network stability and seamless operations. Ultimately, CloudTern’s solution serves as a vigilant guardian, bolstering network integrity and enhancing overall performance through its proactive approach to identifying and resolving disturbances.
Key Benefits
Enhanced Network Stability
CloudTern's microservices swiftly detect and resolve network disruptions, minimizing downtime and ensuring uninterrupted service, thus fortifying overall network stability.
Optimized Performance
With CloudTern's AI-driven analysis of disruption data, network performance is continuously optimized. By proactively addressing potential issues, CloudTern ensures consistent service delivery, enhancing user satisfaction and maximizing the efficiency of network resources.
Efficient Issue Resolution
Leveraging AI, CloudTern swiftly identifies and resolves issues, streamlining operations and boosting productivity, while also utilizing insights from disruption analysis to optimize network performance, elevating efficiency and user satisfaction.
Time Savings
AI in VOIP enhances efficiency by quickly detecting and fixing issues, reducing manual efforts. Real-time analysis identifies disruptions, leading to faster problem resolution, minimized downtime, and consistent communication quality for users.
