AI Workflow Generation from Media Files
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Solution Overview
Problem
Current robotic process automation (RPA) workflows require significant time and effort for developers to manually recreate sequences of logic steps outside of RPA workflow development applications, even with drag-and-drop functionality, leading to duplicative efforts and inefficiencies.
Innovation Solution
A computer-implemented method using AI to automatically generate RPA workflows from text, images, or audio files by processing media files through a workflow generation module, accessing model databases, and predicting workflows for user selection, reducing the need for manual reproduction within RPA workflow development applications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If developers manually recreate workflows outside of RPA workflow development applications (using paper, text editors, or other capture mechanisms), then workflow ideas can be captured during commuting or other tasks, but duplicative effort is required to recreate the workflow in the RPA application
Solution Approach 1:
The patent uses optical character recognition (OCR) to capture workflow logic from images (such as photos of paper notes or whiteboards) and automatically converts them into executable RPA workflow code. This copying mechanism eliminates the need for manual recreation by directly transforming visual representations into functional workflows, thereby resolving the contradiction between capture flexibility and recreation time
Solution Approach 2:
The patent replaces the mechanical process of manual workflow recreation with an automated computer vision system. Instead of manually dragging and dropping activities or coding workflows, the system uses image processing and machine learning algorithms to automatically generate workflow code from captured images, substituting manual mechanical operations with automated computational processes
2Ease of operation
If developers use drag and drop functionality in RPA workflow development applications, then code writing is not required, but manual reproduction of workflow steps and identification of datatypes and variables still requires considerable time and effort
Solution Approach 1:
The patent enables the workflow development system to serve itself by automatically extracting activity names, parameters, and logic from input images and generating corresponding workflow code without requiring manual configuration. The system performs self-service workflow generation by interpreting visual representations and automatically populating workflow elements, thereby eliminating the time-consuming manual drag-and-drop process while maintaining ease of operation
Solution Approach 2:
The patent performs preliminary action by pre-processing and analyzing the input image to extract workflow logic, activities, and parameters before the actual workflow creation process. This preliminary analysis prepares the workflow structure in advance, so that when the workflow is generated, it is already configured with appropriate datatypes and variables, eliminating the need for subsequent manual configuration and accelerating development speed
Data Source
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AI summary
A robotic process automation (RPA) workflow may be automatically created from text, an image, and/or a media file. A workflow sequence may be converted into a digital format using optical character recognition (OCR), and this information may then be analyzed by an artificial intelligence (AI) model and converted into a predicted RPA workflow. The predicted RPA workflow may be presented to a developer for approval, denial, or modification. Information pertaining to the selection by the developer may then be used for subsequent retraining of the AI model to improve prediction accuracy.