<p style="text-wrap-mode: wrap;"><strong style="font-size: 22px; color: rgb(62, 62, 62); text-align: justify;">Yonyou Releases LOM Ontology Large Model: Building a Deep-Thinking Digital Core for Enterprises</strong></p><p><section style="text-wrap-mode: wrap;"><section style="box-sizing: border-box; text-align: justify; color: rgb(62, 62, 62);"><p><br/></p><section style="text-align: center;"><img class="rich_pages wxw-img" src="https://mks.yybip.com/group1/M00/0C/05/CgoRC2m7boyAVW12AECae2fSn7E995.gif" style="vertical-align: inherit;"/> </section><p style="margin-top: 0px; margin-bottom: 0px; padding: 0px; box-sizing: border-box;"><br/></p><section style="max-width: 100%; box-sizing: border-box;"><section style="text-align: left; justify-content: flex-start; display: flex; flex-flow: row; margin-top: 10px; margin-bottom: -10px; box-sizing: border-box; max-width: 100%; transform: translate3d(13px, 0px, 0px);"><section style="display: inline-block; width: auto; vertical-align: top; align-self: flex-start; flex: 0 0 auto; min-width: 10%; max-width: 100%; height: auto; background-color: rgb(255, 255, 255); box-sizing: border-box;"><section style="max-width: 100%; box-sizing: border-box;"><section style="justify-content: flex-start; display: flex; flex-flow: row; margin-top: 10px; box-sizing: border-box; max-width: 100%;"><section style="display: inline-block; vertical-align: middle; width: 26px; align-self: center; flex: 0 0 auto; height: auto; max-width: 100%; box-sizing: border-box;"><section style="max-width: 100%; box-sizing: border-box;"><section style="box-sizing: border-box; max-width: 100%; transform: rotateZ(291deg);"><section style="max-width: 100%; box-sizing: border-box;"><section style="margin-top: 0.5em; margin-bottom: 0.5em; box-sizing: border-box; max-width: 100%;"><section style="background-color: rgb(0, 30, 48); height: 1px; box-sizing: border-box; max-width: 100%;"></section></section></section></section></section></section><section style="display: inline-block; vertical-align: middle; width: auto; align-self: center; flex: 0 0 auto; min-width: 10%; max-width: 100%; height: auto; box-sizing: border-box;"><section style="max-width: 100%; box-sizing: border-box;"><section style="text-align: center; color: rgb(230, 0, 18); box-sizing: border-box; max-width: 100%;"><p style="margin-top: 0px; margin-bottom: 0px; box-sizing: border-box; padding: 0px;"><em style="box-sizing: border-box;"><strong style="box-sizing: border-box;"><span style="text-decoration-thickness: auto; text-decoration-style: solid; text-decoration-color: #6E6E6E; box-sizing: border-box;">yonyou</span></strong></em></p></section></section></section><section style="display: inline-block; vertical-align: middle; width: 26px; align-self: center; flex: 0 0 auto; height: auto; max-width: 100%; box-sizing: border-box;"><section style="max-width: 100%; box-sizing: border-box;"><section style="box-sizing: border-box; max-width: 100%; transform: rotateZ(291deg);"><section style="max-width: 100%; box-sizing: border-box;"><section style="margin-top: 0.5em; margin-bottom: 0.5em; box-sizing: border-box; max-width: 100%;"><section style="background-color: rgb(0, 30, 48); height: 1px; box-sizing: border-box; max-width: 100%;"></section></section></section></section></section></section></section></section></section></section></section><section style="max-width: 100%; box-sizing: border-box;"><section style="text-align: left; justify-content: flex-start; display: flex; flex-flow: row; margin-bottom: 10px; box-sizing: border-box; max-width: 100%;"><section style="display: inline-block; width: 675.116px; vertical-align: top; align-self: flex-start; flex: 0 0 auto; border-style: solid; border-width: 1px; border-color: rgb(25, 15, 73); padding-right: 15px; padding-bottom: 15px; padding-left: 15px; max-width: 100%; box-sizing: border-box;"><section style="max-width: 100%; box-sizing: border-box;"><section style="text-align: justify; box-sizing: border-box; max-width: 100%;"><section style="max-width: 100%; box-sizing: border-box;"><section style="box-sizing: border-box; max-width: 100%;"><p style="margin-top: 0px; margin-bottom: 0px; padding: 0px; box-sizing: border-box;"><br/></p></section></section></section></section><section style="max-width: 100%; box-sizing: border-box;"><section style="text-align: justify; box-sizing: border-box; max-width: 100%; line-height: 1.75; letter-spacing: 1px; color: rgb(0, 0, 0);"><p style="margin-top: 0px; padding: 0px; box-sizing: border-box;">In an era where enterprise digital intelligence upgrades are moving towards greater depth and precision, the ability to efficiently manage and utilize massive amounts of data has become a key factor in determining competitiveness. Facing the complexity of integrating multi-source heterogeneous data and the high demands for decision-making accuracy in complex business scenarios, Yonyou released the <strong><strong>LOM</strong></strong> on February 24th. This model aims to create a "Digital Brain" for enterprises capable of deeply understanding their own business and performing complex logical reasoning.</p></section></section></section></section></section><section style="text-align: center;"><img class="rich_pages wxw-img" src="https://mks.yybip.com/group1/M00/04/55/CgoRDGm7bSiAWzvwAAR2BlOA5Xo635.png"/> </section><p style="margin-top: 0px; margin-bottom: 0px; padding: 0px; box-sizing: border-box;"><br/></p><p style="margin-top: 0px; margin-bottom: 0px; padding: 0px; box-sizing: border-box;"><br/></p><section style="max-width: 100%; box-sizing: border-box;"><section style="text-align: center; justify-content: center; display: flex; flex-flow: row; box-sizing: border-box; max-width: 100%;"><section style="display: inline-block; width: auto; vertical-align: top; align-self: flex-start; flex: 0 0 auto; min-width: 10%; max-width: 100%; height: auto; box-sizing: border-box;"><section style="max-width: 100%; box-sizing: border-box;"><section style="justify-content: center; display: flex; flex-flow: row; font-size: 19px; margin-top: 10px; margin-bottom: 3px; box-sizing: border-box; max-width: 100%;"><section style="display: inline-block; width: 1.8em; vertical-align: top; align-self: flex-start; flex: 0 1 auto; border-width: 1px; border-style: solid; border-color: rgb(230, 0, 18); background-color: rgb(230, 0, 18); height: 1.8em; line-height: 1.8em; border-radius: 100%; margin-left: auto; margin-right: auto; font-size: 16px; color: rgb(255, 255, 255); max-width: 100%; box-sizing: border-box;"><section style="box-sizing: border-box; max-width: 100%;"><p style="margin-top: 0px; margin-bottom: 0px; padding: 0px; box-sizing: border-box;"><strong style="box-sizing: border-box;">01</strong></p></section></section></section></section><section style="max-width: 100%; box-sizing: border-box;"><section style="justify-content: center; display: flex; flex-flow: row; box-sizing: border-box; max-width: 100%;"><section style="display: inline-block; width: 0px; vertical-align: top; align-self: flex-start; flex: 0 1 auto; height: 0px; overflow: hidden; border-style: solid; border-width: 9px 6px 0px; border-color: rgb(230, 0, 18) rgba(255, 255, 255, 0) rgba(255, 255, 255, 0); max-width: 100%; box-sizing: border-box;"></section></section></section></section></section></section><section style="max-width: 100%; box-sizing: border-box;"><section style="text-align: center; box-sizing: border-box; max-width: 100%; color: rgb(240, 11, 11); font-size: 18px;"><p style="margin-top: 0px; margin-bottom: 0px; padding: 0px; box-sizing: border-box;"><br/></p><p style="margin-top: 0px; margin-bottom: 0px; padding: 0px;"><strong><span style="color: #FF0000;"><strong>Technological Innovation: LOM Ontology Large Model Constructs a New Foundation for Enterprise Intelligence</strong></span></strong></p></section></section><p style="margin-top: 0px; margin-bottom: 0px; padding: 0px; box-sizing: border-box;"><br/></p><section style="color: rgb(0, 0, 0); line-height: 1.75; letter-spacing: 1px; box-sizing: border-box;"><p style="margin-top: 0px; padding: 0px; box-sizing: border-box;">The LOM Ontology Large Model uses the Yonyou BIP Enterprise AI Ontology Agent as its underlying logic. It completes a paradigm shift from traditional two-dimensional "tabular" data management to a <strong><strong>"graph-centered"</strong></strong> approach. By defining entities in enterprise operations as nodes and relationships as edges, it transforms scattered enterprise data into "living connections" that are computable and reason-capable, upgrading enterprise knowledge from static storage to dynamic, interactive intelligent assets.</p></section><section style="text-align: center; margin-top: 10px; margin-bottom: 10px; line-height: 0; box-sizing: border-box;"><section style="max-width: 100%; vertical-align: middle; display: inline-block; line-height: 0; box-sizing: border-box;"><img class="rich_pages wxw-img" src="https://mks.yybip.com/group1/M00/0C/05/CgoRC2m7bo2AcVQAAAH4RIwwTSo132.png" width="100%" style="vertical-align: middle; width: 630.324px; box-sizing: border-box;"/> </section></section><section style="color: rgb(0, 0, 0); line-height: 1.75; letter-spacing: 1px; box-sizing: border-box;"><p style="margin-top: 0px; margin-bottom: 0px; padding: 0px; box-sizing: border-box;"><br/></p><p style="margin-top: 0px; padding: 0px; box-sizing: border-box;">With its full-link capability of "Construction - Alignment - Reasoning," the LOM model connects business systems with data and ontology applications, achieving life-cycle management of enterprise knowledge from mining and integration to value output. In the Construction Stage:<span style="caret-color: red;"> LOM enables the automatic construction of multi-source ontologies, breaking down barriers between structured and unstructured data, explicit and implicit knowledge, and real-time and historical data. Through its knowledge mining and construction engine, it performs entity extraction, relationship establishment, knowledge deposition, and reasoning completion to create an enterprise-wide data system. </span>In the Alignment Stage:<span style="caret-color: red;"> Using the BIP standard ontology as the core anchor to build the model’s skeletal nodes, it employs efficient dynamic alignment capabilities to ensure that continuous data flows remain semantically consistent and deeply integrated with the ontology structure. </span>In complex Logical Reasoning:<span style="caret-color: red;"> The LOM model can perform multi-step complex logic deductions. In professional evaluations involving 19 types of graph reasoning tasks, the </span>LOM-4B model ranked first with an overall accuracy of 89.47%<span style="caret-color: red;">, achieving 100% accuracy in several core tasks, fully validating the effectiveness and sophistication of the technology.</span></p></section><p style="margin-top: 0px; margin-bottom: 0px; padding: 0px; box-sizing: border-box;"><br/></p><section style="max-width: 100%; box-sizing: border-box;"><section style="text-align: center; justify-content: center; display: flex; flex-flow: row; box-sizing: border-box; max-width: 100%;"><section style="display: inline-block; width: auto; vertical-align: top; align-self: flex-start; flex: 0 0 auto; min-width: 10%; max-width: 100%; height: auto; box-sizing: border-box;"><section style="max-width: 100%; box-sizing: border-box;"><section style="justify-content: center; display: flex; flex-flow: row; font-size: 19px; margin-top: 10px; margin-bottom: 3px; box-sizing: border-box; max-width: 100%;"><section style="display: inline-block; width: 1.8em; vertical-align: top; align-self: flex-start; flex: 0 1 auto; border-width: 1px; border-style: solid; border-color: rgb(230, 0, 18); background-color: rgb(230, 0, 18); height: 1.8em; line-height: 1.8em; border-radius: 100%; margin-left: auto; margin-right: auto; font-size: 16px; color: rgb(255, 255, 255); max-width: 100%; box-sizing: border-box;"><section style="box-sizing: border-box; max-width: 100%;"><p style="margin-top: 0px; margin-bottom: 0px; padding: 0px; box-sizing: border-box;"><strong style="box-sizing: border-box;">02</strong></p></section></section></section></section><section style="max-width: 100%; box-sizing: border-box;"><section style="justify-content: center; display: flex; flex-flow: row; box-sizing: border-box; max-width: 100%;"><section style="display: inline-block; width: 0px; vertical-align: top; align-self: flex-start; flex: 0 1 auto; height: 0px; overflow: hidden; border-style: solid; border-width: 9px 6px 0px; border-color: rgb(230, 0, 18) rgba(255, 255, 255, 0) rgba(255, 255, 255, 0); max-width: 100%; box-sizing: border-box;"></section></section></section></section></section></section><section style="max-width: 100%; box-sizing: border-box;"><section style="text-align: center; box-sizing: border-box; max-width: 100%; color: rgb(240, 11, 11); font-size: 18px;"><p style="margin-top: 0px; margin-bottom: 0px; padding: 0px; box-sizing: border-box;"><br/></p><p style="margin-top: 0px; margin-bottom: 0px; padding: 0px;"><strong><span style="color: #FF0000;"><strong>Scenario Implementation: LOM Model Empowers Agile and Lean Management Across All Dimensions</strong></span></strong></p></section></section><p style="margin-top: 0px; margin-bottom: 0px; padding: 0px; box-sizing: border-box;"><br/></p><section style="line-height: 1.75; letter-spacing: 1px; color: rgb(0, 0, 0); box-sizing: border-box;"><p style="margin-top: 0px; padding: 0px; box-sizing: border-box;"><span style="text-align: left;">The value of technology eventually lands in enterprise scenarios. With its powerful reasoning capabilities, the LOM model is deeply adapted to core business scenarios such as procurement, production, sales, and finance, transforming reasoning power into actual business efficacy.</span></p></section><section style="line-height: 1.75; letter-spacing: 1px; color: rgb(0, 0, 0); box-sizing: border-box;"><section style="text-align: center;"><img class="rich_pages wxw-img" src="https://mks.yybip.com/group1/M00/04/55/CgoRDGm7bSmAXzVxAAdPIQMKNV0976.png"/> </section><p style="margin-top: 0px; margin-bottom: 0px; padding: 0px; box-sizing: border-box;"><br/></p><p style="margin-top: 0px; padding: 0px; box-sizing: border-box;"><span style="text-align: left;">The following four typical fields illustrate how the LOM model empowers intelligent decision-making and complex system analysis.</span></p></section><section style="margin: 10px 0px; text-align: left; justify-content: flex-start; display: flex; flex-flow: row; width: 675.116px; letter-spacing: 1px; border-left: 5px solid rgb(235, 33, 33); border-bottom-left-radius: 0px; padding: 0px 0px 0px 10px; height: auto; align-self: flex-start; box-sizing: border-box; max-width: 100%;"><section style="width: 660.683px; box-sizing: border-box; transform: translate3d(2px, 0px, 0px); max-width: 100%;"><section style="font-size: 17px; line-height: 1.8; color: rgb(235, 33, 33); width: 660.683px; box-sizing: border-box; max-width: 100%;"><p style="margin-top: 0px; margin-bottom: 0px; padding: 0px; box-sizing: border-box;"><strong><span style="color: #FF0000;"><strong>In the field of Procurement, helping to build a more resilient supply chain.</strong></span></strong></p></section></section></section><section style="line-height: 1.75; letter-spacing: 1px; color: rgb(0, 0, 0); box-sizing: border-box;"><p style="margin-top: 0px; padding: 0px; box-sizing: border-box;"><br/></p><p style="margin-top: 0px; padding: 0px; box-sizing: border-box;"><span style="text-align: left;">When a core supplier faces a shutdown risk, the LOM model can quickly identify that supplier's position in the supply chain network and scan level-2 and level-3 suppliers that may be affected to issue early warnings. Before a purchase order is placed, the system automatically verifies whether pre-conditions—such as supplier qualifications, quality inspection records, and budget indicators—are complete, avoiding compliance risks caused by missing information. For critical materials, it identifies "keystone" strategic suppliers to help enterprises establish backup plans in advance.</span></p><section style="text-align: center;"><img class="rich_pages wxw-img" src="https://mks.yybip.com/group1/M00/0C/05/CgoRC2m7bo2AWnr-AAYqvkzkqiI905.png"/> </section></section><section style="line-height: 1.75; letter-spacing: 1px; color: rgb(0, 0, 0); box-sizing: border-box;"><p style="margin-top: 0px; margin-bottom: 0px; padding: 0px; box-sizing: border-box;"><br/></p></section><section style="margin: 10px 0px; text-align: left; justify-content: flex-start; display: flex; flex-flow: row; width: 675.116px; letter-spacing: 1px; border-left: 5px solid rgb(235, 33, 33); border-bottom-left-radius: 0px; padding: 0px 0px 0px 10px; height: auto; align-self: flex-start; box-sizing: border-box; max-width: 100%;"><section style="width: 660.683px; box-sizing: border-box; transform: translate3d(2px, 0px, 0px); max-width: 100%;"><section style="font-size: 17px; line-height: 1.8; color: rgb(235, 33, 33); width: 660.683px; box-sizing: border-box; max-width: 100%;"><p style="margin-top: 0px; margin-bottom: 0px; padding: 0px; box-sizing: border-box;"><strong><span style="color: #FF0000;"><strong>In the field of Manufacturing, achieving full-process traceability and dynamic optimization.</strong></span></strong></p></section></section></section><section style="line-height: 1.75; letter-spacing: 1px; color: rgb(0, 0, 0); box-sizing: border-box;"><p style="margin-top: 0px; margin-bottom: 0px; padding: 0px; box-sizing: border-box;"><br/></p><p style="margin-top: 0px; padding: 0px; box-sizing: border-box;"><span style="text-align: left;">When product quality defects occur, the LOM model can trace back from the finished product to specific raw material batches along the Bill of Materials (BOM) to precisely locate the failure point. In smart factories, it plans optimal paths for automated handling equipment to reduce ineffective material movement. By monitoring task backlogs at each station in real-time, it identifies bottlenecks, helping managers dynamically allocate resources to balance production flow.</span></p></section><section style="line-height: 1.75; letter-spacing: 1px; color: rgb(0, 0, 0); box-sizing: border-box;"><section style="text-align: center;"><img class="rich_pages wxw-img" src="https://mks.yybip.com/group1/M00/04/55/CgoRDGm7bSmAT6MEAAbhTGb-0kI118.png"/> </section></section><section style="margin: 10px 0px; text-align: left; justify-content: flex-start; display: flex; flex-flow: row; width: 675.116px; letter-spacing: 1px; border-left: 5px solid rgb(235, 33, 33); border-bottom-left-radius: 0px; padding: 0px 0px 0px 10px; height: auto; align-self: flex-start; box-sizing: border-box; max-width: 100%;"><section style="width: 660.683px; box-sizing: border-box; transform: translate3d(2px, 0px, 0px); max-width: 100%;"><section style="font-size: 17px; line-height: 1.8; color: rgb(235, 33, 33); width: 660.683px; box-sizing: border-box; max-width: 100%;"><p style="margin-top: 0px; margin-bottom: 0px; padding: 0px; box-sizing: border-box;"><strong><span style="background: #FFFFFF;"><strong>In the field of Sales and Marketing, supporting precise customer insights and resource allocation.</strong></span></strong></p></section></section></section><section style="line-height: 1.75; letter-spacing: 1px; color: rgb(0, 0, 0); box-sizing: border-box;"><p style="margin-top: 0px; margin-bottom: 0px; padding: 0px; box-sizing: border-box;"><br/></p><p style="margin-top: 0px; padding: 0px; box-sizing: border-box;"><span style="text-align: left;">Based on historical interaction records and social relationship networks, the LOM model identifies high-influence customers, helping enterprises focus limited sales resources on the most valuable nodes. In private domain traffic operations, it can quickly cover potential customer circles directly related to existing clients, reducing acquisition costs. For high-value customers, it constructs full-journey behavior funnels to mine hidden causes of churn and support targeted retention strategies.</span></p></section><section style="line-height: 1.75; letter-spacing: 1px; color: rgb(0, 0, 0); box-sizing: border-box;"><section style="text-align: center;"><img class="rich_pages wxw-img" src="https://mks.yybip.com/group1/M00/0C/05/CgoRC2m7bo2ATzcdAAd0Wgpz16o660.png"/> </section></section><section style="margin: 10px 0px; text-align: left; justify-content: flex-start; display: flex; flex-flow: row; width: 675.116px; letter-spacing: 1px; border-left: 5px solid rgb(235, 33, 33); border-bottom-left-radius: 0px; padding: 0px 0px 0px 10px; height: auto; align-self: flex-start; box-sizing: border-box; max-width: 100%;"><section style="width: 660.683px; box-sizing: border-box; transform: translate3d(2px, 0px, 0px); max-width: 100%;"><section style="font-size: 17px; line-height: 1.8; color: rgb(235, 33, 33); width: 660.683px; box-sizing: border-box; max-width: 100%;"><p style="margin-top: 0px; margin-bottom: 0px; padding: 0px; box-sizing: border-box;"><strong><span style="background: #FFFFFF;"><strong>In the field of Finance and Risk Control, achieving "look-through" supervision and automated compliance verification.</strong></span></strong></p></section></section></section><section style="line-height: 1.75; letter-spacing: 1px; color: rgb(0, 0, 0); box-sizing: border-box;"><p style="margin-top: 0px; margin-bottom: 0px; padding: 0px; box-sizing: border-box;"><br/></p><p style="margin-top: 0px; padding: 0px; box-sizing: border-box;"><span style="text-align: left;">At the moment of fund disbursement, the LOM model can identify the direct transaction associates of the receiving account; if a high-risk entity exists among the connected nodes, the system can automatically trigger an interception. For complex corporate equity structures, it can penetrate multiple layers of shareholding to reach the ultimate actual controller, providing a clear risk view for M&A and investment decisions. In "three-way matching," starting from a payment request, it identifies all precursor documents—including purchase contracts, receiving notes, and invoices—achieving high transparency in financial settlement through automated comparison.</span></p></section><section style="line-height: 1.75; letter-spacing: 1px; color: rgb(0, 0, 0); box-sizing: border-box;"><section style="text-align: center;"><img class="rich_pages wxw-img" src="https://mks.yybip.com/group1/M00/04/55/CgoRDGm7bSmAUk5QAAbhSC2nX9A764.png"/> </section><p style="margin-top: 0px; padding: 0px; box-sizing: border-box;"><span style="text-align: left;">From technical architecture to scenario landing, the LOM Ontology Large Model consistently stands on actual enterprise needs. It achieves a breakthrough in enterprise-level complex reasoning with a lightweight and efficient design, significantly lowering the threshold and cost of deploying enterprise AI. Furthermore, it builds a bridge between structured data and unstructured knowledge, creating a self-growing and self-optimizing intelligent system.</span></p><p style="margin-top: 0px; margin-bottom: 0px; padding: 0px; box-sizing: border-box;"><br/></p></section><section style="margin: 0px; text-align: left; justify-content: flex-start; display: flex; flex-flow: row; width: 675.116px; border: 1px solid rgb(218, 11, 11); background-color: rgba(218, 11, 11, 0.05); align-self: flex-start; box-sizing: border-box; max-width: 100%;"><section style="margin: 15px 0px 20px; width: 673.634px; box-sizing: border-box; max-width: 100%;"><section style="color: rgb(0, 0, 0); padding: 0px 10px; line-height: 1.75; letter-spacing: 1px; text-align: justify; width: 673.634px; box-sizing: border-box; max-width: 100%;"><p style="margin-top: 0px; padding: 0px; box-sizing: border-box;"><span style="text-align: left;">In the future, Yonyou LOM will continue to deepen technological innovation, upgrade reinforcement learning strategies, and build public evaluation benchmarks to tackle more extreme reasoning tasks. This will continuously improve the model's reasoning capabilities in complex enterprise scenarios, ensuring every enterprise has a "brain" capable of deep thinking!</span></p></section></section></section></section></section></p><p><br/></p>
Consulting on digital transformation products or solutions
