Edge AI
Edge AI Computers – Real-Time Analysis Without Cloud Dependence
Why Edge AI?
Edge AI means that artificial intelligence moves closer to the source – that is, where the data is created. Instead of sending everything to the cloud, data can be processed locally on the device itself. This provides several advantages. Delays are avoided because the systems can react in real time – crucial in solutions such as robots, production equipment, or autonomous vehicles. At the same time, data security is increased, since sensitive information does not need to be sent out to external systems.
As we produce and collect ever larger amounts of data, the need for fast analysis and action continues to grow. Edge AI makes it possible to handle these volumes of data efficiently and reliably, even if the internet connection fails. For businesses, this means faster and better decision-making, more stable and reliable systems, and greater confidence in data security and compliance with regulations such as GDPR, NIS2, and the Cyber Resilience Act.
What is Edge Computing?
Edge computing moves data processing from the cloud to local devices such as industrial PCs, gateways, and IoT systems. This provides lower latency, better bandwidth utilization, higher operational reliability, and increased data security. Data is processed closer to the source, ensuring faster response times and more reliable solutions, even without a constant internet connection.
What is Edge AI?
Edge AI combines artificial intelligence and edge computing, allowing AI algorithms to run directly on local devices. This enables real-time analysis with low latency and without reliance on the cloud. The technology is crucial in critical systems such as robotics, manufacturing, and autonomous vehicles, where fast decision-making is necessary and both data volumes and communication interruptions must be minimized.
Explore the Edge AI Computers We Offer
We offer advanced Edge AI systems from Compulab, SolidRun, and JHCTECH, carefully selected for demanding environments and real-time applications without relying on the cloud.
Compulab EdgeAI-ORN
- Processor: NVIDIA Jetson Orin NX / Orin Nano SoC
- AI-accelerator: Up to 100 TOPS (INT8) performance
- OS: Linux (Ubuntu with NVIDIA JetPack SDK)
- Properties: Fanless design, robust industrial temperature range, ideal for computer vision, robotics, and edge IoT
SolidRun Bedrock R7000 Edge AI
- Processor: AMD Ryzen V3000 serie
- GPU: Option for dedicated AI accelerators (e.g., AMD Instinct GPUs)
- OS: Linux and Windows IoT
- Features: Modular design, powerful for edge server workloads and AI training/inference close to the data source.
SolidRun Bedrock R8000 AI Edge
- Processor: AMD Ryzen 7000 serie
- GPU: High-end PCIe accelerator support (NVIDIA/AMD)
- OS: Linux, Windows Server, container-ready
- Features: Industrial fanless design with high scalability – perfect for predictive maintenance and Industry 4.0.
JHCTECH BRAV-7601
Processor: Intel Core 12./13. Gen Alder Lake-H
AI support: Integrated GPUs or dedicated NVIDIA MXM GPU modules
OS: Linux, Windows 11 IoT
Features: Powerful, compact system with multiple LAN ports, ideal for edge networking, video analytics, and the transportation sector.
What Does Edge AI Deliver?
Edge AI means that artificial intelligence runs directly on local devices instead of relying on the cloud. It provides:
- Low latency: Decisions can be made within just a few milliseconds.
- High data security: Sensitive information stays on site and is not sent outside the organization.
- Robust operation: Systems continue to function even if the internet connection fails.
- Greater efficiency: Reduced network load and lower operating costs.
What Can Edge AI Be Used For?
Edge AI is already in use across many areas:
- Video surveillance and security: Object detection, facial recognition, and behavior analysis in real time.
- Industry 4.0 and maintenance: Predict machine failures and minimize downtime with predictive maintenance.
- Transport and Smart Cities: Intelligent traffic systems and autonomous vehicles.
- Healthcare technology: Local analysis of medical images – fast and GDPR-compliant.
- Retail: Insights into customer behavior, shelf optimization, and efficient queue management.
Edge AI and Regulations – GDPR, NIS2, and the Cyber Resilience Act
When AI moves to the edge, security can be strengthened because data stays local – but at the same time, compliance and IT security become even more important to manage.
- GDPR: Local data processing ensures that sensitive data is not sent outside the organization.
- NIS2: Requirements for resilience and security in critical infrastructures are easier to meet with control over your own edge devices.
- Cyber Resilience Act: Edge AI computers from our suppliers are designed with a focus on updatability, security, and Open Source support.
At Nord Technology, we combine hardware, Linux expertise, and IoT security to deliver solutions that not only provide high performance but also comply with the strictest regulatory requirements.
Do you have any questions?
Feel free to reach out to us by phone, email, or through the contact form. We will return as soon as possible.