Support Robots for RPA Task Recognition and Workflow Automation
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Solution Overview
Problem
Current UI automation technologies are inefficient in automating repetitive communications and approvals in the workplace, leading to reduced employee productivity and delayed actions.
Innovation Solution
A system utilizing AI/ML models and RPA robots to monitor user interactions across multiple computing systems, analyze communications, and generate automations for initiating and responsive tasks, allowing for the deployment of RPA workflows that automate these tasks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual monitoring and handling of communications and approvals is performed, then employees can perform tasks with flexibility and judgment, but productivity is reduced and actions are delayed
Solution Approach 1:
The system enables self-service automation where RPA robots automatically monitor, analyze, and execute communications and approvals without human intervention. The robots independently perform tasks such as sending emails, updating status, and obtaining approvals, eliminating the need for employees to manually handle these repetitive communications and significantly improving productivity while reducing time delays
Solution Approach 2:
The patent replaces the mechanical human manual process with an automated RPA robot system. The robots use AI/ML models to analyze user interactions and automatically execute tasks that previously required manual human effort, such as monitoring communications, sending approvals, and updating status, thereby eliminating productivity losses and time delays associated with manual processing
2Productivity
If RPA robots are deployed to automate tasks, then productivity and efficiency are improved, but the system complexity increases
Solution Approach 1:
The RPA robot system is designed with multi-functionality to handle various types of communications and approvals across different applications and systems. A single robot framework can perform email sending, status updates, approval workflows, and monitoring across multiple user computing systems, reducing the need for separate specialized systems and managing complexity through universal automation capabilities
Solution Approach 2:
The system introduces an intermediary AI/ML model layer between the RPA robots and the various applications. This intermediary analyzes user interactions and determines automation opportunities, serving as a mediator that simplifies the complexity by providing a unified analysis layer that works across different systems and applications without requiring complex integration logic in each robot
3Measurement precision
If AI/ML models are used to analyze user interactions, then accurate pattern recognition is achieved, but computational resources and processing time are consumed
Solution Approach 1:
The system applies partial action by using AI/ML models selectively only for analyzing user interactions to determine automation opportunities, rather than continuously processing all data. The models analyze patterns in user communications and approvals to identify suitable tasks for automation, consuming computational resources only when needed for pattern recognition and automation decision-making, not for executing the actual automated tasks
Data Source
AI summary
Task automation by support robots for robotic process automation (RPA) is disclosed. RPA robots may be located on the computing systems of two or more users and/or remotely. The RPA robots may use an artificial intelligence (AI)/machine learning (ML) model that is trained to use computer vision (CV) to recognize tasks that the respective user is performing with the computing system. The RPA robots may then determine that the respective user is performing certain tasks on a regular basis in response to a certain action, such as receiving a request via email or another application, determining that a certain task has been completed, noting that a time period has elapsed, etc., and automate the respective tasks.