How ChinaMarket uses digital tools to make cross-border sourcing faster and more accessible for smaller businesses
A rack of colourful scarves. PHOTO: UNSPLASH
The 5th RCEP (Shandong) Import Commodities Expo opened this week at the Linyi International Expo Center, bringing together more than 5,300 buyers and over 400 exhibitors from 48 countries. Alongside the scale of the event, a quieter shift was visible in how trade itself is being organised.
ChinaMarket, the official platform of Linyi Mall, used the expo to show how sourcing is moving from manual coordination to software-led systems. On the first day, it hosted procurement matchmaking sessions and signed agreements with buyer groups from Argentina, South Korea and Ghana. But the focus was less on the deals themselves and more on the mechanism behind them.
The platform operates as a structured network of verified manufacturers, grouped by industrial clusters. Instead of buyers searching supplier by supplier, the system uses data and AI tools to match demand with production capacity. At the expo, this process was made visible through real-time data screens and guided sourcing sessions, where procurement teams connected directly with factories across categories such as building materials, textiles and electronics.
"Sourcing suppliers separately was time-consuming and inefficient. ChinaMarket accurately matches our needs and recommends reliable factories, saving us considerable effort," commented an Argentine buyer.
The underlying problem being addressed is not new. Cross-border sourcing is often slow, fragmented and dependent on intermediaries. What is changing is how that process is being compressed. By combining supplier verification, demand matching and communication into a single system, platforms like ChinaMarket aim to shorten sourcing cycles. They also reduce uncertainty in procurement decisions.
Financing is another layer where the model is evolving. Even when suppliers and buyers are matched efficiently, access to capital can still slow transactions down. Small and medium-sized firms often face constraints around payment terms and access to credit in international trade.
ChinaMarket’s “data + order financing” model links transaction data with financial services, allowing funding decisions to be tied more directly to verified orders rather than external collateral. In practice, this shifts part of the risk assessment from institutions to platform-level data.
The company is also extending this structure into agricultural supply chains. At the expo, it signed an agreement with a local government in Yinan County to build a digitally managed agricultural belt. The model combines sourcing at origin with platform distribution, with an emphasis on traceability for buyers across RCEP markets. This reflects a broader attempt to standardise supply visibility in sectors that are typically less digitised.
Geographically, the platform has been expanding into Southeast Asia. It has launched a digital marketplace in Malaysia and established operations in Indonesia, including support for government-linked procurement projects. These moves suggest a focus on embedding the platform within regional trade flows rather than operating as a standalone marketplace.
"We aim to be a 'super connector' between Chinese industrial belts and global markets", said Quan Chuanxiao, Chairman of Depth Digital Technology Group and ChinaMarket. "By digitizing the cross-border trade process, we solve trust and efficiency issues, making it simpler, faster, and more reliable for overseas buyers to source from China".
What emerges from the expo is less about a single platform and more about a shift in infrastructure. Trade is gradually moving toward systems where discovery, verification, negotiation and financing are handled within integrated digital layers. The question is not whether sourcing can be digitised, but how reliably these systems can scale across industries where trust and execution still depend on physical outcomes.
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Rethinking 3D modelling for a world that generates too much, too quickly.
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January 8, 2026 6:32 PM
A hologram in the franchise Star Wars, in Walt Disney World Resort, Orlando. PHOTO: UNSPLASH
MicroCloud Hologram Inc. (NASDAQ: HOLO), a technology service provider recognized for its holography and imaging systems, is now expanding into a more advanced realm: a quantum-driven 3D intelligent model. The goal is to generate detailed 3D models and images with far less manual effort — a need that has only grown as industries flood the world with more visual data every year.
The concept is straightforward, even if the technology behind it isn’t. Traditional 3D modeling workflows are slow, fragmented and depend on large teams to clean datasets, train models, adjust parameters and fine-tune every output. HOLO is trying to close that gap by combining quantum computing with AI-powered 3D modeling, enabling the system to process massive datasets quickly and automatically produce high-precision 3D assets with much less human involvement.
To achieve this, the company developed a distributed architecture comprising of several specialized subsystems. One subsystem collects and cleans raw visual data from different sources. Another uses quantum deep learning to understand patterns in that data. A third converts the trained model into ready-to-use 3D assets based on user inputs. Additional modules manage visualization, secure data storage and system-wide protection — all supported by quantum-level encryption. Each subsystem runs in its own container and communicates through encrypted interfaces, allowing flexible upgrades and scaling without disrupting the entire system.
Why this matters: Industries ranging from gaming and film to manufacturing, simulation and digital twins are rapidly increasing their reliance on 3D content. The real bottleneck isn’t creativity — it’s time. Producing accurate, high-quality 3D assets still requires a huge amount of manual processing. HOLO’s approach attempts to lighten that workload by utilizing quantum tools to speed up data processing, model training, generation and scaling, while keeping user data secure.
According to the company, the system’s biggest advantages include its ability to handle massive datasets more efficiently, generate precise 3D models with fewer manual steps, and scale easily thanks to its modular, quantum-optimized design. Whether quantum computing will become a mainstream part of 3D production remains an open question. Still, the model shows how companies are beginning to rethink traditional 3D workflows as demand for high-quality digital content continues to surge.