Autonomous API Trigger Generation for Data Integration
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Manual integration of large data sets into software systems is time-consuming and resource-intensive, particularly when integrating external data to initiate workflows, which often involves hundreds of keys and requires significant human effort.
Innovation Solution
A method and system that autonomously generate an API trigger based on data objects within a data segment, such as a JSON blob, using a processor to identify key-value pairs and recursively iterate through the data structure, allowing for automated workflow initiation, including threat remediation and data enhancement procedures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual integration of large data sets is performed using a client user interface, then data can be integrated into the system, but the process becomes time-consuming and resource-intensive
Solution Approach 1:
The system performs self-service by automatically analyzing received data segments, identifying data objects and their types, and generating API triggers without requiring manual user configuration. The processor autonomously iterates through data structures, infers types, and creates workflow triggers, eliminating the need for manual data integration efforts while maintaining high accuracy.
Solution Approach 2:
The system performs preliminary actions by pre-defining data object types and their associated API triggers before actual data integration occurs. When data segments are received, the system has already prepared the framework for automatic type identification and trigger generation, enabling rapid processing without manual intervention during the integration phase.
2Reliability
If manual integration of large data sets is performed using a client user interface, then data can be integrated into the system, but significant human resources are required
Solution Approach 1:
The system performs self-service by automatically analyzing received data segments, identifying data objects and their types, and generating API triggers without requiring manual user configuration. The processor autonomously iterates through data structures, infers types, and creates workflow triggers, eliminating the need for manual data integration efforts while maintaining high accuracy.
Solution Approach 2:
The patent replaces the mechanical manual process of data integration with an automated computational system. Instead of human operators manually configuring each data object and trigger through a user interface, a processor executes algorithms to automatically identify data objects, determine their types, and generate corresponding API triggers, substituting human labor with automated mechanical computation.
3Loss of time
If automated workflow initiation is implemented, then integration time is reduced, but system complexity increases
Solution Approach 1:
The system implements a universal processor-based platform that handles multiple functions: receiving data segments, identifying data objects, determining data types, generating API triggers, and initiating workflows. This multi-functional approach consolidates what would otherwise require separate systems for each task, reducing overall system complexity while enabling automated workflow initiation and significantly reducing integration time.
Solution Approach 2:
The system introduces an intermediary processing layer between data receipt and workflow initiation. This intermediary automatically analyzes data segments, identifies objects and types, and generates appropriate API triggers before passing control to workflow execution. This intermediary layer simplifies the overall process by handling complexity internally while presenting a clean interface to users.
Data Source
AI summary
Methods and systems for initiating a workflow are disclosed. The systems and methods described herein may receive as input a data segment from an external source, and identify at least one type of data object present in the data segment. The systems and methods described herein may then autonomously generate an application programming interface (API) trigger to initiate a workflow, wherein the API trigger is based on the at least one type of data object present in the data segment.