AI-RAN: Connecting AI Factories to the Physical World

Bringing AI and 5G RAN together on shared infrastructure at the edge.

SynaXG — AI-RAN

The AI-Grid: bridging AI factories and physical AI

SynaXG's AI-RAN solution connects centralised AI compute with physical AI devices through the AI-Grid. Massive AI factories train models and run inference at scale, while robots, drones, cameras, and connected devices need real-time intelligence at the edge. The AI-Grid is the layer that brings 5G and AI together on a single, commercially ready platform.

What is AI-RAN?

AI-RAN refers to the full scope of AI integration across the RAN stack. Spanning centralised and distributed intelligence.

Our AI-RAN strategy combines intelligent networking with AI-native capabilities, enabling new use cases for consumer, enterprise, and public-sector deployments while maximising the return on infrastructure already in the ground.

AI improves the network itself. Efficiency, capacity, reliability, and energy savings are delivered through intelligent optimisation running at the network layer — improving performance without new physical infrastructure.
AI and 5G run on the same hardware, creating new monetisation opportunities from infrastructure already deployed. Operators turn fixed network assets into a revenue-generating compute platform without additional capex.
Inference runs inside the RAN node itself, enabling real-time edge decisions with ultra-low latency. This unlocks closed-loop physical AI applications where sensing, deciding, and acting happen concurrently at the edge.

Why AI-RAN?

The AI-Grid transforms what a mobile network can do, in two fundamental ways — making the network itself more intelligent, and turning it into the connective tissue for physical AI.

  • AI for networks: improving performance, automation, and energy efficiency across the RAN.
  • Networks for AI: delivering programmable, deterministic infrastructure to support emerging AI-driven services.
  • Closed-loop intelligence: physical AI devices sense, decide, and act concurrently — requiring real-time, deterministic connectivity and high uplink capacity.
  • Flexible architecture: combining intelligence at the radio sites with centralised data centres, supporting both purpose-built and Cloud AI deployments over Open RAN interfaces.

What's in it for you

01

Boost RAN performance and energy efficiency

Intelligent optimisation increases throughput and reduces energy consumption across the network.

02

Accelerate your automation journey

AI-native control simplifies operations and unlocks autonomous, intent-driven network management.

03

Maximise ROI on deployed infrastructure

Run AI and 5G on the same hardware, creating new monetisation from assets already in the ground.

04

Future-proof with an open platform

O-RAN compliant and commercially ready, built on NVIDIA AI Aerial™ and CUDA-X.

How the AI-Grid connects everything

AI Factory

Centralized compute

For training of LLMs and large-scale models

Non-real-time inference

Asynchronous workloads at data centre scale

Model orchestration & lifecycle

End-to-end management and versioning

Data aggregation

Centralised collection and pipelines

AI Grid

Connected by Fiber
Connected by 5G
AI Applications and AI-RAN

Physical AI

Closed-loop intelligence

Sense → decide → act, concurrently

Real-time connectivity

Deterministic, ultra-low latency

High uplink capacity

Sensor and vision data at volume

24/7 stability

Always-on operational requirements


AI-RAN on four hardware platforms

SynaXG runs across a range of NVIDIA GPU architectures from high-capacity data centre deployments to compact edge nodes. We provide operators the flexibility to match hardware to environment.

Platform Description Best suited for

NVIDIA GH200

High Capacity
Ultra-high performance for large-scale AI workloads, ideal for dense urban deployments and high-throughput inference. Dense urban, high-throughput inference

NVIDIA DGX Spark™

Smaller Deployments
Compact and power-efficient, designed for smaller-scale and edge deployments where footprint matters. Edge deployments, low footprint

Arc Pro

Arm-Based
Built for customers requiring Arm-based architecture on the NVIDIA Grace/Arm ecosystem. Arm-native deployments

RTX Pro

x86 Compatible
For customers with existing x86 infrastructure who want to add AI-RAN without replacing their server fleet. Existing x86 infrastructure

End-to-end Deployment

A commercially ready platform running FR1, FR2, and AI workloads concurrently on a single GPU server. Compute and connectivity become one system.

Software Stack — Concurrent Workloads

5G FR1

RAN Software Stack + AI Control

Layer 1–3

5G FR2

RAN Software Stack + AI Control

mmWave

AI Workloads

Training + Inference, concurrent

GPU-Native

NVIDIA AI Aerial™

Foundation software layer

CUDA-X

Hardware Reference — Integrated Ecosystem

AI-RAN

NVIDIA GH200

High Capacity

DGX Spark

Smaller Deployments

Timing

GPS / PTP

Precision timing

Fronthaul Switch

eCPRI transport

Radio Units

O-RU

Open RAN compliant

DAS

Indoor coverage


Devices & use cases

📱

Phones

5G-connected handsets requiring low-latency AI services.

📷

Cameras

Edge vision for security and real-time scene analysis.

🤖

Robots

Autonomous robots needing deterministic 5G uplink.

🚁

Drones

Aerial platforms on real-time command and sensor loops.

Ready to deploy AI-RAN on your network?