An ai-driven platform private domain data adaptive sharing system and method

By using an AI-driven platform private domain data sharing system, data collection and task priorities are dynamically adjusted, and high-priority tasks are assigned backup resources. This solves the problems of data synchronization delays and unreasonable resource allocation caused by manual scheduling, thereby improving task processing efficiency and customer satisfaction.

CN122387609APending Publication Date: 2026-07-14GUANGDONG LETEN TECH DEV CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
GUANGDONG LETEN TECH DEV CO LTD
Filing Date
2026-04-15
Publication Date
2026-07-14

AI Technical Summary

Technical Problem

In the existing platform's private domain data sharing system, manual scheduling leads to data synchronization delays and the inability to dynamically adjust task priorities. This results in delayed handling of urgent issues, resource consumption for ordinary issues, low task processing efficiency, and a high risk of customer churn, especially in the case of unreasonable resource allocation under high-concurrency tasks.

Method used

It adopts an AI-driven dynamic data acquisition mechanism, scene feature analysis mechanism, task execution efficiency monitoring mechanism, and task execution progress adjustment mechanism. It adaptively adjusts the data acquisition cycle and task priority according to the urgency and importance of the scene, sets up backup resources for high-priority tasks, and monitors and adjusts the task execution progress in real time to avoid task congestion and duplication.

Benefits of technology

It improved the efficiency of data scheduling tasks, avoided task congestion and timeouts, reduced the risk of customer churn, optimized resource allocation, and improved the efficiency of handling customer issues.

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Abstract

The application discloses an AI-driven platform private domain data adaptive sharing system and method, relates to the technical field of platform private domain data sharing, and sets a dynamic data collection mechanism to collect data in platform private domain data; sets a scene feature analysis mechanism to acquire data scheduling task priorities and allocate data scheduling available resources according to the priorities; sets a task execution efficiency monitoring mechanism to monitor and process automatic repeated execution in a task execution process; sets a task execution progress and threshold adjustment mechanism to adjust the task execution progress; and monitors task concurrency in real time, and adjusts the task execution progress in time when it is monitored that the task concurrency exceeds a threshold, so that the processing efficiency of tasks with higher urgency under high-concurrency task conditions is improved, and the shortage of high-priority task processing resources caused by low-priority task occupation of resources is solved.
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