Ugreen pushes smart home control back into the living room

Ugreen has officially entered the AIoT market with the launch of its HomeAgent smart home ecosystem. The system is built around a local-first architecture, meaning that data processing, storage, and device control happen directly within the home rather than relying on remote cloud servers. This approach is designed to eliminate monthly storage fees and reduce the latency associated with sending household data to external data centers.

The launch includes two hub models, three security cameras, a smart speaker, and digital display frames. By keeping sensitive information like surveillance footage and personal photos on local hardware, Ugreen positions the system as a privacy-focused alternative to traditional cloud-based smart home setups. The company, which serves over 300 million users globally, is leveraging its existing hardware expertise to create a unified platform for managing household devices.

Hardware drives local processing

At the center of the lineup is the HomeAgent HA100, a hub that combines storage, security, and smart home control into a single unit. It processes files and surveillance footage locally, allowing for real-time responses without internet dependency. For users with heavier workloads, the HA100 Pro offers faster network connectivity and enhanced AI capabilities, such as voice-based rule creation and context-aware device control.

The most powerful option is the MasterAgent MA100, which utilizes NVIDIA Jetson Thor T5000 technology. This hub is designed to run larger AI models and manage multiple complex tasks simultaneously. It serves as a local brain for the home, capable of interpreting rich context and coordinating various devices without needing to send data off-site for processing.

Privacy features and user control

The system supports Matter, an industry standard that allows devices from different brands to work together. This interoperability lets users create automation scenes involving third-party products while maintaining local control. Ugreen’s voice assistant, Uliya, can manage supported devices, check live status, and review event history, all while keeping the data within the local network.

A key differentiator is the ability to preserve personal moments rather than just recording security incidents. The system can identify highlights from live video and photo libraries, automatically generate highlight videos, and display them on Gallery smart frames. This feature transforms the smart home from a security tool into a lifestyle device that curates family memories locally.

Trade-offs in local AI

While local processing offers significant privacy benefits, it places a higher demand on the home’s hardware and network infrastructure. Users must ensure their local setup can handle the computational load of advanced AI tasks, such as person recognition and vehicle detection. This trade-off means that while the system reduces reliance on third-party servers, it requires a robust local environment to function optimally.

According to GN technics/smarthome, the launch reflects a broader shift in the market toward on-device intelligence. By keeping data in the home, manufacturers are addressing growing concerns about data ownership and security. However, this approach also means that users bear the responsibility for maintaining the local hardware and ensuring that the system remains updated and secure against local threats.

Local processing enhances privacy and speed

The updated reporting confirms that Ugreen’s design philosophy centers on keeping data processing within the home rather than relying on external cloud servers. By handling tasks locally, the system is engineered to significantly reduce response times, ensuring that commands and automations execute with minimal delay.

This architectural choice also serves to strengthen user privacy. Since sensitive information such as surveillance footage and personal media remains on the local hardware, the risk of data exposure through third-party cloud infrastructure is substantially lowered. This approach aligns with a broader industry trend toward local-first computing in residential technology.