On July 3rd, the Digital Circulation Forum and Logistics Data & Artificial Intelligence Conference of the 2026 Global Digital Economy Summit was held in Beijing.

During the event, the Big Data Branch of the China Federation of Logistics & Purchasing released the "2026 Logistics Supply Chain Big Data and AI Application Typical Case Studies."

The application practice of a warehouse digital intelligence operation platform built by Kejie, a subsidiary of DC HOLDINGS (00861), based on a closed-loop "Five-Step Method," was successfully selected.

This case focuses on long-standing pain points in the warehousing and logistics industry, such as reliance on individual experience, delayed response to exceptions, inefficient cross-role collaboration, and inconsistent multi-warehouse management standards.

By establishing a digital operation platform, it transforms frontline operational experience, work data, and management rules into replicable, executable, and evolving intelligent operational capabilities.

This case also represents a successful implementation of Kejie Logistics's enterprise-level intelligent agent cluster, "Xiaojin," in the direction of warehouse digital intelligence.

In this case, Kejie has constructed a matrix-style operational architecture featuring "1 data lake, 6 major work platforms, and multiple role positions," covering key roles such as warehouse supervisors, warehouse managers, customer service, transportation, industry account managers, and management decision-makers.

Core Innovations in the Approach

The core innovation lies in the closed-loop "Five-Step Method" design integrated across all dashboards: "Assess Status, Analyze Trends, Identify Issues, Diagnose Causes, Execute Actions."

Unlike traditional dashboards that only display results, Kejie's platform emphasizes the closed-loop transformation from data discovery to business action.

More importantly, this project transforms warehouse management capabilities, which were long dependent on individual experience, into digital assets that can be accumulated by the enterprise.

Through rule engine implementation, visual diagnostics, and dynamic threshold configuration, Kejie encodes the tacit knowledge of expert order processors, top pickers, and seasoned warehouse supervisors into system rules.

The project has already codified over 200 management rules, enabling the replication of best practices from top supervisors across different warehouses and supporting standardized operations within a national multi-warehouse network.

Advancing AI Integration

Against the backdrop of Kejie's comprehensive push for AI transformation, this case also provides an important foundational scenario for the deployment of the Xiaojin intelligent agents.

The processes of problem identification, root cause analysis, task assignment, execution tracking, and review within warehouse operations naturally correspond to the capability chain of role-specific intelligent agents.

With the further introduction of large AI models, predictive algorithms, and automated linkage capabilities, the platform will evolve from "visibility and control" towards "prediction, suggestion, and execution," promoting the true embedding of Xiaojin role agents into specific workflows for supervisors, customer service, transportation dispatchers, and business analysts.

Relevant data shows that Kejie has built over 40 visual work platforms for key roles including warehouse supervisors, managers, customer service, transportation, industry specialists, and management, serving core positions nearly ten thousand times daily on average.

For instance, the intelligent picking heatmap platform for warehouse supervisors can identify area congestion in real-time, automatically suggest adjusting picking waves and optimizing bin locations, resulting in a 15% reduction in picking paths and a 40% decrease in waiting time for order verification.

The inventory management platform for warehouse managers uses AI to drill down and analyze stagnant stock, generating clearance lists for execution, which has helped a cosmetics client reduce inventory turnover days from 45 to 30 and cut the proportion of stagnant materials by 25%.

Measurable Performance Improvements

In terms of operational efficiency, the response to warehouse exceptions has been upgraded from lagging investigations of over half an hour to real-time Xiaojin alerts, improving response speed by 80%.

Access to various business performance indicators is now achieved in seconds, reducing query time by 90%.

The training cycle for new warehouse personnel has been compressed from 2-3 months to 1 month, significantly lowering personnel training costs.

Regarding cost and service, leveraging Xiaojin's intelligent control over assets and packaging materials has led to a 15% reduction in packaging material capital tie-up and a 20% decrease in equipment failure rates.

The 24-hour transit fulfillment rate for cosmetics business has been elevated to over 99%.

Furthermore, by integrating with the customer service platform, Xiaojin proactively predicts and pushes delay information, significantly enhancing customer service experience.

The efficiency gap between personnel across different warehouses has narrowed from 20% to within 5%, achieving unified standardized management nationwide.

This industry recognition affirms Kejie Logistics's practice in warehouse digital intelligence and marks the company's ongoing advancement under its positioning as a "technology-driven industry supply chain expert."

This advancement involves a capability leap from empiricism to digital-intelligent operations, from internal efficiency gains to customer enablement, and from system tools to AI agents.

Looking ahead, Kejie will continue to focus on developing the Xiaojin intelligent agents and industry digital intelligence solutions.

It aims to promote the deep integration of AI capabilities with core links such as warehousing, transportation, fulfillment, customer service, and management decision-making.

The goal is to provide clients with more agile, transparent, and intelligent supply chain services, enabling AI to truly enter workflows, assist in decision-making, and enhance execution efficiency, thereby offering a replicable practical model for the digital-intelligent transformation of the logistics industry.