AmberFlux Opus for Manufacturing

AmberFlux Opus microproduct range provides cognitive inferencing at low cost edge devices like mobile phones, IOT, microcontrollers, wearables, appliances, machinery, WiFi Routers, etc. Enterprises can leverage their existing designs for enabling them for EdgeAI for sensor data analysis and IoT. Opus’s deep learning model ensures both learning and inferencing can be done on the Edge Devices powered by low-cost, low-power processors, including most of the existing generation of microcontrollers. Opus framework enables AmberFlux to release EdgeAI inference microproducts in 30-60 days per feature to ensure our customers can have the early mover advantage.

The challenge of fitting any learning and analysis on the low-compute microcontrollers, can be overcome with Opus deep learning model giving unhindered flexibility to enterprises to provide analysis, and inferencing on the edge devices. Using Opus microproducts, the end-users can have real-time access to the health of the machinery, appliances, IoT, devices, wearables etc., without waiting for data being referenced back to the cloud and receiving the inferencing back. This will also save valuable time and send only relevant data to the cloud for further analysis and fine-tuning inferencing.

Using Opus, Manufacturers can leverage their existing designs for enabling them for EdgeAI for sensor data analysis and IoT. Using Opus Framework, we can built lightweight, containerized, microproducts for manufacturing companies to enable a range of products like industrial machinery, tools, commercial and domestic appliances, rolling stock, process machinery, etc., for AI learning, analyzing, and inferencing at the Edge. Manufacturing companies can receive critical information on the condition of their equipment like temperature, vibration, sound, color, etc., Opus framework enables manufacturing companies to manage multiple feature data on a single microcontroller without redesign or making radical changes to their operational processes.

Opus products can be integrated to existing enterprise applications or customer management solutions to enable the manufacturing companies to receive the data and alerts from edge devices. This would provide these companies valuable information for predictive maintenance, and critical inputs on the usage of machinery for product improvements.