At Digital Carbon, a Managed Service Provider specialising in VeloCloud SD-WAN for the manufacturing and construction sectors, we have a front-row seat to the transformative changes taking place in connectivity. One of the most significant shifts we’re witnessing is the impact of artificial intelligence (AI) on enterprise edge networks.
AI is revolutionising operations across industries with applications like predictive analytics, automation, and advanced monitoring. Manufacturing and construction, in particular, are embracing AI-driven tools such as computer vision for quality control, IoT-enabled maintenance, and AR for remote troubleshooting. However, these cutting-edge applications introduce unique networking challenges, requiring a rethinking of how edge networks are designed and managed.
Why AI is Changing Network Requirements
AI workloads differ fundamentally from traditional applications, placing unprecedented demands on network infrastructure. Key challenges include:
- Symmetrical Traffic Patterns: AI workloads often generate equal volumes of upload and download traffic, unlike conventional WAN traffic, which skews heavily towards downloads. In construction, for example, AI-driven drones capturing site data may need to upload massive amounts of information for analysis in real-time.
- High Throughput Needs: AI applications, particularly those involving video analytics or augmented reality, demand significantly higher bandwidth. In manufacturing, IoT devices transmitting multimodal data require robust connectivity to ensure seamless production lines.
- Low Latency: Real-time AI applications, such as robotic process automation or remote equipment monitoring, are highly sensitive to delays. Even minor latency can disrupt operations.
- Bursty and Unpredictable Traffic: AI workloads often feature erratic traffic patterns, requiring dynamic adjustments to maintain performance. Construction site monitoring or IoT-enabled predictive maintenance tools may transmit data in bursts, depending on environmental conditions or operational needs.
- Peer-to-Peer Traffic: AI applications often operate on distributed architectures with multiple components communicating simultaneously. This is particularly relevant in manufacturing, where edge-based AI agents interact with centralised models to optimise production.
For industries like manufacturing and construction, traditional network architectures simply aren’t equipped to handle these requirements effectively. Without the right infrastructure, organisations risk bottlenecks, downtime, and missed opportunities for innovation.
Enter AI-Optimised SD-WAN: A Game Changer for the Edge
The solution to these challenges lies in SD-WAN, particularly VeloCloud, enhanced with AI capabilities. An AI-ready SD-WAN enables manufacturers and construction firms to optimise their networks dynamically, ensuring seamless connectivity for demanding applications. Here’s how:
- Bandwidth Optimisation: VeloCloud’s Dynamic Multipath Optimisation™ (DMPO) aggregates bandwidth from multiple sources, ensuring the uplink capacity required for high-throughput AI workloads.
- Traffic Prioritisation: AI-enabled traffic steering ensures latency-sensitive applications like AR troubleshooting or real-time analytics receive top priority, maintaining quality of experience (QoE).
- Real-Time Traffic Shaping: By adapting to bursty and unpredictable traffic patterns at a per-packet level, VeloCloud ensures stability even under fluctuating conditions.
- Secure Peer-to-Peer Communication: With intelligent overlays, AI-ready SD-WAN enables secure communication between distributed AI agents and centralised systems, critical for protecting proprietary data in manufacturing and construction environments.
Introducing VeloRAIN: AI Networking for the Next Generation
To address these demands, VeloCloud has introduced VeloRAIN (Robust AI Networking), an extension of its market-leading SD-WAN platform. VeloRAIN integrates advanced AI capabilities to optimise edge networks for high-performance AI applications. It enhances:
- Application Profiling: Identifying and prioritising encrypted AI traffic.
- Dynamic Slicing: Allocating resources on a per-application basis to ensure QoE.
- AIOps: Automating network operations to adapt policies in real time.
- Enhanced Security: Isolating AI traffic to safeguard against emerging threats.
For manufacturing and construction firms, this means more than just better connectivity—it’s about enabling a new era of smart factories, dynamic construction sites, and AI-driven innovation.
Why Partner with Digital Carbon?
At Digital Carbon, we specialise in designing, deploying, and co-managing VeloCloud SD-WAN solutions tailored to the unique needs of manufacturing and construction. Our expertise ensures you can unlock the full potential of AI applications without the complexity and resource drain of managing your network in-house.
Whether it’s enabling remote monitoring of construction sites, optimising supply chain connectivity, or enhancing IoT integration in smart factories, we’re here to make your transition to AI-optimised connectivity seamless and efficient.
Ready to Future-Proof Your Network?
The AI revolution is here, and the right connectivity can make all the difference. Let Digital Carbon help you embrace this new era with AI-ready SD-WAN solutions designed for the demands of manufacturing and construction.
Discover more about VeloRAIN and how it can transform your operations. Schedule a discovery call with one of our experts