deploy it yourself

transform your cameras to AI vision

deploy on your terms

You don’t need heavy hardware that’s difficult to find. We offer either cloud based or edge based computing. Get started with a few clicks or just plug in the edge computing device. Get started without time consuming installation projects.

Both deployment solutions seamlessly integrate with your existing infrastructure. Our platform can be connected to you production lines in any way you chose.

Cloud based computing offers easily accessible computing power whilst edge based computing keeps all your data on your premisses.

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deploy on your terms

option 1 (recommended)
edge deployment

  • A no-effort edge AI solution for complete AI deployment from start to finish

  • Smooth interaction with existing industrial or IP cameras and controllers

  • On-premise processing and image management and output analysis

  • Built on Nvidia Jetson (a compact, energy-efficient GPU Powerhouse for AI Edge computing)

✓ Secure (on-premise)
✓ Low latency (lightning fast)
✓ Scalable (easily connect multiple cameras)

option 1 (recommended) edge deployment

option 2
cloud deployment

  • Accelerate deployment time without the necessity for edge device configuration

  • Effortlessly scale projects on multiple locations

  • Start within minutes

option 2 cloud deployment

technical specification edge computer

Nvidia Jetson Nano 8GB

General

Dimensions (W x D x H)
130 x 130 x 46 mm (5.1″ x 5.1″ x 1.8″)
Weight
1.2 kg (2.65 lbs)
Installation methods
Desktop / Wall mount
Capturing frame rate
up to 8 camera’s
GigE & USB 3.0 camera compatibility
Basler Pylon SDK
Allied Vision Vimba SDK
IDS uEye(+) SDK
Inference throughput
Object Detection (YOLOv5m): 131 FPS
Internal storage capability
256GB or 512GB
Jetson GPU
1024-core NVIDIA Ampere architecture GPU with 32 Tensor Cores
AI performance reference
Up to 40 TOPs
CPU
6-core Arm® Cortex®-A78AE v8.2 64-bit CPU
1.5MB L2 + 4MB L3
I/O
Ethernet 1 x 10/100/1000 Mbps
Display HDMI (Max. resolution 3840×2160 @ 60Hz)
USB External: 2 x USB 3.2 Gen 2, 1 x USB 2.0
Internal: 1 x USB 2.0 (by pin header)
OTG USB 1 x Micro USB

Nvidia Jetson Orin NX 8 GB

General

Dimensions (W x D x H)
194.8 x 174.3 x 65.85 mm (7.67″ x 6.86″ x 2.59″)
Weight
1.2 kg (2.65 lbs)
Installation methods
Desktop / Wall mount
Capturing frame rate
up to 10 camera’s
GigE & USB 3.0 camera compatibility
Basler Pylon SDK
Allied Vision Vimba SDK
IDS uEye(+) SDK
Inference throughput
Object Detection (YOLOv5m): 193 FPS
Internal storage capability
256GB or 512GB
Jetson GPU
1024-core NVIDIA Ampere GPU with 32 Tensor Cores
AI performance reference
Up to 70 TOPs
CPU
6-core NVIDIA Arm® Cortex A78AE v8.2 64-bit CPU
I/O
Ethernet 1 x 10/100/1000 Mbps
Display HDMI (Max. resolution 3840×2160 @ 60Hz)
USB External: 6 x USB 3.2 Gen 2
Digital I/O 4-ch DI, 4-ch DO
Serial Port (Optional) 2 x RS-232/422/485 (On-board pin header reserved)
CANBus 1
OTG USB 1 x Micro USB

Nvidia Jetson Orin NX 16GB

General

Dimensions (W x D x H)
194.8 x 174.3 x 65.85 mm (7.67″ x 6.86″ x 2.59″)
Weight
1.2 kg (2.65 lbs)
Installation methods
Desktop / Wall mount
Capturing frame rate
up to 12 camera’s
GigE & USB 3.0 camera compatibility
Basler Pylon SDK
Allied Vision Vimba SDK
IDS uEye(+) SDK
Inference throughput
Object Detection (YOLOv5m): 193 FPS
Internal storage capability
256GB or 512GB
Jetson GPU
1024-core NVIDIA Ampere GPU with 32 Tensor Cores
AI performance reference
Up to 100 TOPs
CPU
8-core NVIDIA Arm® Cortex A78AE v8.2 64-bit CPU (2MB L2 + 4MB L3)
I/O
Ethernet 1 x 10/100/1000 Mbps
Display HDMI (Max. resolution 3840×2160 @ 60Hz)
USB External: 6 x USB 3.2 Gen 2
Digital I/O 4-ch DI, 4-ch DO
Serial Port (Optional) 2 x RS-232/422/485 (On-board pin header reserved)
CANBus 1
OTG USB 1 x Micro USB

Nvidia Jetson Orin AGX 32GB

General

Dimensions (W x D x H)
192 x 230 x 87 mm (7.55″ x 9.05″ x 3.43″)
Weight
4.5 kg (9.9 lbs)
Installation methods
Desktop / Wall mount
Capturing frame rate
up to 16 camera’s
GigE & USB 3.0 camera compatibility
Basler Pylon SDK
Allied Vision Vimba SDK
IDS uEye(+) SDK
Inference throughput
Object Detection (YOLOv5m): 342 FPS
Internal storage capability
256GB, 512GB or 1 TB
Jetson GPU
1792-core NVIDIA Ampere GPU with 56 Tensor
Cores, Maximum Operating Frequency: 930 MHz
AI performance reference
Up to 200 TOPs
CPU
8-core NVIDIA Arm® Cortex A78AE v8.2
64-bit CPU, 2MB L2 + 4MB L3
I/O
Ethernet 4 x 10/100/1000 Mbps (Optional PoE support, IEEE 802.3af/at)
Display HDMI (Max. resolution 3840×2160 @ 60Hz)
USB External: 2 x USB 2.0, 4 x USB 3.2 Gen 2
Internal: 1 x USB 2.0
Digital I/O 4-ch DI, 4-ch DO
Power Switch 1 x Power ON/OFF Button
Serial Ports 2 x RS-232/422/485 (On-board pin header)
OTG USB 1 x Micro USB

Nvidia Jetson Orin AGX 64GB

General

Dimensions (W x D x H)
192 x 230 x 87 mm (7.55″ x 9.05″ x 3.43″)
Weight
4.5 kg (9.9 lbs)
Installation methods
Desktop / Wall mount
Capturing frame rate
up to 20 camera’s
GigE & USB 3.0 camera compatibility
Basler Pylon SDK
Allied Vision Vimba SDK
IDS uEye(+) SDK
Inference throughput
Object Detection (YOLOv5m): 342 FPS
Internal storage capability
256GB, 512GB or 1 TB
Jetson GPU
2048-core NVIDIA Ampere GPU with 64 Tensor
Cores] Maximum Operating Frequency: 1.3GH
AI performance reference
Up to 275 TOPs
CPU
12-core NVIDIA Arm® Cortex A78AE v8.2
64-bit CPU, 3MB L2 + 6MB L3
I/O
Ethernet 4 x 10/100/1000 Mbps (Optional PoE support, IEEE 802.3af/at)
Display HDMI (Max. resolution 3840×2160 @ 60Hz)
USB External: 2 x USB 2.0, 4 x USB 3.2 Gen 2
Internal: 1 x USB 2.0
Digital I/O 4-ch DI, 4-ch DO
Power Switch 1 x Power ON/OFF Button
Serial Ports 2 x RS-232/422/485 (On-board pin header)
OTG USB 1 x Micro USB

in just 10 minutes you’ll
be on your way:

Option 1

I already have my edge computing or will use cloud:

Start for free

Option 2

I don’t want or can’t use cloud. I want processing locally within my network. That’s why I need a processing unit (edge computing) and still need to buy that

Shop devices

Option 3

I need advise on what to buy so I get the best hardware for my use case:

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