Semantic RPA Builder for Zero-Code Workflow Generation
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Solution Overview
Problem
Novice developers face time-consuming processes when manually configuring activities in robotic process automation (RPA) workflows, as they require coding and logical thinking skills, which are barriers for those unfamiliar with these concepts.
Innovation Solution
A semantic automation builder that uses machine learning to generate workflows from natural language descriptions, providing a zero-code intuitive user interface for editing actions and automating activity configurations, enabling enhanced discoverability of activities and reducing design time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If manual configuration of activities is used in RPA workflow designer applications, then developers can configure workflows with full control, but the process becomes time-consuming and requires coding expertise
Solution Approach 1:
The system enables self-service automation by allowing the RPA bot to automatically discover and configure activities without human intervention. The bot autonomously navigates the target application, identifies actionable elements, and generates workflow activities based on observed user interactions, eliminating the need for manual configuration by developers
Solution Approach 2:
The patent replaces the mechanical manual configuration process with an automated discovery mechanism. Instead of developers manually setting up activities through a workflow designer interface, the system uses an RPA bot to automatically explore the target application, capture user actions, and translate them into configurable workflow activities, substituting human effort with automated software agents
2Adaptability or versatility
If manual configuration of activities is used in RPA workflow designer applications, then developers can customize workflows according to specific needs, but coding and logical thinking skills are required
Solution Approach 1:
The patent introduces an intermediary RPA bot that acts as a bridge between the target application and the workflow designer. The bot observes user interactions with the application, translates these interactions into meaningful activities, and presents them to the workflow designer in a structured format. This intermediary layer enables novice developers to create customized workflows without needing to understand coding concepts or complex logical structures
Solution Approach 2:
The system uses copying by having the RPA bot replicate user actions and interactions with the target application. The bot captures screenshots, records user clicks and inputs, and creates copies of these interactions as workflow activities. This copying mechanism allows the workflow to be automatically generated based on actual usage patterns, enabling customization without requiring developers to manually program each step
3Productivity
If automated activity configuration is implemented, then design time is reduced and accessibility to novice developers is improved, but automation extent increases
Solution Approach 1:
The system performs preliminary action by having the RPA bot execute the discovery process before the actual workflow design begins. The bot proactively explores the target application, identifies all possible activities and their relationships, and prepares a structured representation of the workflow. This preliminary automated configuration reduces the subsequent design time and allows novice developers to work with pre-analyzed data
Solution Approach 2:
The patent implements feedback by having the RPA bot continuously monitor and learn from user interactions with the target application. The bot captures feedback from actual usage patterns, refines its understanding of the workflow requirements, and adjusts the automated configuration accordingly. This feedback loop enables the system to improve its automation capability over time while maintaining ease of use for novice developers
Data Source
AI summary
A method is provided. The method is implemented by a semantic automation builder executed on a processor. The method generating semantic automations of a robotic process automation. The method includes receiving user inputs corresponding to a target application, a written automation task, or steps to identify actions of the robotic process automation. The method also includes mapping each action to an activity to generate mapped activities, transforming the actions into the semantic automations based on the mapped activities, and providing the semantic automations in a user interface of the semantic automation builder to enable editing of the actions.