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.
Keep Reading
Inside the funding round driving the shift to intelligent construction fleets
Updated
March 17, 2026 1:02 AM
Aerial shot of an excavator. PHOTO: UNSPLASH
Bedrock Robotics has raised US$270 million in Series B funding as it works to integrate greater automation into the construction industry. The round, co-led by CapitalG and the Valor Atreides AI Fund, values the San Francisco-based company at US$1.75 billion, bringing its total funding to more than US$350 million.
The size of the investment reflects growing interest in technologies that can change how large infrastructure and industrial projects are built. Bedrock is not trying to reinvent construction from scratch. Instead, it is focused on upgrading the machines contractors already use—so they can work more efficiently, safely and consistently.
Founded in 2024 by former Waymo engineers, Bedrock develops systems that allow heavy equipment to operate with increasing levels of autonomy. Its software and hardware can be retrofitted onto machines such as excavators, bulldozers and loaders. Rather than relying on one-off robotic tools, the company is building a connected platform that lets fleets of machines understand their surroundings and coordinate with one another on job sites.
This is what Bedrock calls “system-level autonomy”. Its technology combines cameras, lidar and AI models to help machines perceive terrain, detect obstacles, track work progress and carry out tasks like digging and grading with precision. Human supervisors remain in control, monitoring operations and stepping in when needed. Over time, Bedrock aims to reduce the amount of direct intervention those machines require.
The funding comes as contractors face rising pressure to deliver projects faster and with fewer available workers. In the press release, Bedrock notes that the industry needs nearly 800,000 additional workers over the next two years and that project backlogs have grown to more than eight months. These constraints are pushing firms to explore new ways to keep sites productive without compromising safety or quality.
Bedrock states that autonomy can help address those challenges. Not by removing people from the equation—but by allowing crews to supervise more equipment at once and reduce idle time. If machines can operate longer, with better awareness of their environment, sites can run more smoothly and with fewer disruptions.
The company has already started deploying its system in large-scale excavation work, including manufacturing and infrastructure projects. Contractors are using Bedrock’s platform to test how autonomous equipment can support real-world operations at scale, particularly in earthmoving tasks that demand precision and consistency.
From a business standpoint, the Series B funding will allow Bedrock to expand both its technology and its customer deployments. The company has also strengthened its leadership team with senior hires from Meta and Waymo, deepening its focus on AI evaluation, safety and operational growth. Bedrock says it is targeting its first fully operator-less excavator deployments with customers in 2026—a milestone for autonomy in complex construction equipment.
In that context, this round is not just about capital. It is about giving Bedrock the runway to prove that autonomous systems can move from controlled pilots into everyday use on job sites. The company bets that the future of construction will be shaped less by individual machines—and more by coordinated, intelligent systems that work alongside human crews.