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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AI’s expansion into the physical world is reshaping what investors choose to back
Updated
March 17, 2026 1:02 AM
Exterior view of the Exchange Square in Central, Hong Kong. PHOTO: UNSPLASH
Artificial intelligence is often discussed in terms of large models trained in distant data centres. Less visible, but increasingly consequential, is the layer of computing that enables machines to interpret and respond to the physical world in real-time. As AI systems move from abstract software into vehicles, cameras and factory equipment, the chips that power on-device decision-making are becoming strategic assets in their own right.
It is within this shift that Axera, a Shanghai-based semiconductor company, began trading on the Hong Kong Stock Exchange on February 10 under the ticker symbol 00600.HK. The company priced its shares at HK$28.2, debuting with a market capitalization of approximately HK$16.6 billion. Its listing marks the first time a Chinese company focused primarily on AI perception and edge inference chips has gone public in the city — a milestone that underscores growing investor interest in the hardware layer of artificial intelligence.
The listing comes at a time when demand for flexible, on-device intelligence is expanding. As manufacturers, automakers and infrastructure operators integrate AI into physical systems, the need for specialized processors capable of handling visual and sensor data efficiently has grown. At the same time, China’s domestic semiconductor industry has faced increasing pressure to build local capabilities across the chip value chain. Companies such as Axera sit at the intersection of these dynamics, serving both commercial markets and broader industrial policy priorities.
For Hong Kong, the debut adds to a cohort of technology companies seeking public capital to scale hardware-intensive businesses. Unlike software firms, semiconductor designers operate in a capital-intensive environment shaped by supply chains, fabrication partnerships and rapid product cycles. Their presence on the exchange reflects a maturing investor appetite for AI infrastructure, not just consumer-facing applications.
Axera’s early backer, Qiming Venture Partners, led the company’s pre-A financing round in 2020 and continued to participate in subsequent rounds. Prior to the IPO, it held more than 6 percent of the company, making it the second-largest institutional investor. The public offering provides liquidity for early investors and new funding for a company operating in a highly competitive and technologically demanding sector.
Axera’s market debut does not resolve the competitive challenges of the semiconductor industry, where innovation cycles are short and global competition is intense. But it does signal that investors are placing tangible value on the hardware, enabling AI’s expansion beyond the cloud. In that sense, the listing represents more than a corporate milestone; it reflects a broader transition in how artificial intelligence is built, deployed and financed — moving steadily from software abstraction toward the silicon that makes real-world autonomy possible.