The market for efficient large AI model deployment is rapidly growing, especially on edge devices or with limited resources, indicating a large potential market. The technical approach of streaming weights from NVMe is innovative and feasible for a small team to build an MVP around, given the existing C inference engine. While there are many AI inference tools, this specific optimization for massive models on limited hardware presents a competitive niche. Localization is moderately feasible as the core technology is hardware-dependent, but the demand for AI model access can be global with appropriate business models.