Former Li Auto executives' robotics startup Zhijian Power approaches unicorn status with Tencent and Alibaba backing, prioritizing production-ready general-purpose robots over humanoids using adapted autonomous driving stacks.
Zhijian Power, an embodied AI startup founded by former Li Auto executives, is nearing a $1 billion valuation after securing multiple funding rounds from prominent investors including Tencent, Alibaba, and Sequoia China. The company, established in July 2025, aims to mass-produce general-purpose robots this year by repurposing autonomous driving technology originally developed for vehicles.
Core Technical Strategy
Rather than pursuing complex bipedal humanoids like Tesla's Optimus, Zhijian Power focuses on wheeled or tracked general-purpose robots designed for enterprise applications. This approach leverages existing autonomous driving stacks—including perception, navigation, and decision-making systems—originally created by founders Jia Peng (CEO, former Li Auto autonomous driving R&D head) and Wang Kai (Chairman, former Li Auto CTO). The technology transfer allows faster commercialization by adapting validated components:
- Sensor Fusion Systems: Reusing LiDAR, camera, and radar processing pipelines from automotive applications
- Motion Planning Algorithms: Modified pathfinding modules for indoor/industrial environments
- Control Systems: Adapted vehicle dynamics models for robotic platforms
Funding and Production Timeline
The company completed three funding rounds by October 2025 (Yuanjing Capital, Sequoia China, BlueRun Ventures), increasing registered capital from RMB 1M to RMB 15.19M (~$2.1M). A fourth round led by Tencent Investment with Alibaba, Legend Capital, and Lanfeng Capital participation has pushed Zhijian toward unicorn status. Capital will accelerate their 2026 production roadmap targeting B2B sectors like logistics and manufacturing.
Key Personnel Advantage
Recent hire Wang Jiajia—former Li Auto intelligent driving production lead—brings critical mass-production expertise. At Li Auto, he managed:
- Transition from map-based to map-free autonomous systems
- Deployment of end-to-end neural network architectures
- Commercial scaling of ADAS features across 300,000+ vehicles His experience in hardware-software integration addresses a common bottleneck in robotics commercialization.
Technical Constraints
Despite advantages, Zhijian faces significant challenges:
- Environmental Adaptation: Autonomous driving stacks excel in structured road environments but require retraining for unpredictable indoor spaces
- Power Efficiency: Vehicle-grade compute systems may prove overbuilt and energy-inefficient for stationary robots
- Competition: Enters crowded market against companies like Boston Dynamics and Geek+ with established industrial deployments
- Hardware Limitations: General-purpose designs risk being outperformed by task-specific robots in target verticals
Industry analysts note that while Zhijian's automotive tech reuse provides short-term advantages, long-term success depends on developing specialized robotics competencies beyond transplanted algorithms. The company's B2B focus avoids consumer market complexities but faces pressure to demonstrate ROI in enterprise settings where reliability requirements exceed those of prototype demonstrations.
Source: Leiphone (Original report in Chinese)
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