AI for 5G Network Optimization

Optimize 5G RAN, transport, and core with AI to deliver higher throughput

5G optimization spans beam/slice management, mobility, edge placement, and core policy tuning. AI improves decisions across RAN/transport/core with guardrails for stability, SLAs, and regulatory constraints.

Boost performance and reliability of 5G networks through explainable, safe automation and decision support.

RAN KPIs, UE capabilities, beam/slice configs, mobility events, edge locations

Beamforming/tilt optimization, slice resource allocation, mobility/HO optimization, traffic forecasting, anomaly detection, and edge placement are key areas for AI intervention.

Planner/ops consoles, recommendation engines, closed-loop controllers with approvals and rollback provide the operational framework for these intelligent systems.

live demo · related simulation● LIVE

Reduce drops and ping-pong with better HO parameters

Place workloads based on latency and demand to minimize network congestion and improve user experience.

Optimize networks for concerts or disaster scenarios with rapid policy adjustments, ensuring minimal disruption.

Frequently asked questions

Question about Integrate OSS, probes, slice managers, p?

Integrate OSS, probes, slice managers, policy/PCF; ensure time-sync, security, and logging; keep provenance and approvals.

Question about Governance, Safety, and Explainability?

Governance, Safety, and Explainability

Question about Show reasons and expected impact for cha?

Show reasons and expected impact for changes.

Question about Bounded changes, canarying, rollback, an?

Bounded changes, canarying, rollback, and human approvals.

▶ Try it live

Everything above runs in your browser — open Force-Directed Graph and change the parameters while it is running. Nothing is installed, nothing is uploaded, the whole model lives in one tab.

▶ Open Force-Directed Graph simulation