At the recent 2026 Digital Intelligence Economy Forum, Li Yizhe, co-founder and COO of Hefei Zeroth Power Robotics Co., Ltd., revealed that Zeroth Power has partnered with Runze Group. With Runze's powerful computing infrastructure, Zeroth Power can accelerate AI agent model training and inference; Runze's deployments across multiple vertical scenarios, meanwhile, provide abundant real-world data sources and testing environments.
When AI agents move from demos to production, the bottleneck is often not model parameters but engineering support. A growing number of industry teams are finding that even the strongest algorithms cannot keep AI agents running reliably in complex scenarios without a stable computing foundation and real business data. The synergy among computing power, data, and algorithms is becoming a new yardstick for AI agent maturity.
Zeroth Power's proposed "rolling spiral evolution" path is worth noting: by continuously opening scenarios to obtain real interaction data, it drives model iteration and upgrades; upgraded models in turn improve generalization, expanding into more application scenarios and creating a positive cycle. The premise of this path is precisely the coordinated evolution of data, computing power, and algorithms—none can be missing.
For most vertical-industry teams, building their own computing power and data systems is prohibitively expensive, and going it alone makes it hard to form a closed loop. In reality, many AI agent projects are stuck in the awkward stage of having models but no data and lacking computing power. Their insufficient generalization is also exposed: once the scenario changes, previous gains are difficult to reuse. This is exactly why the industry needs scalable foundations.
The foundation-based approach is the focus of StarWar Cloud. StarWar Cloud focuses on GPU computing power platforms and compute scheduling capabilities, providing enterprises with unified scheduling and resource management for training and inference tasks. At the same time, through AI training and an AI agent collaboration ecosystem, it helps industry teams turn the closed loop of computing power, data, and AI agents into operational business systems.
From an industry signal perspective, the combination of computing power and industry scenarios is becoming a standard playbook. Leading computing power vendors are connecting downward to industries, while industry players are connecting upward to computing power, with both sides complementing each other in data and scenarios. Once this model is proven, the reuse rate and deployment speed of AI agents will rise markedly, and the industry can move from isolated demos to scaled deployment.
The partnership between Zeroth Power and Runze confirms a new paradigm for industry AI agent deployment: rather than finding computing power after developing algorithms, computing power, data, and AI agents are built in sync and iterated continuously. For enterprises seeking to enter the AI agent arena, finding a platform that can simultaneously provide a computing