The same component has different codes in different systems. No matter how powerful the large model is, it cannot understand the enterprise-specific data caliber: Digital Governance Cloud uses "ontology" to build the business semantic foundation for industrial data.
Implementation of Industrial AI is Bottlenecked at the "Business Semantics" Layer
In the digitalization project of a large energy group, ERP, MES, supply chain and financial systems have operated independently for many years, with data of orders, materials and equipment all stored in respective systems. However, the same component often has different codes in different systems, and cross-system caliber verification relies on repeated manual comparison. This is a scenario repeatedly encountered by Shuzhiyun (Beijing) Technology Co., Ltd. when providing data governance consulting services in the energy, nuclear power, electric power, communications and other industries.
The problem does not lie in the insufficient data volume, but in the "language barrier". Equipment data, process data and material data belong to different systems, and there has been a lack of a unified business semantic layer for a long time. After the large model is connected, it can neither understand the enterprise's own business calibers, nor can it be safely applied for reasoning and decision-making.
At the policy level, this gap is being further highlighted. In April 2026, the General Office of the Ministry of Industry and Information Technology and the Comprehensive Department of the National Data Administration jointly issued a notice on the "Modulus Resonance" action, targeting 20 key manufacturing industries including steel, petrochemical and chemical, automobile, aerospace, to promote the mutual coordination and promotion of artificial intelligence models and data resources. The Implementation Opinions on the Special Action of "AI + Manufacturing" issued by 8 departments including the Ministry of Industry and Information Technology proposes to launch 1000 high-level industrial agents by 2027. Whether the data base can be understood by the model has become a prerequisite for the large-scale application of industrial AI.
Building a "Semantic Base" for Industrial Data with Ontology
The solution proposed by Shuzhiyun is Ontology. According to the company's official website, its business covers strategic planning for digital transformation, data governance system planning consulting, as well as data governance platforms, data asset management software, industry data intelligent application solutions and industrial internet data interconnection solutions, and provides related system implementation, consulting, training and certification services. The platform side includes modules such as metadata management, master data platform, data indicator management, data quality management and data security management.
The technical accumulation is reflected in its patents. In 2026, two invention patents of the company were published successively, one is "An Ontology-based Business Semantic Modeling Method and System" (July 2026), and the other is "A Method and Application for AI Training and Reasoning of Material Business Data" (May 2026). The former abstracts business concepts, attributes and relationships into a structured semantic model, enabling data to complete a "business translation" before entering the model; the latter points to the AI training and reasoning method for master data such as materials. According to data from Tianyancha, the company has a total of 4 patent records and 21 copyright records.
In terms of industry-university-research cooperation, the Shuzhiyun team cooperated with researchers from the National Industrial Information Security Development Research Center directly under the Ministry of Industry and Information Technology, and published Research on the Construction Method of AI Dataset for Small and Medium-sized Enterprises Driven by Lightweight Ontology, discussing how to reduce the threshold for small and medium-sized enterprises to build AI datasets with lightweight ontology.
A Team with 20 Years of Deep Cultivation in the Energy Industry
Shuzhiyun was established in March 2022, with a registered capital of 4 million yuan, and its legal representative Cheng Huajun is the actual controller. In the equity structure, Beijing Shuzhiyun Chuang Technology Development Center (Limited Partnership), the employee stock ownership platform, holds 50% of the shares, Cheng Huajun holds 30%, Cai Chunjiu holds 15%, and Liu Wenping holds 5%.
According to the company's official website, the founding team comes from enterprises including Tencent, IBM, Microsoft, HP and Yonyou, with an average of more than 15 years of experience in the energy industry engaged in information strategy consulting, data governance, digital transformation consulting, software development, system integration and other businesses, and the core backbones have more than 20 years of relevant experience. Cai Chunjiu, the shareholder and co-founder, has more than 20 years of experience in IT consulting and data governance, has provided data governance services for enterprises such as Sinopec, China Southern Power Grid, State Power Investment Corporation, China National Nuclear Corporation, and is also one of the editors of Data Governance: The Path to Digital Transformation of Industrial Enterprises.
In terms of qualifications, in January 2025, the 4th batch of high-tech enterprise filing announcements reported by the Beijing municipal certification authority in 2024 disclosed that Shuzhiyun was on the list, with the certificate number GR202411006200; the company is also a provincial-level innovative small and medium-sized enterprise in 2025.
From Project Delivery to Platform Replication
Public bidding information shows that Shuzhiyun has participated in 35 bidding projects, including the top-level planning for digital transformation of CGN Group's nuclear energy industry, top-level planning consulting services for Taishan Nuclear Power's digital transformation, information project consulting and technical services for CNOOC, construction of the "three lists" of data assets for Wuling Power, big data system planning consulting for CICT, and material data governance for Henan Huirong. In June 2026, the company won the bid for the municipal-level master data implementation service procurement project of Henan Huirong Digital Technology Co., Ltd.
Industrial and commercial information shows that the company has invested in 7 enterprises externally, and has holding subsidiaries in Chongqing, Nanjing, Shenzhen, Wuhan and other places, of which the shareholding ratio for Shuzhiyun (Nanjing) and Shuzhiyun (Shenzhen) is 90%, and the shareholding ratio for Shuzhiyun (Chongqing) is 80%. In March 2026, as one of the organizers, the company participated in the high-quality development series salons of Hefei's data industry themed "Data as Foundation, Emergence of Intelligence" hosted by Hefei Data Industry Association and other institutions.
Shuzhiyun is seeking a new round of financing. For this company, the real test lies in precipitating the project-based delivery that used to rely on expert experience into replicable ontology models and platform capabilities — this is not only the direct extension of the team's 20-year accumulation in the energy industry, but also a necessary step for industrial AI to evolve from "being able to answer" to "being able to execute".