Traditional packet-based monitoring solutions are no longer enough for the complexity of modern, cloud-native 5G networks. AI-driven observability, powered by eBPF and AI CEO Agents, enables real-time automation, self-healing networks, and predictive security enforcement—without the limitations of legacy tools.
Real-time AI-driven network intelligence—beyond packet capture limitations
Fully automated QoE enforcement, traffic steering, and anomaly detection
Self-healing capabilities that proactively resolve network failures
Adaptive security enforcement to mitigate threats in real time
CSPs that embrace AI-native network assurance are leaving competitors behind. Those who insist on traditional packet-based methods will struggle to keep up. AI CEO Agents provide a fully cloud-native, AI-first approach that eliminates manual inefficiencies.
Optimize network slicing dynamically to meet SLA requirements
Reduce service disruptions by enabling predictive self-healing networks
Eliminate manual troubleshooting with AI-powered observability
Enhance observability across Kubernetes-based 5G Core
Automate compliance enforcement through AI-driven security intelligence
Optimize ultra-low latency applications with AI traffic steering
Ensure ultra-reliable low-latency communication (URLLC) for industrial IoT
Secure 5G infrastructure against evolving cyber threats
Optimize business-critical applications with AI-driven performance tuning
AI-native assurance is for those ready to lead. If you are comfortable relying on packet-based monitoring, this may not be for you. But if you’re ready to outpace competitors with AI-driven automation, then the future of 5G network intelligence is yours to own.
Problem:
Frequent call drops, handover failures, and registration delays.
Solution:
AI CEO Agents monitor NAS, RRC, SCTP, and GTP-U signaling in real-time and automatically optimize handover and attach procedures.
Example Automation:
AI CEO detects frequent handover failures and reconfigures neighbor cell lists dynamically to optimize mobility.
Problem:
Network failures require manual intervention, increasing downtime.
Solution:
eBPF telemetry continuously monitors UPF congestion, gNB health, and packet loss while AI CEO Agents predict failures and trigger self-healing workflows.
Example Automation:
AI CEO Agent detects packet drops at the UPF due to congestion and autonomously reroutes traffic to another UPF instance to prevent service degradation.
Problem:
Gaming, AR/VR, and Vo5G applications suffer from unpredictable latency.
Solution:
AI CEO Agents correlate eBPF-powered QoS metrics (latency, jitter, packet loss) with application performance and dynamically adjust network slicing policies.
Example Automation:
AI CEO detects latency spikes in a telemedicine session and allocates higher priority resources to ensure consistent video quality.
Problem:
Signaling fraud, rogue base stations, and DDoS attacks are difficult to detect in real time.
Solution:
eBPF provides deep packet inspection (DPI) on 5G signaling (GTP, SIP, Diameter), allowing AI CEO Agents to detect threats and automatically execute remediation actions.
Example Automation:
AI CEO Agent identifies a GTP flood attack on a UPF, blocks malicious IPs, updates firewall rules, and rate-limits attack vectors autonomously.
eBPF captures network data in real time at the kernel level without modifying existing infrastructure.
Provides deep observability into 5G user-plane (GTP-U) and control-plane (NAS, RRC, SCTP) signaling events.
Step 1: Ingests real-time telemetry from eBPF-based network monitoring.
Step 2: AI models predict failures, detect anomalies, and identify optimization opportunities.
Step 3: AI CEO Agents execute automated actions such as dynamic traffic steering, resource allocation, and policy enforcement.
