European partner in rugged miniā€‘PC solutions

Edge AI systems

Edge AI computers for industrial inference, vision and automation

Configurable edge AI systems for machine vision, robotics, smart gateways and local AI processing.

Edge AI brings processing closer to the machine, camera or installation. Instead of sending every image, signal or event to the cloud, an edge AI computer can support local inference, faster response times and more control over data flow.

MiniDis helps European B2B customers select and configure edge AI computers for professional applications such as machine vision, robotics, industrial automation, smart gateways and field deployments. The right platform depends on the AI workload, camera input, I/O, operating system, mounting, power input, thermal design and long-term availability.
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Configuration advice Project-based supply Validation before rollout
B2B supplier

European B2B supply

MiniDis supports professional customers with product sourcing, project-based supply and practical communication around availability.

Configuration

Configurable for projects

Select memory, storage, OS and service options where available. Our team validates the configuration before delivery.

Project advice

Technical selection support

MiniDis helps compare platforms, accelerators, I/O, operating systems and mounting options before you commit to a project system.

Selection process

Start with the workload, then choose the hardware

Edge AI selection becomes easier when the first question is not ā€œwhich PC looks strongest?ā€, but ā€œwhat must run locally, which signals are involved and where will the system be installed?ā€.

01

Define the AI workload

Camera streams, model type, operating system, I/O, mounting and expected deployment volume decide the shortlist.

02

Compare the hardware route

Jetson, Hailo, RK3588, x86 industrial PCs and AI workstations solve different problems. The filter below helps narrow that choice.

03

Validate before rollout

MiniDis can check configuration fit, service options, sourcing route and repeatability before you order project hardware.

Not sure which platform fits? Send us the workload and the required interfaces. We will help you compare the realistic options.
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Selection guidance

Choose the right Edge AI platform for the workload

Edge AI hardware should be selected around the application, not only around the accelerator. Camera input, AI model size, operating system, I/O, mounting, power and lifecycle can all influence the best system choice.

MiniDis approach

From technical idea to deployable system

MiniDis helps professional customers move from hardware selection to a practical project configuration. Our team can review the required workload, interfaces, storage, operating system and service options before the system is prepared for delivery.

  • Compare Jetson, Hailo, RK3588 and x86-based options where relevant
  • Validate I/O, camera, network, mounting and OS requirements
  • Support configuration, in-house assembly and project supply
AI workload

AI acceleration

Choose the platform based on the workload. Jetson, Hailo, RK3588 and x86-based systems each fit different inference, vision and deployment requirements.

Machine vision

Camera and I/O requirements

For vision projects, check camera interfaces, PoE, LAN ports, serial, CAN, GPIO and expansion options before selecting the system.

Installation

Mounting and environment

Edge AI systems may need DIN-rail, wall mounting, fanless cooling, wide temperature support or industrial power input depending on the installation.

Lifecycle

Software and lifecycle

Operating system, SDK support, long-term supply and update strategy can matter as much as raw AI performance.

Edge AI systems

Compare Edge AI systems

Start with the systems that fit common industrial Edge AI routes: NVIDIA Jetson, Hailo acceleration, RK3588 platforms and rugged x86 edge computers.

Edge AI hardware chooser Filter by workload instead of browsing every system

Use the filters to shortlist systems for camera vision AI, robotics, industrial automation, AI gateways, development and workstation-class AI workloads.

Showing all selected Edge AI systems.
Jetson Orin EdgeAI ORN ā€“ NVIDIA Jetson AI PC

MiniDis / Compulab

EdgeAI ORN ā€“ NVIDIA Jetson AI PC

NVIDIA Jetson Orin edge AI computer Camera vision and robotics deployment
AI function

GPU inference for camera vision, robotics, autonomous machines and multi-camera edge AI.

Strength

Strong Jetson deployment route with Orin Nano/NX options and camera expansion for PoE, GMSL2, FPD-Link or USB vision projects.

Camera vision AI Robotics Automation Development
Deployment-grade Jetson View system Ask about this system
RK3588 G6S RK3588S ā€“ Compact ARM AI System

MiniDis / MDucat

MDucat RK3588 16GB / 128GB Edge AI Computer

Preconfigured RK3588 ARM AI computer ARM AI validation and IoT edge projects
AI function

ARM-based local inference for IoT workloads, light vision tasks, smart devices and edge application validation.

Strength

RK3588 platform with 16GB RAM and 128GB SSD for teams that want a practical ARM AI box without building a full custom configuration first.

Camera vision AI Automation AI gateway Development
6 TOPS class NPU View system Ask about this system
x86 industrial Tensor-I22 ā€“ Industrial Edge AI PC

MiniDis / Compulab

Tensor-I22 ā€“ Industrial Edge AI PC

Industrial x86 edge computer Industrial software, control and I/O-heavy AI projects
AI function

Runs industrial software stacks, control logic, analytics, gateways and AI-adjacent workloads where x86 compatibility matters.

Strength

Tiger Lake CPU options, up to 64GB DDR4, modular I/O, multiple storage options and networking modules for industrial integration.

Automation AI gateway AI workstation Industrial
Modular I/O View system Ask about this system
RK3588 G6 RK3588 ā€“ ARM Edge AI Computer

MiniDis / MDucat

G6 RK3588 ā€“ ARM Edge AI Computer

RK3588 ARM edge AI computer ARM vision, signage and edge automation
AI function

Local AI inference, media intelligence, sensor processing and computer vision on an ARM platform.

Strength

RK3588 with 6 TOPS NPU for compact AI, display, camera and edge applications where ARM efficiency is useful.

Camera vision AI Automation AI gateway Development
6 TOPS NPU View system Ask about this system
RK3588S G6S RK3588S ā€“ Compact ARM AI System

MiniDis / MDucat

G6S RK3588S ā€“ Compact ARM AI System

Compact RK3588S ARM AI system Compact embedded AI and IoT systems
AI function

Compact local inference for embedded vision, smart displays, IoT systems and lightweight edge AI applications.

Strength

Smaller RK3588S form factor for projects that need ARM AI capability in a compact box.

Camera vision AI Automation AI gateway Development
Compact ARM AI View system Ask about this system
Jetson dev kit Jetson Orin Nano Super ā€“ 67 TOPS AI Kit

MiniDis / NVIDIA

Jetson Orin Nano Super ā€“ 67 TOPS AI Kit

NVIDIA Jetson developer kit Jetson development and vision prototyping
AI function

Development platform for computer vision, robotics, multimodal AI, Jetson software validation and prototype inference.

Strength

67 TOPS Jetson Orin Nano Super platform with the NVIDIA software ecosystem for teams building and testing AI workloads.

Camera vision AI Robotics Development NVIDIA Jetson
67 TOPS View system Ask about this system
AI camera reCamera Gimbal 2002w ā€“ AI Vision Camera

MiniDis / Seeed Studio

reCamera Gimbal 2002w ā€“ AI Vision Camera

AI vision camera with gimbal Tracking, inspection and camera-first AI
AI function

Camera-first AI for object tracking, inspection demos, robotics experiments and smart monitoring.

Strength

Combines embedded AI vision with a moving gimbal, useful when the camera itself is part of the AI workflow.

Camera vision AI Robotics Development AI camera
Vision + gimbal View system Ask about this system
Hailo / CM5 reComputer AI Industrial R2135-12 Edge AI PC

MiniDis / Seeed Studio

reComputer AI Industrial R2135-12 Edge AI PC

Hailo-accelerated industrial AI PC Efficient camera vision inference
AI function

Efficient local vision inference for AI cameras, inspection, monitoring and industrial automation.

Strength

CM5-class industrial platform with Hailo-8 acceleration, PoE-oriented connectivity and expansion options for vision deployments.

Camera vision AI Automation AI gateway Industrial
Hailo-8 class AI View system Ask about this system
Hailo / CM5 reComputer R2135 ā€“ Industrial AI Computer

MiniDis / Seeed Studio

reComputer R2135 ā€“ Industrial AI Computer

Hailo-accelerated industrial AI PC Efficient camera vision inference
AI function

Efficient local vision inference for AI cameras, inspection, monitoring and industrial automation.

Strength

CM5-class industrial platform with Hailo-8 acceleration, PoE-oriented connectivity and expansion options for vision deployments.

Camera vision AI Automation AI gateway Industrial
Hailo-8 class AI View system Ask about this system
IoT gateway Tensor-I20 ā€“ Industrial Edge AI PC

MiniDis / Compulab

Tensor-I20 ā€“ Industrial Edge AI PC

Industrial IoT and protocol gateway Industrial gateway and data aggregation
AI function

Connects machines, PoE devices, serial equipment and field networks to an edge AI or cloud workflow.

Strength

Best as the industrial connectivity layer when the project needs multi-LAN, multi-COM, PoE or protocol aggregation rather than maximum AI acceleration.

Automation AI gateway Industrial Control
Multi-LAN / COM View system Ask about this system
AI workstation Lenovo ThinkStation PGX SFF ā€“ NVIDIA Grace Blackwell AI Workstation

MiniDis / Lenovo

Lenovo ThinkStation PGX SFF ā€“ NVIDIA Grace Blackwell AI Workstation

NVIDIA Grace Blackwell AI workstation High-end AI development and simulation
AI function

Heavy local AI development, model experimentation, simulation and workstation-class AI workloads.

Strength

Best positioned as a high-end AI workstation route for teams that need substantially more compute than embedded edge boxes.

Development AI workstation high performance generative
Grace Blackwell class View system Ask about this system

AI TOPS explained

What AI TOPS means for your Edge AI project

TOPS means tera operations per second. It is often used to describe AI accelerator throughput, but it is not the same as real project performance. A good hardware choice also depends on model support, camera input, memory, storage, software stack, cooling and the full data pipeline.

TOPS is a throughput signal, not the full hardware decision.

Use TOPS to shortlist accelerator class, then validate the complete pipeline: camera input, model support, CPU load, memory, storage, thermals, I/O and software stack.

InputCamera, sensor or data stream InferenceAccelerator, model and SDK ApplicationCPU, memory and pre-processing DeploymentI/O, storage, network and thermals
Selected route 1-10 TOPS

small models

Indicative accelerator range 22%
CompactVisionMulti-cameraWorkstation
Focused edge tasks

Small models, event filtering and compact AI gateways

Use this route when the model is compact, camera count is limited or the device mainly filters events before forwarding data.

  • Confirm model conversion and accelerator toolchain support first.
  • Reserve CPU and memory for the full application, not only inference.
  • Good starting point for validation, compact gateways and focused vision tasks.
Common Edge AI route

Camera vision, robotics prototypes and local inference

This is often where teams compare Hailo acceleration, NVIDIA Jetson systems or efficient embedded AI platforms for camera-based workloads.

  • Map camera input first: USB, PoE, MIPI, GMSL or another interface.
  • Check end-to-end latency, including pre-processing and application logic.
  • Validate OS, SDK and model conversion before a larger rollout.
Higher local inference

Multi-camera vision, robotics perception and heavier pipelines

Higher accelerator capacity can help when the project combines multiple camera streams, larger models or richer perception close to the machine.

  • Plan thermal design around continuous load, not short benchmark bursts.
  • Include video pipeline, pre-processing and post-processing costs.
  • Check storage and network bandwidth against the real data volume.
Development route

Model development, simulation and workstation-class AI

When the goal is development, simulation or heavier local experimentation, workstation-class hardware can make more sense than a small embedded edge system.

  • Separate development hardware from deployable hardware.
  • Use the workstation to validate models, then select the field system.
  • Consider power, size, noise, procurement and support expectations.
Ask MiniDis to compare your workload Compare systems

Use cases

Edge AI use cases from real projects

These selected articles show why the hardware choice is more than compute. Camera input, local processing, field deployment, supportability and integration all influence the right system.

Use cases show the real deployment questions behind the hardware: cameras, interfaces, field deployment, supportability and local processing. View all insights

Applications

Where Edge AI systems are typically used

Edge AI is useful when data needs to be processed close to a machine, camera, vehicle, robot or remote installation. The best fit depends on the AI workload and the environment around it.

Field deployment

Smart field systems

For outdoor, mobile or remote systems, local inference can reduce bandwidth use and support faster event-based decisions.

IoT gateway

Industrial IoT gateways

AI-ready gateways can combine local processing with industrial connectivity for monitoring, automation and field deployments.

Robotics

Robotics and autonomy

Compact edge AI platforms can support robotics, sensor fusion, local decision-making and autonomous systems where cloud dependency is not ideal.

Vision AI

Machine vision

Edge AI computers can support local inspection, object detection, camera processing and vision workloads close to the production line.

Selection support

Need a second opinion before choosing the system?

MiniDis can help compare embedded AI hardware, AI cameras, industrial gateways and workstation-class systems based on your workload, interfaces and rollout context.

Request hardware advice Send your workload and get a practical shortlist. About MiniDis Show who supports the project and why MiniDis fits B2B rollouts. Contact page Use the standard contact route for general questions.

FAQ

Edge AI computer questions

Short answers for buyers comparing Edge AI systems for professional projects.

What is an edge AI computer?
An edge AI computer is a compact system that runs AI workloads close to the machine, camera or sensor instead of relying only on cloud processing. It can support local inference, machine vision, robotics, smart gateways and industrial automation tasks.
Which edge AI platform should I choose?
The right platform depends on the AI model, camera input, required interfaces, operating system, power budget, mounting method and lifecycle requirements. Jetson-based systems, Hailo acceleration, RK3588 platforms and x86 industrial PCs all serve different types of edge AI projects.
Can MiniDis help configure an edge AI system?
Yes. MiniDis can help professional customers compare suitable systems and configuration options such as memory, storage, operating system, mounting and service options. For project deployments, our team can help validate whether the selected system fits the intended application.
Are edge AI computers only used for machine vision?
No. Machine vision is a common use case, but edge AI computers can also be used for robotics, industrial gateways, smart monitoring, autonomous systems, field installations and local analytics.

Need help choosing?

Discuss your Edge AI project with MiniDis

Share the workload, interface requirements, mounting preference and expected deployment context. We can help you compare suitable systems and prepare the right next step.

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