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Core Business Scenario

Core Business Scenario
Early Warning Center Decision-Making Center Command Center Indicator System Data Governance Qiaojiang Large Model Industry Solution Library
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.


Learn moreEarly Warning CenterEarly Warning Center
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.


Learn moreDecision-Making CenterDecision-Making Center
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.


Learn moreCommand CenterCommand Center
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.


Learn moreIndicator SystemIndicator System
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.


Learn moreData GovernanceData Governance
Data Governance Data Governance
Qiaojiang Large Model
Domain Knowledge Embedding: Compression of hundreds of billions of industrial knowledge and understanding of hundreds of management theories.

Multimodal Perception: Collaborative decoding of sound, image, and time-series data, with built-in mechanism models.

Causal Reasoning Engine: Breaking through the limitations of traditional AI's focus on correlation, and proficient in sand table simulation.

Few-Shot Adaptation: Self-synthesis and self-supervision of samples, solving the dilemma of scarce industrial data.

Human-Machine Collaborative Evolution: Two-way domestication between experts and AI, with automatic feedback of precipitated business knowledge to the model.

Learn moreQiaojiang Large Model Qiaojiang Large Model
Qiaojiang Large Model Qiaojiang Large Model
Industry Solution Library

Rich Indicators and Diverse Scenarios: Preset with over 2,000 industry-standard indicators, digital twin models, and analysis scenarios.
Battle-Tested Best Practices: All solutions are derived from and validated by the practical experience of leading enterprises.
Ready-to-Use with Preset Integration: Indicators, models, and scenario rules can all be published to the MI platform with one click.
Modular Assembly for Flexible Adaptation: Supports "LEGO-style" on-demand selection to form complete scenario solutions.
Continuous Evolution and Ecological Co-construction: The solution library can continuously absorb industry wisdom and evolve dynamically.

Learn moreIndustry Solution LibraryIndustry Solution Library
Industry Solution Library Industry Solution Library
Core Business Scenario

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.


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.


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.


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.


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.


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.


Qiaojiang Large Model
Domain Knowledge Embedding: Compression of hundreds of billions of industrial knowledge and understanding of hundreds of management theories.

Multimodal Perception: Collaborative decoding of sound, image, and time-series data, with built-in mechanism models.

Causal Reasoning Engine: Breaking through the limitations of traditional AI's focus on correlation, and proficient in sand table simulation.

Few-Shot Adaptation: Self-synthesis and self-supervision of samples, solving the dilemma of scarce industrial data.

Human-Machine Collaborative Evolution: Two-way domestication between experts and AI, with automatic feedback of precipitated business knowledge to the model.

Industry Solution Library

Rich Indicators and Diverse Scenarios: Preset with over 2,000 industry-standard indicators, digital twin models, and analysis scenarios.
Battle-Tested Best Practices: All solutions are derived from and validated by the practical experience of leading enterprises.
Ready-to-Use with Preset Integration: Indicators, models, and scenario rules can all be published to the MI platform with one click.
Modular Assembly for Flexible Adaptation: Supports "LEGO-style" on-demand selection to form complete scenario solutions.
Continuous Evolution and Ecological Co-construction: The solution library can continuously absorb industry wisdom and evolve dynamically.

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