Smarter Networks, Maximized Service
– AI Enabled 5G NQoS

Agent-based NQoS (Network Quality of Service). Monitor, predict, and optimize network performance in real-time, enabling proactive management rather than reactive troubleshooting.

Impact

More accurate
bandwidth allocation

50%

Reduction in
packet loss

50%

Improved traffic
prediction accuracy

8%

Faster MTTR
(men time to repair)

15%

Optimized latency
and jitter

7%

Improving NQoS at Scale

Traffic Prioritization

Agent-based algorithms optimize real-time network traffic management and prioritization. By making networks more adaptive and efficient in handling diverse traffic loads, critical services and applications maintain high performance while minimizing congestion and delays.

Traffic Shaping and Policing

Enhanced ability to analyze traffic flows in real-time, identifying bursts or congestion patterns before they become critical. This allows the system to dynamically adjust the shaping rate to smooth traffic and maintain optimal performance.

Bandwidth Management

Dynamically adapts to real-time conditions, ensuring more efficient use of available bandwidth, preventing congestion, and maintaining optimal network performance, especially for high-demand applications like video streaming, VoIP, and cloud services.

Latency and Jitter Optimization

Advanced machine learning algorithms and real time network analytics dynamically predict, manage, and optimize traffic flows to reduce delays and minimize packet variance.

Who Benefits from the MicroAI NQoS Agent?

Network Engineers and Architects: “Unforseen network traffic congestion is still a problem for our team. We simply don’t have the capaiblity to accurately predict periods of potential congestion and their sources”.
Biggest Stressor: Tying to police our various sources of traffic with limited insights.
Industrial Engineers: “We suffer from periods of high latency within several of our critical applications. We are unable to get the maximum output from our connected IIoT devices”.
Biggest Stressor: Having to find workarounds to overcome our persistent latancy problem.
Fleet Managers: “Our fleet status data often arrives too late to make effective decsions. By the time we try to reroute our vehicles it is often already too late”.
Biggest Stressor: Having our vehcicles, and their cargo, arrive too late or at the wrong destination.
Broadcast Engineers: “Our bandwidth allocation can be inconstent. Our ability to provide high quality streaming can be affected. This has a negative impact on our consumers”.
Biggest Stressor: Worry that we will loose market share due to inconsistent performance
City Infrastructure Enigeers: “We have the infrastructure monitoring devices in place. We just lack the ability to apply intelligence to the data that they produce”.
Biggest Stressor: Knowing that we have the necessary hardware but not the software to fully enable it.

Smart NQoS – Self-Governing, Self-Healing

Predictive traffic analysis

Predicting traffic congestion before it happens by analyzing trends in network usage. This allows networks to adjust resources proactively, preventing bottlenecks and ensuring that high-priority applications receive adequate bandwidth.

Traffic profiling

Creation of dynamic, granular traffic profiles that reflect the specific behavior of applications, users, or devices. These profiles are continuously updated based on traffic flow data, allowing the network to police traffic with more granularity.

Congeston detection and mitigation

Continuous monitoring for network congestion and rule-based implementation of insight-based corrective actions when congestion thresholds are breached.

Dynamic NQoS settings

Optimizing NQoS settings dynamically, ensuring that low-latency traffic is prioritized across the network while reducing the variability in packet delivery times (jitter). AI algorithms adjust DSCP (Differentiated Services Code Point) values, prioritizing critical traffic.

Jitter detection and mitigation

AI models learn normal jitter patterns for specific types of traffic, then use that knowledge to detect when jitter exceeds acceptable thresholds, triggering corrective actions to stabilize traffic flow.

More reliable and more predictable. Download our NQoS Agent for a smarter network.
Download NQoS Agent

See it in action

Book your free demo today