Project Background

We collaborated with a major Chinese conglomerate to help it quickly adapt its strategy to the rapid evolution of AI. Their key challenges included strategic conflicts, a fragmented ecosystem, no clear implementation plan for AI applications, and uncertain ROI on investments. Thus, they needed to build a coherent strategic framework for their AI ecosystem, clarifying the paradigm shift to large model-driven products and technology, as well as designing a practical roadmap for AI deployment.

Consulting Process

Based on the latest technological transformations driven by LLMs, as well as evolving product innovation systems and industry paradigms, we designed the client's AI strategy through the following phased approach: 1) Technology Paradigm Shift & Ecosystem Analysis: Analyzed large model evolution trajectory, dissected the impact of the 3 core paradigm shifts in compute, development, and interaction on the conglomerate’s business, including a thorough competitiveness assessment on existing technical architecture and ecosystem positioning; 2) AI Strategy Framework Design: Introduced our proprietary "ParaShift Cube" methodology to plan distinct roadmaps for both AI-native and AI-assisted products, differentiated between B2B and B2C scenarios, outlined potential AI Agent application archetypes, and formulated a strategy to scale from general-purpose models to specialized, vertical industry models; 3) Application & Implementation Roadmap: Leveraging the client's unique data assets and industry-specific use cases, developed a detailed roadmap for business "intelligentization" and proposed customized solutions, including continued pre-training, model distillation, and Retrieval-Augmented Generation (RAG); 4) Organizational Design & Ecosystem Synergy: designed a restructured, AI-native team architecture, established a "Data-Algorithm-Compute" synergy framework to integrate internal compute resources with partner capabilities, culminating in the design of a platform-based ecosystem strategy.

Collaborative Achievements

We delivered a comprehensive AI ecosystem roadmap, defined clear investment priorities under the three paradigms, and developed a technology maturity assessment model for AI. Additionally, we analyzed core scenarios for smart cities, helping the enterprise build a framework to enhance the quality of its intelligent business avenues. We also directed the launch of an industry AI Agent platform with 30+ partners onboarded, dramatically increasing compute resource efficiency and building a strong technological moat. Ultimately, this project enabled the client's strategic leap from a traditional architecture to an intelligent paradigm, allowing them to lead their industry's intelligent transformation.

Project Background

A leading architectural design firm faced mounting pressure from challenges such as increased competition, compressed timelines, and more complex projects. To stay competitive, they aimed to leverage large model technology to increase design efficiency and creativity. Although the firm has extensive design expertise and a wealth of past project data, they lacked the knowledge to apply AI systematically, thus needing a professional consulting team to deliver a comprehensive, AI-driven solution for their design workflow.

Consulting Process

We began by conducting in-depth interviews across the firm to understand their workflows, tools, and pain points. We then systematically introduced their team to the principles, limits, and trends of large model technology. Supplemented by cutting-edge case studies of AI applications in the architectural design field from both domestic and international sources, with a special focus on recent advancements in areas like spatial planning, intelligent layout generation, and parametric design, helping the client establish a robust conceptual framework for understanding AI. Working closely with the firm, we pinpointed several measurable and closed-loop stages in their design workflow, including initial data analysis and organization, site analysis, design alternative generation and evaluation, regulatory compliance checks, and other key nodes. For each stage, we designed specific AI entry points and value-loop models to ensure the technology complements and enhances the designers' professional skills.

Collaborative Achievements

We successfully defined and delivered a clear roadmap for the client's AI adoption, including a phased plan and value assessment metrics. We then co-developed two key prototypes with the client: an intelligent layout generator based on design requirements, as well as a design prototype generation and comparison platform, both of which were highly acclaimed by the team. These successful prototype systems have laid a solid foundation for the client's subsequent, full-scale transformation toward AI-integrated applications.