AI Agents for RPA Workflow Conversion Between UI and API Automation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing robotic process automation (RPA) technologies face challenges in maintaining UI automation stability due to changes in the user interface, requiring more maintenance and developer time.
Innovation Solution
The implementation of AI agents using generative AI models to analyze UI automations and back-end communications, and to convert RPA workflows from UI automation to API automation, or vice versa, thereby enhancing flexibility and stability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If UI automation is used in RPA workflows, then automation can be easily designed and delivered, but maintenance requirements increase and reliability decreases when UI changes occur
Solution Approach 1:
The patent introduces an AI agent as an intermediary between UI automation and API automation. The AI agent analyzes UI elements, determines their corresponding backend APIs, and automatically generates API automation workflows. This intermediary transformation layer allows the system to leverage the ease of UI automation design while achieving the stability of API automation, as the AI agent handles the complexity of mapping and translation automatically.
2Productivity
If UI automation is used in RPA workflows, then automation can be implemented quickly, but maintenance time increases when UI structure changes
Solution Approach 1:
The patent applies preliminary action by having the AI agent proactively analyze UI elements and generate corresponding API automation workflows before UI changes cause problems. The system continuously monitors UI elements and pre-generates updated API automation when UI changes are detected, rather than waiting for automation failures to occur and then manually fixing them.
Solution Approach 2:
The AI agent enables self-service automation maintenance by automatically detecting UI changes, analyzing the impact on existing workflows, and generating updated API automation without human intervention. The system monitors itself and performs self-updates, eliminating the need for manual maintenance when UI structures change.
3Reliability
If API automation is used instead of UI automation, then reliability and stability improve, but complexity of automation design increases
Solution Approach 1:
The AI agent serves as an intermediary that automatically handles the complex task of mapping UI elements to backend APIs. Instead of requiring automation designers to manually understand and implement complex API interactions, the AI agent performs this translation automatically, generating ready-to-use API automation workflows from UI automation definitions.
Solution Approach 2:
The patent replaces the manual mechanical process of API automation design with an AI-based automated system. The AI agent uses machine learning and natural language processing to automatically generate API automation workflows, substituting the complex manual configuration process with an intelligent automated system that reduces design complexity for users.
Data Source
AI summary
Artificial intelligence (AI) agents for user interface (UI) automation to application programming interface (API) automation, and vice versa, are disclosed. The operations performed by a UI automation on the back-end can be captured by an AI agent, including what communications are sent and the context thereof. A robotic process automation (RPA) activity can then be built in an RPA workflow that replaces the UI automation with an API automation. Alternatively, an API automation is replaced with a UI automation. The AI agent employs a fine-tuned generative AI model to understand the context of the communications. The AI agent may also find obsolete duplicates of UI automations and replace these with API automations, or vice versa.