{"id":49707,"date":"2026-03-02T08:08:00","date_gmt":"2026-03-02T01:08:00","guid":{"rendered":"https:\/\/thaipropertynews.com\/feeds\/?p=49707"},"modified":"2026-03-02T08:08:00","modified_gmt":"2026-03-02T01:08:00","slug":"yonyou-unveils-the-large-ontology-model-lom-forging-a-deep-thinking-digital-core-for-the-enterprise","status":"publish","type":"post","link":"https:\/\/thaipropertynews.com\/feeds\/?p=49707","title":{"rendered":"Yonyou Unveils the Large Ontology Model (LOM): Forging a Deep-Thinking Digital Core for the Enterprise"},"content":{"rendered":"

BEIJING<\/span>, March 2, 2026 \/PRNewswire\/ — As enterprise digital transformation advances with increasing depth and precision, the ability to efficiently manage and harness massive\u00a0datasets has become the core competitive barrier. Facing the significant challenges of integrating multi-source heterogeneous data and the intense demand for high-fidelity decision-making in complex business scenarios, Yonyou officially released the Large Ontology Model (LOM) on February 24th<\/span>. This release provides enterprises with a true “digital brain” capable of deeply understanding their operations and executing complex logical reasoning.<\/span><\/p>\n

I. Technological Breakthrough: LOM as the New Foundation for Enterprise Intelligence<\/b><\/p>\n

Grounded in the Yonyou BIP Enterprise AI Ontology Agent, the LOM represents a fundamental paradigm shift from conventional two-dimensional tabular models to knowledge graph-based architectures. B<\/span>y using nodes and edges to capture entities and their relationships, LOM transforms siloed enterprise data into computable, reason-capable “live connections.” It upgrades enterprise knowledge from static storage into dynamic, e<\/span>xecutable intelligent assets.<\/p>\n

Leveraging a unified construct-align-reason framework,<\/span>\u00a0LOM seamlessly connects bottom-layer business systems and data with top-layer ontology applications. It enables the full-lifecycle management of enterprise knowledge, from raw extraction to high-value output. During the construction phase, LOM automates multi-source ontology construction,<\/span> bridging the barriers between structured databases and unstructured text, explicit and implicit knowledge, and dynamic real-time versus static historical data. Driven by a robust knowledge construction engine, it performs entity-relation extraction, link prediction, knowledge distillation, and reasoning completion, culminating in a comprehensive enterprise-scale data architecture. Simultaneously, using the\u00a0BIP standard ontology as the core anchor, it builds the skeletal structure of the model’s nodes. Then, through highly efficient dynamic text-ontology alignment, it ensures continuous data streams remain semantically consistent and deeply fused with the ontology structure.<\/p>\n

When it comes to complex logical reasoning, the LOM is exceptionally capable. It executes reliable, multi-hop reasoning over heterogeneous enterprise data. In rigorous benchmark testing covering 19 diverse graph reasoning tasks,<\/span> our 4B<\/span>-parameter\u00a0LOM achieved state-of-the-art performance, taking the top rank with an overall accuracy of 89.47%,<\/span> while hitting near-perfect accuracy (100%) on several core tasks. This unequivocally validates the cutting-edge effectiveness of our architecture.<\/p>\n

II. Real-World Impact: LOM Supercharges Agile and Lean Enterprise Management Across All Dimensions<\/b><\/p>\n

The ultimate test of any technology is its real-world application. Armed with formidable reasoning capabilities, LOM is deeply optimized for core enterprise workflows\u2014procurement, production, sales, and finance. It translates raw computational power into tangible business momentum, delivering full-stack empowerment from intelligent decision-making to complex system analysis.<\/p>\n

Here is how the Large Ontology Model empowers intelligent decision-making and complex system analysis across these four critical domains:<\/p>\n

Procurement: Engineering an Antifragile Supply Chain<\/b><\/p>\n

When a core supplier faces disruption, the LOM doesn’t just see a localized failure; it instantly pinpoints that node within the global graph, executing a deep traversal across Tier-2 and Tier-3 dependencies to broadcast predictive early warnings. Before a purchase order is even issued, the system autonomously validates prerequisites\u2014credentials, QA logs, budget constraints\u2014eliminating compliance risks caused by missing information. For mission-critical materials, the LOM runs centrality and topology analysis to identify strategic bottleneck suppliers\u2014those “single points of failure”\u2014allowing enterprises to engineer redundancy and backup plans ahead of time.<\/p>\n

Production: Full-Stack Traceability and Dynamic Optimization<\/b><\/p>\n

When a product defect occurs, the LOM performs predecessor node searches along the Bill of Materials (BOM), reverse-tracing from the finished product back to the exact raw material batch to precisely locate the point of failure. In the smart factory, it acts as a routing engine, computing the shortest path for automated material handling equipment, significantly reducing dead time between operations. By monitoring task backlogs across workstations in real-time, it identifies throughput bottlenecks, enabling managers to dynamically allocate resources and smooth out the production flow.<\/p>\n

Sales & Marketing: High-Precision Customer Insight and Resource Allocation<\/b><\/p>\n

Leveraging historical interaction logs and social relation graphs, the LOM runs PageRank-style centrality algorithms to identify high-influence customer nodes, focusing your finite sales bandwidth where it generates the highest ROI. In owned <\/span>channel ecosystems operations, it uses common neighbor analysis starting from existing users to rapidly map and capture directly connected prospect clusters, fundamentally driving down customer acquisition costs. For high-value accounts, it constructs a full-journey behavioral funnel, uncovering the hidden relational patterns behind churn to power highly targeted retention strategies.<\/p>\n

Finance & Risk Management: Penetrative Oversight and Autonomous Compliance<\/b><\/p>\n

The moment funds are deployed, the LOM identifies direct transactional counterparties of the receiving account. If the connected component contains high-risk entities, it triggers an autonomous hard stop. For labyrinthine corporate equity structures, the LOM penetrates multi-hop ownership layers to expose the ultimate beneficial owner, delivering a crystal-clear risk topology for M&A and investment decisions. In three-way matching, it starts at the payment request and traverses upward to validate all predecessor documents \u2014POs, receipts, invoices\u2014ensuring complete transparency in financial settlements through automated alignment.<\/p>\n

From bare-metal architecture to real-world deployment, the LOM is rigorously grounded in actual enterprise needs. Its highly efficient, lightweight 4B<\/span>-parameter model design cracks the code on complex enterprise-level reasoning, massively lowering the barrier and cost of deploying enterprise AI. More than that, it builds the definitive bridge between structured databases and unstructured textual knowledge, creating a continuously evolving intelligence framework where enterprise data assets self-generate and self-optimize.<\/p>\n

Looking ahead,\u00a0Yonyou’s LOM will relentlessly push the technical frontier. We will upgrade our reinforcement learning strategies,<\/span> build open evaluation benchmarks, and tackle complex challenges. We are scaling\u00a0LOM’s inference capabilities in complex enterprise environments so that every<\/i> company is equipped with a deep-thinking “brain.”<\/p>\n

https:\/\/chinaxiv.org\/abs\/202601.00187<\/a>\u00a0<\/p>\n

\u00a0<\/p>","protected":false},"excerpt":{"rendered":"

<\/p>\n

BEIJING<\/span>, March 2, 2026 \/PRNewswire\/ — As enterprise digital transformation advances with increasing depth and precision, the ability to efficiently manage and harness massive\u00a0datasets has become the core competitive barrier. Facing the significant challenges of integrating multi-source heterogeneous data and the intense demand for high-fidelity decision-making in complex business scenarios, Yonyou officially released the Large Ontology Model (LOM) on February 24th<\/span>. This release provides enterprises with a true “digital brain” capable of deeply understanding their operations and executing complex logical reasoning.<\/span><\/p>\n

I. Technological Breakthrough: LOM as the New Foundation for Enterprise Intelligence<\/b><\/p>\n

Grounded in the Yonyou BIP Enterprise AI Ontology Agent, the LOM represents a fundamental paradigm shift from conventional two-dimensional tabular models to knowledge graph-based architectures. B<\/span>y using nodes and edges to capture entities and their relationships, LOM transforms siloed enterprise data into computable, reason-capable “live connections.” It upgrades enterprise knowledge from static storage into dynamic, e<\/span>xecutable intelligent assets.<\/p>\n

Leveraging a unified construct-align-reason framework,<\/span>\u00a0LOM seamlessly connects bottom-layer business systems and data with top-layer ontology applications. It enables the full-lifecycle management of enterprise knowledge, from raw extraction to high-value output. During the construction phase, LOM automates multi-source ontology construction,<\/span> bridging the barriers between structured databases and unstructured text, explicit and implicit knowledge, and dynamic real-time versus static historical data. Driven by a robust knowledge construction engine, it performs entity-relation extraction, link prediction, knowledge distillation, and reasoning completion, culminating in a comprehensive enterprise-scale data architecture. Simultaneously, using the\u00a0BIP standard ontology as the core anchor, it builds the skeletal structure of the model’s nodes. Then, through highly efficient dynamic text-ontology alignment, it ensures continuous data streams remain semantically consistent and deeply fused with the ontology structure.<\/p>\n

When it comes to complex logical reasoning, the LOM is exceptionally capable. It executes reliable, multi-hop reasoning over heterogeneous enterprise data. In rigorous benchmark testing covering 19 diverse graph reasoning tasks,<\/span> our 4B<\/span>-parameter\u00a0LOM achieved state-of-the-art performance, taking the top rank with an overall accuracy of 89.47%,<\/span> while hitting near-perfect accuracy (100%) on several core tasks. This unequivocally validates the cutting-edge effectiveness of our architecture.<\/p>\n

II. Real-World Impact: LOM Supercharges Agile and Lean Enterprise Management Across All Dimensions<\/b><\/p>\n

The ultimate test of any technology is its real-world application. Armed with formidable reasoning capabilities, LOM is deeply optimized for core enterprise workflows\u2014procurement, production, sales, and finance. It translates raw computational power into tangible business momentum, delivering full-stack empowerment from intelligent decision-making to complex system analysis.<\/p>\n

Here is how the Large Ontology Model empowers intelligent decision-making and complex system analysis across these four critical domains:<\/p>\n

Procurement: Engineering an Antifragile Supply Chain<\/b><\/p>\n

When a core supplier faces disruption, the LOM doesn’t just see a localized failure; it instantly pinpoints that node within the global graph, executing a deep traversal across Tier-2 and Tier-3 dependencies to broadcast predictive early warnings. Before a purchase order is even issued, the system autonomously validates prerequisites\u2014credentials, QA logs, budget constraints\u2014eliminating compliance risks caused by missing information. For mission-critical materials, the LOM runs centrality and topology analysis to identify strategic bottleneck suppliers\u2014those “single points of failure”\u2014allowing enterprises to engineer redundancy and backup plans ahead of time.<\/p>\n

Production: Full-Stack Traceability and Dynamic Optimization<\/b><\/p>\n

When a product defect occurs, the LOM performs predecessor node searches along the Bill of Materials (BOM), reverse-tracing from the finished product back to the exact raw material batch to precisely locate the point of failure. In the smart factory, it acts as a routing engine, computing the shortest path for automated material handling equipment, significantly reducing dead time between operations. By monitoring task backlogs across workstations in real-time, it identifies throughput bottlenecks, enabling managers to dynamically allocate resources and smooth out the production flow.<\/p>\n

Sales & Marketing: High-Precision Customer Insight and Resource Allocation<\/b><\/p>\n

Leveraging historical interaction logs and social relation graphs, the LOM runs PageRank-style centrality algorithms to identify high-influence customer nodes, focusing your finite sales bandwidth where it generates the highest ROI. In owned <\/span>channel ecosystems operations, it uses common neighbor analysis starting from existing users to rapidly map and capture directly connected prospect clusters, fundamentally driving down customer acquisition costs. For high-value accounts, it constructs a full-journey behavioral funnel, uncovering the hidden relational patterns behind churn to power highly targeted retention strategies.<\/p>\n

Finance & Risk Management: Penetrative Oversight and Autonomous Compliance<\/b><\/p>\n

The moment funds are deployed, the LOM identifies direct transactional counterparties of the receiving account. If the connected component contains high-risk entities, it triggers an autonomous hard stop. For labyrinthine corporate equity structures, the LOM penetrates multi-hop ownership layers to expose the ultimate beneficial owner, delivering a crystal-clear risk topology for M&A and investment decisions. In three-way matching, it starts at the payment request and traverses upward to validate all predecessor documents \u2014POs, receipts, invoices\u2014ensuring complete transparency in financial settlements through automated alignment.<\/p>\n

From bare-metal architecture to real-world deployment, the LOM is rigorously grounded in actual enterprise needs. Its highly efficient, lightweight 4B<\/span>-parameter model design cracks the code on complex enterprise-level reasoning, massively lowering the barrier and cost of deploying enterprise AI. More than that, it builds the definitive bridge between structured databases and unstructured textual knowledge, creating a continuously evolving intelligence framework where enterprise data assets self-generate and self-optimize.<\/p>\n

Looking ahead,\u00a0Yonyou’s LOM will relentlessly push the technical frontier. We will upgrade our reinforcement learning strategies,<\/span> build open evaluation benchmarks, and tackle complex challenges. We are scaling\u00a0LOM’s inference capabilities in complex enterprise environments so that every<\/i> company is equipped with a deep-thinking “brain.”<\/p>\n

https:\/\/chinaxiv.org\/abs\/202601.00187<\/a>\u00a0<\/p>\n

\u00a0<\/p>\n

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