黄金城集团

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SIE MI

SIE MI
Origin of the Concept:Derived from the closed-loop governance philosophy of "Formulating Rules → Establishing Core → Observing Changes → Making Decisions → Issuing Orders" in traditional Chinese management wisdom.
Value Goal:Empowering Chinese manufacturing enterprises to build digital leadership.
Business Coverage:Inventory of data resources,Assetization of data resources,Indexing of data assets,Servitization of indices,Scenario-based application of services,Value realization of scenarios
Product Forms:MI Light (Data sets → Charts, reports, digital twins; benchmarking traditional BI): Tailored for medium-sized enterprises with needs for rapid deployment and application.
MI Pro (Data governance → Index system → Three major centers + AI-driven): Designed for large enterprise groups with diversified operation requirements.
Technical Architecture:Self-developed visual designer,Self-developed lake-house integrated index engine,Self-developed early warning engine,Self-developed intelligent business analysis agent,Self-trained industry-specific large models,
Deployment Architecture:Support for standalone deployment, microservice deployment, high-availability deployment, etc.
Product Honors:National Cross-Platform for Industrial Internet
Huawei Cloud Certification
SIE MI
Core business scenario
Early Warning Center

Management Philosophy: Observe subtle changes, anticipate trends through data, and eliminate risks invisibly.

Scenario Value: Sense and predict abnormal fluctuations in production, supply, and sales within seconds, nipping operational and management risks in the bud.
Functional Features: Multiple types of warning objects, flexible rule configuration, hierarchical push of risk messages, AI-driven root cause tracing, and cross-domain collaboration.
Data Characteristics: Real-time aggregation of global data, millisecond-level stream processing, and multi-source heterogeneity.
Technical Features: Rule engine + deep learning, visual tracking, and personalized cockpits tailored to individual users.


Early Warning Center Early Warning Center
Decision-Making Center

Management Philosophy: Establish a five-tier system covering "group, company, value stream owner, business domain supervisor, and frontline executor."

Scenario Value: Enable linkage among multi-level decision-making organizations, build consensus, and align goals across all levels.

Functional Features: 100% consistency of indicator data, 3-level drill-down to details, and intelligent auxiliary analysis.

Data Characteristics: Fusion of multi-source heterogeneous data, interweaving of historical and real-time data, and digital twin simulation.

Technical Features: AI-assisted attribution, integration of decision-making and task execution.


Decision-Making Center Decision-Making Center
Command Center

Management Philosophy: The only manifestation of data value lies in improving task execution and verifying results.

Scenario Value: Ensure rigid closed-loop execution, intelligently summarize experience, and eliminate vague accountability.

Functional Features: Intelligent task recommendations, pre-configured lean templates, and full-cycle traceability of tasks.

Data Characteristics: Real-time penetration of command streams and full-link traceability.

Technical Features: Automatic integration of improvement experience into knowledge graphs to support future optimizations.


Command Center Command Center
Indicator System

Management Philosophy: Establish standards, integrate data and logic into governance, and turn baselines into benchmarks.

Scenario Value: Connect strategic decoding to execution endpoints, anchor business directions with quantitative metrics, and eliminate vague goals.

Functional Features: AI-driven multi-dimensional penetration diagnosis, supporting closed-loop integration of goals, actions, and verification.

Data Characteristics: Fusion of global heterogeneous data, interweaving of historical, real-time, and predictive data, and traceability of indicator lineage.

Technical Features: Knowledge graphs to build indicator networks, and intelligent engines to recommend optimal baseline ranges.


Indicator System Indicator System
Data Governance

Management Philosophy: Establish standards with data and shape order through governance.

Scenario Value: Break down data silos, build a trusted data foundation, and support the three centers.

Functional Features: Metadata lineage penetration, quality rule engines, and hierarchical authorized governance.

Data Characteristics: Global heterogeneous integration (OT/IT/ETL), indicator-based conversion, and interweaving of three data states.

Technical Features: AI-driven intelligent cleaning and completion, with dynamic policy engines supporting compliant evolution.


Data Governance Data Governance
Product blueprint
As the 4th-generation intelligent decision-making platform, SMI signifies the ultimate transformation from data display to an intelligent decision-making brain. It breaks through the static presentation of traditional BI, with "indicator-knowledge hybrid analysis" at its core, constructing a complete decision chain covering "what the figures are → why they are so → what to do about it".


By integrating the four-tier data governance foundation (standards/modeling/indicators/services) and the dual-dimensional depth of knowledge governance (information + theory), it forms an event-logic graph that can precipitate business wisdom. Leveraging AI-driven visualization frameworks, Doris real-time computing, and AI semantic engines, it achieves an intelligent leap from data atoms to decision actions, ultimately delivering directly executable optimization solutions (such as dynamic response strategies for supply chain disruptions). This enables enterprise decision-making to be as precise and traceable as "using a turtle shell oracle to determine the universe's order".


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Application value
Early Warning Center (Anticipating Issues)

Timely capture key indicator information across all business domains. Based on preset management rules (Know-How) and AI capabilities, it provides real-time warnings of operational risks, automatically attributes causes, and prompts relevant responsible persons to take improvement actions.

Command Center (Execution Closed-Loop)

Assign tasks with supporting templates integrated with concepts like 8D and lean improvement. It manages task progress, tracks execution results, and upon task completion, verifies the closed-loop effectiveness to ensure precise alignment with goals.

Decision-Making Center (Analysis & Decision-Making)

The management cockpit dynamically simulates target baselines, anchoring budgets and assessments during operational meetings. It decomposes benefit drivers through special reports, quantifies performance management, and outputs decision schemes. It links with the Early Warning Center to calibrate risk thresholds and issues executive guidelines to the Command Center.

Customer cases
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