Industries & Cases

CoT Network has accumulated AI project experience across multiple industries. In keeping with client confidentiality, the following cases are displayed by industry and organizational type.

ENER

Energy", "client": "Large Central SOE", "description": "Built knowledge management and internal intelligent Q&A systems, enabling efficient accumulation, retrieval, and reuse of specialized knowledge.

CONS

Construction & Engineering", "client": "Leading State-Owned Enterprise", "description": "Combined with project-based management scenarios, organized business processes and documentation systems, exploring AI-assisted knowledge extraction, project support, and management efficiency.

MANU

Manufacturing", "client": "Large State-Owned Group", "description": "Designed enterprise-level AI application roadmaps around production, management, and internal collaboration scenarios, driving pilot deployment of core scenarios.

TRAN

Transportation & Logistics", "client": "Central Enterprise System Unit", "description": "Focused on business knowledge distribution, process assistance, and operational support to drive AI adoption for internal service efficiency improvement.

FINA

Financial Services", "client": "State Capital-Backed Institution", "description": "Built intelligent assistance systems for professional roles around compliance, knowledge services, and internal operational support.

CONS

Consumer Goods", "client": "Large Enterprise Group", "description": "Combined with market, operations, and sales management needs, exploring comprehensive AI applications in business analysis, content assistance, and management support.

PHAR

Pharmaceutical & Healthcare", "client": "State-Backed Platform", "description": "Advanced integration of AI capabilities with existing business systems around knowledge systems, process optimization, and professional service support.

EDUC

Education & Training", "client": "Large Institution", "description": "Built AI-assisted applications and content production support systems with course content, knowledge services, and internal operational efficiency as the core.

Different Industries, Same Underlying Logic

While AI applications differ across industries, successful projects share similar underlying logic: starting from real business problems, under organizationally feasible conditions, progressively building deployable, measurable, and replicable capabilities.