Live Mirror of Your Physical Network
OranSense builds a continuously synchronized digital replica of your RAN, edge, and core infrastructure — enabling simulation, prediction, and autonomous optimization before changes ever touch production.
Simulate Before You Deploy
Every configuration change, software upgrade, or capacity expansion carries risk in live networks. The OranSense Digital Twin eliminates that risk by maintaining a physics-accurate, AI-enriched replica of your entire network stack — from the radio unit to the cloud core.
Powered by NVIDIA Omniverse and our proprietary InfraSense telemetry pipeline, the twin ingests real-time KPIs, topology data, and RF measurements to stay synchronized within 50ms of the physical network. Engineers can test changes, run failure scenarios, and validate AI model updates in the twin before a single packet is affected in production.
Twin Capabilities
Six core modules that keep your digital twin accurate, actionable, and always in sync with the physical world.
Real-Time Telemetry Sync
Continuous ingestion of KPIs, alarms, topology changes, and RF measurements from the live network. The twin stays synchronized within 50ms, reflecting every state change automatically.
What-If Scenario Engine
Model capacity expansions, new site deployments, software upgrades, and traffic surges in the twin. Predict outcomes and identify failure modes before committing to production.
AI Model Validation
Test and validate new AI/ML models — beamforming algorithms, scheduling policies, interference classifiers — against the twin before live deployment. Eliminate regression risk.
Failure Mode Simulation
Inject faults, simulate outages, and stress-test redundancy mechanisms. Validate your NOC runbooks and automated recovery procedures in a safe, isolated environment.
Omniverse 3D Visualization
Render your network in photorealistic 3D using NVIDIA Omniverse. Visualize coverage maps, interference patterns, and traffic flows overlaid on real-world geography.
Change Impact Analysis
Quantify the blast radius of any planned change. The twin predicts downstream effects on QoS, coverage, capacity, and energy consumption before the change window opens.
From Physical Network to Digital Insight
Ingest
Telemetry collectors pull real-time data from RAN, transport, and core via O1, E2, and vendor APIs.
Model
AI enriches raw telemetry into a structured graph model — nodes, links, RF conditions, and traffic state.
Synchronize
The digital twin updates continuously, maintaining sub-100ms fidelity to the physical network.
Simulate
Engineers run scenarios, test changes, and validate AI models against the live twin replica.
Deploy
Validated changes are promoted to production with confidence — automated rollback policies stand by.
Every sensor. Every antenna. Every link — mirrored in real time.
Deployment Use Cases
Network Capacity Planning
Model traffic growth, new site builds, and spectrum additions in the twin. Optimize CapEx allocation with data-driven forecasts instead of conservative over-provisioning.
Autonomous NOC Operations
Train and validate autonomous remediation workflows in the twin. When the AI detects an anomaly in production, it already knows the fix — tested and proven in simulation.
5G/6G Technology Trials
Evaluate new waveforms, massive MIMO configurations, and AI-RAN algorithms in the twin before committing to hardware. Accelerate technology adoption cycles by months.
See Your Network in the Twin
Book a live demonstration and see your own network topology rendered in the OranSense Digital Twin within 48 hours of onboarding.