Central Service Generating Customized Queries for Entity Evaluation
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Solution Overview
Problem
Small businesses face challenges in utilizing existing software applications due to their complexity and over-engineering, which leads to underutilization of features and increased costs, as these applications often provide more features than needed, creating a barrier for adoption.
Innovation Solution
A cloud-based service that generates customized queries to extract specific metric data from third-party applications, allowing businesses to selectively incorporate features and analyze data for improved efficiency, using APIs to interact with various applications and provide a unified platform tailored to the business's needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If small businesses adopt existing software applications, then they gain access to comprehensive features and services, but the applications become overly complex and costly, leading to underutilization
Solution Approach 1:
The patent segments the monolithic software application into modular microservices that can be independently selected and deployed. Each microservice represents a discrete functional unit (e.g., authentication, data storage, analytics) that businesses can choose based on their specific needs, avoiding the complexity of adopting entire application suites while still accessing comprehensive features when required.
Solution Approach 2:
The patent extracts only the necessary features and functions that small businesses require from complex software applications, separating them from unnecessary components. This extraction process creates a simplified, customized application package that maintains essential functionality while removing complexity and reducing costs, allowing businesses to adopt software without being forced to utilize unused features.
2Adaptability or versatility
If small businesses use over-engineered applications, then they access advanced features, but the onboarding process and learning curve become challenging, reducing adoption rates
Solution Approach 1:
The patent implements dynamic configuration and adaptive onboarding processes that adjust to the user's skill level and specific business needs. The system dynamically simplifies the interface and onboarding流程 based on the selected microservices and business context, providing advanced features when needed while maintaining ease of operation through adaptive complexity management.
Solution Approach 2:
The patent introduces an intermediary layer (abstraction layer or platform) that mediates between the complex underlying microservices infrastructure and the simple user interface. This intermediary handles the complexity of feature integration and configuration, presenting a simplified, unified interface to users while maintaining access to advanced capabilities through the intermediary's intelligent routing and management.
3Adaptability or versatility
If small businesses adopt comprehensive application packages, then they access multiple features, but they incur higher costs for features that may not be utilized
Solution Approach 1:
The patent applies local quality by allowing each business to customize their application package with specific microservices tailored to their local needs and requirements. Instead of providing uniform comprehensive packages to all businesses, the system enables selective adoption of features based on individual business contexts, ensuring that businesses pay only for the specific features they utilize while maintaining access to a variety of capabilities when needed.
Solution Approach 2:
The patent implements parameter changes by allowing businesses to dynamically adjust their feature set and configuration parameters based on their evolving needs. The system supports flexible parameter adjustment where businesses can add, remove, or modify microservice subscriptions, enabling cost optimization by aligning feature variety with actual utilization patterns while maintaining the ability to access comprehensive features when required.
Data Source
AI summary
Techniques for provisioning a central, cloud-based service (i) that generates customized queries for execution against multiple third-party applications to collect certain metric data and (ii) that generates an evaluation score based on the collected metric data are disclosed. A corresponding query is created for each of the third-party applications. Each query is designed to extract certain metric data. The queries are transmitted to their corresponding third-party applications. Metric data is returned, including first and second metric data. The first and second metric data are used to validate one another with respect to an event, which is classified. The metric data is weighted. An evaluation score is then generated based on the weighted metric data.