YUZHH
On the morning of November 3, 2026, the Beijing–Dongguan matchmaking meeting and release of Dongguan's state-owned enterprise opportunity list took place on the third floor of the Dongguan Exhibition International Hotel. YUZHH was among the companies named on the place cards. A presentation on secondary water-supply pump rooms set out a particular facility, its problem and a proposed improvement.
This captures the idea behind an open use case. Organizations describe real operational problems so technology suppliers can test possible solutions in context. For an AI company, that offers a more concrete starting point than an exhibition, but it also requires more preparation. Here is how we read the policy and the opportunities.
What the event brought together
According to the invitation, the organizers were Dongguan's Development and Reform Bureau, municipal state-owned assets regulator and Beijing Liaison Office, with support from the Dongguan Application Scenario Innovation Center. The agenda included the opportunity list, municipal enterprises' requirements, pitches from Beijing suppliers and open discussion.
The invitation described a platform linking Beijing innovators with Dongguan state-owned enterprises to validate and apply technology in real business settings and support wider deployment. Beijing's innovative businesses supplied capabilities, while Dongguan's municipal companies set out demand.
The policy behind access and validation
In November 2025 the General Office of the State Council issued Implementation Opinions on Accelerating the Cultivation and Opening of Scenarios and Promoting Large-Scale Application of New Scenarios (No. 37 of 2025). This first systematic national deployment links technical breakthroughs, use-case validation, industrial application and system upgrades. It calls on state-owned enterprises, particularly centrally managed ones, to open core business settings to private companies, small businesses and research institutions, and calls for high-value AI use cases.
Dongguan subsequently issued its 2026–2028 implementation plan for innovative products and livable communities. Led by the municipal development and reform bureau and state assets regulator, it promotes access to core activities of central enterprises in Dongguan and municipal companies. It calls for regular capability lists, an online publishing platform, matchmaking, proposal refinement and pitches. AI and the wider use of agents are among its priorities.
At the Guangdong (Dongguan) Application Scenario Innovation Conference on March 24, 2026, the city published 160 opportunities and 106 capabilities. The November 3 event narrowed the focus to municipal enterprises and introduced suppliers from Beijing as part of regular matchmaking.
- State Council General Office: Implementation Opinions on Cultivating and Opening Scenarios (No. 37 of 2025)
- Dongguan: Implementation Plan for Cultivating and Opening New Application Scenarios (2026–2028)
- Nanfang Plus: What do Dongguan's two lists reveal about its ambitions? (March 24, 2026)
Four questions to ask of an opportunity
Listings often give just an organization, an activity and a desired result. Applying on the strength of a keyword can leave both sides stuck at their first meeting. Break the requirement into four questions and take any gaps to the discussion.
| Question | What to look for | When the answer is missing |
|---|---|---|
| Business problem | Who performs the work today? Which step takes the most labor or is prone to error? What exactly should become smarter? | Ask the host to walk through one complete current workflow before presenting a solution. |
| Existing conditions | Which systems and data exist? Who controls them? Can data leave the internal network, are labels available, and are equipment and connectivity adequate? | List data and permission requirements and confirm each one. They determine feasibility. |
| Evaluation | What is the pilot's scope and duration? Which metric defines success, and what is the comparison baseline? | Propose a small, measurable trial with clear criteria. |
| Ongoing operations | Who will use and maintain it, update the model and rules, and pay for the work after the pilot? | Set delivery boundaries before starting so somebody owns the next stage after successful validation. |
Suppose a host wants AI-assisted inspection in the pump rooms shown at the meeting. Manual checks may be infrequent and find faults late. Confirm sensors and connectivity, then consider a three-month trial at a few sites comparing alert accuracy and manual review volume. Assign responsibility for tuning alerts. This illustrates the method only. It does not describe the actual pilot.
What AI suppliers often overlook
- Data and security. Much state-owned enterprise data must stay inside its network. Establish local deployment options, how model calls travel and which data may be used for debugging.
- Outcome claims. Without a test on the customer's data, leave accuracy and labor savings for validation rather than promising figures.
- Human checks. State who verifies the output, at which step, and how to recover from an error.
- Exit conditions. Agree how to close a trial if it misses the criteria so that it does not continue indefinitely.
- Team and qualifications. Hosts check legal identity, experience and delivery capacity. Submitted materials should match the public record.
Access creates an opportunity to validate. Admission and expansion depend on the host's assessment and pilot results. An application or pitch establishes no partnership.
How hosts find potential suppliers
After a list is published, hosts face many unfamiliar suppliers. Beyond pitches and directories, they search company names and visit websites. Some ask assistants which companies handle a particular inspection task or what a supplier does. Those descriptions may influence the first shortlist.
An assistant may omit a supplier, repeat stale or incorrect information, or present a description that conflicts with its submitted capabilities. Publish verifiable facts about capabilities, reference cases and applicable settings. Observe answers across platforms, correct sources and check again.
This is part of generative engine optimization (GEO). Yuz GEO organizes brand facts, observes how AI describes a company and maintains its content. Desktop clients are available for Windows and macOS, with an optional managed service. Answers vary by question and time. Clearer information cannot guarantee mention or selection.
Our perspective
Exhibitions, pitches and opportunity lists now bring companies closer to concrete AI applications. Opening operational problems makes validation an early step toward collaboration. Suppliers gain more by describing boundaries and proposing a test than by showing more features. Accurate and consistent public information helps both sides decide whether to continue.