The traditional market for telecom operators is nearing saturation. However, with the rapid rise of AI technology, new opportunities in intelligent applications across industries are emerging. According to reports, the global smart applications market is projected to grow at a CAGR of 31.7% from 2025 to 2033, reaching $488.54 billion by 2033. To harness this opportunity, telecom operators should offer integrated computing and network services to support industrial AI applications, lowering the barriers and costs of these foundational resources and fostering their own “second growth curve.” However, operators face several issues when providing computing-network services. * First, the complexity of industry intelligent services requires operators to understand industry business characteristics, diverse resource characteristics, and integration of heterogeneous products / resources to meet customized B2B needs, leading to difficult business analysis and long configuration time. * Second, high AI resource costs—smart computing resources and networks for AI-driven applications are costly, and inefficient allocation prevents operators from achieving economies of scale. Additionally, the intensive computing nature of AI-driven applications greatly increases resource energy consumption and power costs. * Third, complex operation and maintenance (O&M) of heterogeneous resources across computing-network domains raises O&M difficulties and weakens service guarantee. In conclusion, ineffective operation means may cause operator margins to fall short of expectations. To address these challenges, this Catalyst project aims to build an intelligent infrastructure that integrates network and computing resources, enabling efficient deployment of vertical AI applications. By leveraging Agentic AI and autonomous operations, the project will enable intelligent understanding of industrial AI workloads, precise resource matching, dynamic scheduling, cross-domain operational assurance, and holistic energy-saving strategies. The project will focus on AI medical imaging in healthcare as the initial application scenario, lowering costs and barriers for hospitals and offering strong replicability for other AI healthcare use cases and cross-industry adoption, empowering telecom operators to explore new markets.