京东工业携手上游企业发起首个工业大模型生态“百川计划”

This article covers the core announcement that JD Industrial launched the Baichuan Program, China’s first large model ecosystem for the industrial sector, on June 1. The initiative brings together upstream partners to co-build an ecosystem that solves common industry pain points, and its value has already been validated through real-world implementation. Key takeaways are as follows:

1. Industry pain points addressed: For a long time, the industrial upstream has struggled with scattered, disorganized, and siloed data. This has slowed the development of industry-specific large models, weakened collaborative value, and prevented AI from delivering on its promise to empower the industrial sector.

2. Core content of the Baichuan Program: JD Industrial is partnering with more than 100 upstream industry players to build an ecosystem along three dimensions: data, model development, and real-world applications. The program enables high-quality data circulation, unifies industry language frameworks, and delivers multi-scenario applications to drive cost reduction and efficiency improvement across the industry. It also provides partners with end-to-end support covering capability sharing, resource backing and business opportunity conversion.

3. Verified implementation outcomes: JD Industrial has already completed a pilot cooperation with Delixi Electric. The partnership boosted data collection efficiency by 3-4 times and shortened customers’ product selection decision time by approximately 70%. It has also produced replicable standard operating procedures (SOPs) for cooperation, proving that the model is viable and the overall strategic direction is sound.

This article outlines digital transformation directions, ecosystem cooperation opportunities and implementation value specifically for industrial brands. Key insights are as follows:

1. Industry trend: At the start of the 15th Five-Year Plan period, policies explicitly support AI plus manufacturing and integrated development of digitalization and industrialization. Intelligent transformation is a clear direction for the industry, and brands must evolve from AI users to co-builders of AI capabilities to capture development opportunities from new quality productivity.

2. Directions for product and operational upgrade: Brands can participate in co-building vertical industrial large models to convert their existing product and material data into standardized, structured formats. This not only improves data organization efficiency, but also enables large model applications in scenarios such as product selection and customer guidance, boosting operational efficiency, improving user experience, and driving GMV growth.

3. Ecosystem cooperation opportunities: Joining JD Industrial’s Baichuan Program gives brands access to JD Industrial’s large model capabilities, preferential access to customer resources, and end-to-end operational support. This helps brands improve their product information quality, reach users across multiple online and offline scenarios, convert tangible business opportunities, and build long-term AI competitiveness.

This article sorts out policy directions, new growth opportunities and actionable practical insights specifically for industrial sellers. Key takeaways are as follows:

1. Policy direction: At the opening of the 15th Five-Year Plan period, policies including AI plus manufacturing, digital supply chain upgrading and industrial data infrastructure building explicitly guide the intelligent transformation of the industrial sector. Digital upgrading is a clear area of policy dividend, and early布局 will deliver first-mover advantage.

2. New growth opportunities: JD Industrial has launched the Baichuan Program, China’s first large model ecosystem for the industrial sector, which is open to cooperation with 100+ upstream partners. After joining the program, sellers gain end-to-end support ranging from large model capability sharing, preferential customer resource allocation, to operational experience backing. This helps sellers improve the standardization of their product information, cut communication costs, reach users across multiple channels and scenarios, and effectively drive business opportunity conversion and growth.

3. Practical reference: The partnership between Delixi Electric and JD Industrial has already validated the feasibility of this model. The approach has produced mature cooperation SOPs and a data confidentiality framework, with no risks at the model level. This is a new growth opportunity well worth seizing by sellers, and its implementation experience can be directly referenced.

This article organizes digital transformation directions, business opportunities and implementation insights specifically for industrial production plants. Key takeaways are as follows:

1. Business opportunities: Policy-makers are now strongly promoting AI plus manufacturing, and market demand for industrial intelligent upgrading is booming, with cultivating new quality productivity set as a clear strategic direction. Plants can participate in large model ecosystem co-building to capture growth opportunities brought by industrial upgrading.

2. Insights for digital transformation: Most plants have accumulated large volumes of unstructured product data that was previously costly and inefficient to organize. By participating in large model ecosystem co-building, plants can leverage their partners’ technical capabilities to convert existing product manuals and material data into standardized, structured formats, boosting data collection efficiency by 3-4 times and greatly cutting data organization costs.

3. Implementation value: The co-built vertical large model can be directly applied to client-facing scenarios such as product selection and guidance. It can shorten decision-making time for customers selecting unfamiliar products by approximately 70%, effectively improving conversion efficiency and driving sales growth. It also helps plants build digital capabilities, standardize business processes, and comprehensively improve their digital operation level.

This article sorts out industry development trends, core customer pain points and reference solutions specifically for industrial service providers. Key takeaways are as follows:

1. Industry development trend: China’s industrial intelligent transformation is now accelerating, and vertical segmented industrial large models are an inevitable direction for industry development. With the official launch of China’s first industrial large model ecosystem, market demand for large model implementation services, data processing services and ecosystem building services is growing rapidly, opening up broad market space.

2. Core customer pain points: The core pain point for industrial customers today is the widespread existence of data silos across the industry. Data from different enterprises is scattered and disorganized, making it impossible to aggregate sufficient high-quality data for large model training. At the same time, non-standard product data, asymmetric supply and demand information, high communication costs, and high barriers to large model implementation all create substantial business opportunities for service providers.

3. Reference solution: JD Industrial’s Baichuan Program has already validated a viable three-dimensional co-construction model covering data, models and applications. It has produced standardized SOPs for data conversion, large model training and scenario implementation, as well as mature cooperation frameworks and data confidentiality mechanisms. Service providers can reference this model to deliver complete large model implementation services to clients based on the open ecosystem, reducing their own exploration costs.

This article sorts out merchant demands, reference operation methods and risk mitigation experience specifically for platform operators active in the industrial sector. Key takeaways are as follows:

1. Core merchant demands: The core demand of industrial merchants from platforms has shifted from basic traffic services to access to large model technology and data capabilities that help merchants complete digital upgrading, cut operating costs and expand business opportunities. No single platform can meet the needs of the entire industry relying on its own capabilities, so ecosystem co-construction is a viable approach to match current demand.

2. Reference best practices: The model behind JD Industrial’s Baichuan Program is worth learning from. JD Industrial open-sources its years-accumulated Mercator standardized product library and self-developed large model capabilities to partner with upstream players for ecosystem co-construction. It provides end-to-end support for partners from capability sharing, resource backing to business opportunity conversion, and validates value by rolling out large models for segmented product categories first before gradual expansion.

3. Risk mitigation experience: When building an industrial large model ecosystem, players should start with segmented vertical categories to validate value, rather than scaling blindly. They should also clarify cooperation frameworks and data confidentiality mechanisms in advance to avoid data security risks and cooperation disputes. During the merchant recruitment phase, platforms can attract participants with preferential customer resources and operational support to improve recruitment outcomes.

This article provides the latest industry developments, core industry problems and an innovative business model reference specifically for researchers in the AI+manufacturing and industrial digitalization fields. Key insights are as follows:

1. Latest industry development: The official launch of the Baichuan Program, China’s first large model ecosystem for the industrial sector, marks that China’s industrial large model development has entered a new stage of ecosystem co-construction from standalone technology exploration. The policy orientation of integrated digitalization-industrialization development and AI+manufacturing has now been put into real industrial practice, and industrial intelligent transformation has entered a new development phase.

2. Core new industry problem: The core bottleneck holding back current industrial large model development does not lie in large model technology itself. Instead, the characteristics of the industrial sector have led to scattered data and widespread data silos, with messy data that is difficult to coordinate. General-purpose large models cannot adapt to the complex scenarios of industry, and weak industry collaborative value has slowed the implementation progress of large models.

3. Reference innovative business model: The three-dimensional co-construction ecosystem model launched by JD Industrial represents a new exploration. JD Industrial partners with upstream players to co-build along three dimensions: data, models and applications, open-sources its own data and technical capabilities, and builds ecosystem collaboration through capability sharing and resource support. The model’s feasibility has already been validated by the Delixi Electric cooperation case, and it has produced replicable co-construction SOPs and cooperation frameworks, providing a new business model reference for the industry.