XPeng Group's first AI Open Competition concludes; a frontline supply-chain employee used Qoder to build the supply-chain risk management platform "Baize" and won the title, boosting risk-screening efficiency 96x
On June 30, 2026, XPeng Group's first AI Open Competition officially came to a close. Launched in May, the competition featured three major tracks and was open to internal employees, employees' family members, and university students nationwide—with no barriers and no professional-background restrictions throughout. It drew more than 21,000 registrations in total, with participating teams including 200 employee-family squads and over 440 university student teams. Qoder, the AI product from Alibaba, served as a key partner of the event, providing technical support and AI capability enablement.
XPeng Group Chairman and CEO He Xiaopeng delivered remarks on site after the competition. He said that XPeng is using AI to drive organizational efficiency, and that AI is no longer exclusive to R&D but has permeated every role and process—"in the future, AI-driven efficiency gains will gradually move from the hundred-million level to the billion level each year, and even larger." In He Xiaopeng's view, AI should play the role of "amplifying employees" rather than replacing them; the core of technology equality is to dismantle technical barriers, so that "everyone can become a creator and beneficiary of technology."
One noteworthy figure: over 50% of the participants in this competition came from non-technical roles. Procurement, supply chain, finance, marketing, quality—these roles that had never written code before stepped onto XPeng's tech stage for the first time as creators of AI products.
Among the most talked-about works at the finals, "Baize," the champion of Track Three "Efficiency Leap," stood out—it was built by a frontline employee from XPeng's supply chain, using Qoder as the creation tool. The author does not come from a traditional technical background but from the supply-chain front line, with a deeper understanding of real business scenarios.
Baize is a complete supply-chain risk management platform. It has 77 built-in risk factors spanning 7 major categories—credit risk, corporate operations, news and public opinion, disaster risk, capacity and delivery, quality, and supporting facilities—while covering 13 primary categories under the two procurement systems of strategic procurement and spot procurement. It comprehensively applies Agent orchestration, large-model reasoning, RAG knowledge enhancement, and time-series forecasting algorithms to achieve 24/7 automated monitoring of full-chain supplier dynamics.
At the risk-governance layer, Baize has handled 100,000+ risk events cumulatively. The platform's built-in risk-disposition generation Agent automatically summarizes events after they occur, distills the core conflicts, provides disposition strategies, and assigns responsible owners. Work that originally required the supply-chain, procurement, and quality teams to coordinate for an entire day can now have AI quickly generate preliminary analysis and disposition recommendations, which business staff then review and refine. At the risk-prediction layer, Baize overlays the EWMA model with large-model AI capabilities to produce a two-dimensional risk-prediction leaderboard across vehicle models and suppliers. After going live, risk-screening efficiency improved 96x, monthly reporting efficiency improved 120x, risk-warning response was shortened to within 5 minutes, and ROI exceeded 35x.
The Baize project was led and built by XPeng's supply-chain business staff, with Qoder providing AI capability support for some of the business scenarios.
First, turning business language directly into AI instructions. Supply-chain staff understand best "what counts as an anomaly" and "what kind of supplier needs an alert," and Qoder helps them quickly convert business experience into reusable AI application capabilities. For Baize's automatic identification of news and public-opinion risks, automatic correlation of credit anomalies, and automatic estimation of capacity bottlenecks, staff turned years of accumulated business experience into more efficient application workflows through Qoder.
Second, an end-to-end loop from idea to usable product. Baize has a complete login page, dashboard, model management, data management, event management, Agent disposition reports, and a risk-prediction module—and is currently in use in relevant business scenarios. Qoder provided AI Coding capability support during project development, helping improve business development efficiency and forming a collaboration model of "business poses the problem, AI assists, technology backstops," further shortening the development cycle of business systems.
Third, precipitating enterprise domain knowledge into reusable AI capabilities. Baize's built-in 77 risk factors and 7 major risk templates are essentially the business experience accumulated over many years by XPeng's supply chain—they were structurally precipitated through Qoder and can be further reused across different business scenarios.
XPeng and Alibaba Cloud have long deepened their collaboration. In the autonomous-driving field, XPeng's second-generation VLA model is trained on Alibaba Cloud's full-stack AI capabilities, with cluster operating efficiency consistently maintained above 90% year-round. XPeng has deployed a foundation model with 72 billion ultra-large-scale parameters in the cloud, with the model completing a full-chain iteration every five days. On the global-business front, Alibaba Cloud's global cloud infrastructure supports XPeng's overseas business expansion, helping XPeng comprehensively improve overseas business deployment efficiency.
From full-stack AI collaboration to global business deployment, and now to the support of Qoder's product lineup for business innovation practices in this AI Open Competition, Alibaba Cloud and XPeng have joined hands comprehensively in the AI field, together opening up an innovation path for AI to move from R&D to the entire workforce, and from tools to productivity.
Business Staff Explore AI Application Innovation with Qoder
Among the most talked-about works at the finals, "Baize," the champion of Track Three "Efficiency Leap," stood out—it was built by a frontline employee from XPeng's supply chain, using Qoder as the creation tool. The author does not come from a traditional technical background but from the supply-chain front line, with a deeper understanding of real business scenarios.