DEEPX partners with KT and Sesol to target the NPU-based on-device AI video analysis market. The three companies plan to jointly develop an AI Edge Box featuring low power consumption and low heat generation, and expand the scope of service application to various industrial sites, including EV charging stations, mobile CCTVs, and traffic infrastructure.

On the 29th, DeepX signed a three-party Memorandum of Understanding (MOU) for NPU-based on-device AIoT business cooperation with KT and Cesol, a company specializing in transportation and commercial vehicle terminals and AI Edge Boxes.

In this agreement, each company divided roles according to their capabilities.

KT is responsible for the commercialization and market expansion of the AI Edge Box service based on its stable network and control platform.

DeepX provides its self-developed ultra-low power NPU chip 'DX-M1' and SDK, and Cesol is responsible for the development, manufacturing, and field demonstration of the AI Edge Box using this.

The joint initiatives agreed upon by the three companies are: joint development of an NPU-based AI Edge Box; joint participation in on-device AIoT businesses; expansion of the AI video surveillance market within transportation infrastructure, such as EV charging stations, buses, and commercial vehicles; and revitalization of the domestic AI Edge ecosystem.

DeepX explained that the AI Edge Box being developed through this collaboration is designed to reduce power consumption and heat generation compared to GPU-based equipment, and to enable real-time AI inference on-site without a cloud connection.

DX-M1 is an on-device AI semiconductor applicable to various Edge AI environments, such as industrial cameras, robots, smart cities, and transportation infrastructure.

Kim Nok-won, CEO of DeepX, stated, “As AI spreads into industrial sites, the importance of on-device AI capable of processing data in real-time with low power consumption is growing even more.”"We will combine the technologies of the three companies to implement AI Edge solutions that can be practically utilized in various industrial fields and contribute to the expansion of the domestic on-device AIoT ecosystem," he said.