Focus
When Technology Meets Reality
Our team is acutely aware of the challenges faced in the current industry landscape, where development predominantly relies on cloud-based AI solutions.
The deployment and integration of edge-AI are imperative, yet the development solutions to support its adoption is insufficient.
The deployment of existing solutions to the diverse environments of edge devices presents significant hurdles.
This often results in escalated development costs and instances where performance targets are not met.
We consider these issues critical and are dedicated to pioneering solutions that will not only overcome these obstacles but also set new standards in efficiency and innovation.
Tackling Edge-AI’s Challenges
In the face of diverse hardware and operating system environments, meticulous hardware analysis for optimization and deployment of AI models becomes essential, making its Automated Machine Learning (AutoML) a challenging yet crucial process.
Our team is dedicated to harnessing the power of AutoML-based hardware analysis tools to support optimization and deployment of AI models on edge environments.
This commitment enables us to enhance development efficiency and achieve superior performance levels.
We are determined to exceed the industry’s evolving demands, ensuring our partners become part of the future of Edge-AI with our transformative technology.
The Challenges of Developing Edge-AI
