Low Latency and Real-Time Response
Real-time data processing is performed at the frontend to minimize the latency of data upload to the cloud and ensure response in milliseconds.
High Security and Privacy Protection
Data is processed locally, which reduces the chance of sensitive information being uploaded to the cloud, lowers the risk of data leakage, and ensures data security during transmission and storage.
Multiple Algorithms and Flexible Load
Supports flexible load and dynamic scheduling of multiple algorithms, and tailors high-precision algorithms to meet industry-specific needs.
Low Bandwidth Requirements and High Cost-Effectiveness
Only a small amount of processing results is transmitted rather than a massive amount of raw data, which greatly lowers the requirements for network bandwidth.
Flexible Deployment and High Adaptability
Features a small size, low power consumption, and flexible deployment in various environments; is ready to use right out of the box, with no need to change the approach to networking. Supports connection over the standard industrial personal computer(IPC) protocol, and can be quickly deployed to meet diverse needs.
Offline Operation and High Stability
Even without internet access, it can run normally to ensure business continuity.
Open Ecosystem and Various Interfaces
Supports mainstream AI frameworks, allows for efficient algorithm development, and provides a wealth of hardware interfaces. Compatible with industrial personal computer (IPC), panel machine, and other devices under mainstream protocols.
Edge-Cloud Collaboration and Efficient Management
Supports edge-cloud collaboration, and forms a closed loop from model training to business application to model optimization through a unified device management platform and AI development platform. Its one-stop edge device management backend makes it easy to complete deployment in a short period of time and implement efficient management.
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