AI Subscription Management for Remote Infrastructure
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Solution Overview
Problem
Service providers face challenges in managing subscriptions for remote infrastructure due to limited access to usage and application data, leading to difficulties in identifying issues and initiating timely actions to address them.
Innovation Solution
The implementation of an automated subscription management system using an artificial intelligence-based framework that processes subscription, usage, and deployment data to identify optimal times for adjusting subscriptions proactively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If service providers deploy managed storage and server infrastructure at customer locations using subscription-based models, then they can provide flexible infrastructure services, but they face difficulty in obtaining usage and application data from remote customer locations
Solution Approach 1:
The patent introduces an intermediary data collection system that operates at the customer location to gather usage and application data. This intermediary component bridges the information gap between the remote customer environment and the service provider's central system, enabling data acquisition without requiring direct access to customer networks or modifying customer infrastructure.
Solution Approach 2:
The patent replaces manual or traditional mechanical data collection methods with automated electronic data gathering mechanisms. The system automatically collects usage data, application data, and subscription information through integrated software components that communicate with both customer and provider systems, eliminating the need for manual interventions or complex physical access arrangements.
2Device complexity
If service providers manually manage subscriptions without automated data collection, then they maintain simpler systems, but they cannot proactively identify issues or adjust subscriptions in timely manner
Solution Approach 1:
The patent implements preliminary data collection and analysis actions that occur continuously in the background. The system proactively gathers usage data, monitors application performance, and identifies potential subscription issues before they become critical, enabling timely adjustments without requiring complex real-time intervention processes.
Solution Approach 2:
The patent establishes automated feedback loops where usage data and application information continuously flow back to the subscription management system. This feedback mechanism enables the system to automatically detect anomalies, evaluate subscription performance, and trigger timely adjustments based on real-time conditions, significantly improving responsiveness compared to manual review processes.
3Measurement precision
If service providers collect and process extensive usage and deployment data using AI frameworks, then they improve subscription management accuracy and proactive issue identification, but they increase processing complexity and data handling requirements
Solution Approach 1:
The patent segments the data processing function into distinct modular components: data collection modules at customer locations, data transmission layers, and centralized AI analysis frameworks. This segmentation allows each component to handle specific data types and processing tasks independently, reducing overall system complexity while maintaining high measurement precision through specialized processing at each stage.
Data Source
AI summary
Methods, apparatus, and processor-readable storage media for automated subscription management for remote infrastructure are provided herein. An example computer-implemented method includes obtaining subscription data related to at least one subscription for hardware infrastructure provided by a service provider, wherein the subscription data is obtained by the hardware infrastructure at a remote location; obtaining usage data and deployment data for the hardware infrastructure that is associated with the at least one subscription; processing the subscription data, the usage data and the deployment data using an artificial intelligence-based framework to identify a time period for initiating performance of one or more actions to automatically adjust the at least one subscription, wherein the artificial intelligence-based framework identifies the time period based on historical subscription data related to one or more other subscriptions; and causing the performance of the one or more actions to be initiated within the identified time period.