Create Feature-Rich, Fast Responding, and Easy to Deploy Applications at the Edge, Close to Your Users.
Orchestrate by Applications by Project, Facility, Device and User.

Containerized Application Delivery and Deployment




Rapid Design

Swappable Machine Learning Models


Modular Code Friendly

Construct Sensing and Control Data Flows


Scalable Deployment

Camera Swap and Capture for Machine Vision at the Edge

Cloud or On-Premise Orchestrated

Transform computers into EDGE PROCESSING UNITS that are fast to deploy and easy to maintain at the EDGE

•Machine vision, image, and video processing
•Heterogeneous wired and wireless sensing
•Machine health in manufacturing and military
•Manufacturing test systems in biopharma, automotive, EMS
•Residential and commercial energy management
•Security and employee safety
•Visual inspection and anomaly detection
•Portable or stationary robotics applications

If your success depends on the rapid deployment of machine vision, analytics, AI, sensor data collection, and IIoT applications uniquely crafted for each of your edge devices over a uniform platform, we suggest adopting ASSET-Rx EDGE. Cloud Orchestrated from ASSET-Rx EDGE SYNC, the platform transforms industrial computers into multi-registry, multi-server Edge Processing Units for heterogeneous sensing applications.

ARM and x86 Systems Covered

ASSET-Rx EDGE Operates on High-Performance multi-core, GPU-enabled ARM-based edge processing hardware, in addition to x86 systems. We offer software solutions deployable on your hardware. Alternatively, pre-installed off-the-shelf and ready-to-use systems are available on request.

Mix and Match Your Existing or New Hardware

ASSET-Rx EDGE deployment accommodates the use of your existing computing hardware and components such as the integrated sensors in your machines, existing security cameras. It creates the pathway to scale the intelligence of your systems by adding new peripherals to your deployment as your operations and operational needs scale.

ASSET-Rx EDGE is a scalable platform for the development and deployment of applications at the edge, especially for machine vision and data acquisition applications. ASSET-Rx EDGE provides a component architecture, low-code tools for development and deployment, and a library of building blocks ranging from configurable production apps to example applications. Although our technology is general, we focus on the following areas:

•Support for edge devices running Linux: Edge devices containing support for many IO channels. Virtually any sensor or image capture device can be connected to our system.
•Machine vision/image processing: We focus on the acquisition of high resolution, high-speed images in the visual and IR ranges, and on the acquisition of data from “vision-like” systems such as LIDAR. We provide configurable components for the acquisition of images and video. We also support the acquisition of data from the other sensors found on these nodes: temperature, accelerometer, proximity, pressure, force, flow, energy, etc.
•Local inferencing and decision capabilities: Connectors from cameras and other sensors channel data to ML inferencing and to decision-making tools that use the output of the ML inferencing. These tools provide alarms, support for process control and command.
•Connectors to the cloud: Communications to services via RESTful transactions, MQTT, and other standard protocols.
•Scalable deployment: The end product of an ASSET-Rx EDGE development cycle is an application package with modular components that can be installed on 1 machine, 10 machines, or 1000 machines. This is a key advantage for system resellers and integrators.

ASSET-Rx EDGE framework provides scalability in deployment for edge computers. It is compatible with (and not competitive with) the platforms that provide compute and storage scalability over the network and in the cloud. Components in an ASSET-Rx EDGE enabled deployment scales up the hardware and provide entry points into Hadoop, Flink, Spark, and similar frameworks that normally reside in the cloud.