A full-stack edge-cloud architecture and four mutually reinforcing technical moats
The edge handles real-time and privacy-sensitive tasks; the cloud handles complex reasoning and continuous evolution
Real-time, privacy-sensitive perception and execution run entirely on-device β offline-capable
Complex reasoning, long-term memory, multi-agent orchestration and full device lifecycle management
Four mutually reinforcing core barriers
Leading foundation models in the cloud guarantee the ceiling of general intelligence, while fully self-developed differentiated small models on the edge are deeply optimized for companionship β flagship LLM experience at edge hardware cost.
Self-developed phoneme-level fuzzy matching keeps wake-up and recognition rates high even with children's accents, slurred speech and noisy environments β a key barrier for companion hardware.
Privacy-sensitive capabilities such as voice wake-up and vision run entirely on-device; only anonymized data flows back to the cloud for product and model iteration.
From chip adaptation, AI OS and model engineering to cloud platforms, the core technology chain is fully self-developed β no third-party black boxes, sustainable evolution.