Production Scheduling · Work order execution · Process management
Enterprise Resource Planning (ERP)Purchasing · Sales Management · Inventory accounting
Warehouse Management System (WMS)Warehousing reservation · Inventory location management · Barcode Operations
Supply Chain Management SystemSupplier management · Demand Forecasting · Procurement Collaboration
Transportation Management System (TMS)Transport Orders · Route Planning · Transport Dispatch
Data Management Platform (DMP)Data Integration · Event collection · Tag Framework
Customer Relationship Management (CRM)Lead Management · Customer profile · Business opportunity follow-up
Private Livestream PlatformLivestream Broadcasting · Livestream Room Management · Audience Interaction
Customer Service Management SystemMulti-channel access · session assignment · Work order management
AI Customer Service Management SystemKnowledge Integration · Retrieval Augmentation · Intelligent Q&A
WeCom Management SystemClient synchronization · Tag Segmentation · Employee collaboration
Digital Human DevelopmentAvatar Management · Speech Synthesis · lip-sync drive
Construction Project Management SystemProject Registers · Construction Planning · Progress Tracking
Property & Industrial Park Management SystemProperty Resources · Lease Management · Fee Management
Education & Training Management SystemEnrollment Leads · Student profile · Course Management
Chain Store Management SystemStore Management · Product management · Stock transfer
Hotel & Travel Management SystemRoom Status · Booking Management · Check-in service
Healthcare & Elderly Care Management SystemService Profiles · Appointment Management · Care Plans
Laboratory Information Management System (LIMS)Sample Registration · Task allocation · Testing Workflows
Agriculture & Livestock Management SystemBase management · Production Planning · Environmental Monitoring
Energy & Environmental Management SystemEnergy Data Collection · Energy Dashboards · Equipment Monitoring
Government & Public Service Management SystemMatter management · Business acceptance · Workflow Approvals
Office Automation System (OA)Workflow Approvals · Organization Management · Attendance Management
AI & Large Language Model DevelopmentEnterprise knowledge base · Retrieval Augmentation · Agent Orchestration
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The basis of knowledge base Q&A is usable and locatable documents. Duplicate data, a mix of old and new versions, or a lack of directories will affect the search scope; sources, applicable times, and access permissions need to be sorted out before accessing the model.
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Answers with quotes do not mean that every sentence is supported by the source. RAG application needs to check the relationship between key conclusions and specific paragraphs. When the source only covers part of the business, the scope of the answer should also be limited and cannot be extended to conclusions for all situations.
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Agent calling tools may change orders or create tasks. The execution service should independently verify the identity, target record and parameters. The actions proposed by the model cannot be directly regarded as the authorization result. The execution record must also indicate whether it is actually completed.
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Large model data permissions need to be implemented at the retrieval and caching layer. The front-end hidden document list cannot prevent the backend from returning restricted content, and the shared cache cannot be read by all accounts by default. Answers and references need to follow the current identity scope.
Explore SolutionA successful demonstration answer does not mean that the large model application covers all businesses. Assessment samples need to include wording changes, insufficient information, and confusing objects, and the judgment criteria need to be clear before the test to avoid showing only smooth questions and answers.
Explore SolutionModel substitution affects return formats, tool requests, and unexpected behavior. The unified business interface helps reduce page migration costs, but just because the page can display text does not mean that tool calls and source references still comply with the original rules, and replacement requires independent verification.
Explore SolutionAI requests may fail during the retrieval, model or tool stages. The request identifier can connect each step, and the log can support troubleshooting without repeatedly saving the complete text. The field design should give priority to answering the failure location, time consumption and reasons.
Explore SolutionWhen intelligent customer service has no basis, it is necessary to let humans continue to deal with the same service problem. Users should not re-describe the entire context, and manual handovers should distinguish between facts provided by users and suggestions generated by the model. The handover content should be clear and traceable.
Explore SolutionBefore pictures and voices enter the business process, they need to be identified, confirmed and field converted. The text extracted by the machine can assist in input, and key data should be marked with confirmation status. Personnel should also be able to review the original input and correction process.
Explore SolutionAI performance depends on request type, context, and deployment resources. When discussing concurrency, it is necessary to distinguish between ordinary question and answer, retrieval and tool operations. Timeout retry may also cause repeated business actions, so the test needs to explain the actual load and execution conditions.
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