Predictive Congestion Forecasting

We apply time-series forecasting and deep learning models on NetFlow, sFlow, and SNMP telemetry to predict congestion events before they impact users.

Dynamic QoS Enforcement

AI engines automatically classify traffic by application type, user identity, and SLA priority—then apply QoS enforcement policies (bandwidth guarantees, throttling, or shaping) in real time.

Application-Aware Traffic Optimization

Our solutions analyze Layer 7 traffic patterns and allocate resources dynamically to critical applications like VoIP, video conferencing, or financial transactions, while deprioritizing bulk or non-critical flows.

Cross-Domain Network Telemetry Correlation

We unify telemetry across LAN, WAN, SD-WAN, and cloud fabrics, correlating network state with application performance for proactive QoS decisions.

Anomaly Detection in Traffic Flows

Machine learning models detect anomalies in traffic patterns, such as volumetric DDoS, sudden surges, or misconfigured flows, and automatically trigger mitigation workflows.

Hybrid & Multi-Cloud QoS Governance

QoS enforcement policies extend seamlessly across AWS, Azure, GCP, and on-premise networks, ensuring consistent application performance globally.