RPA Bot Porting via Intermediary Transformation System
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Solution Overview
Problem
Robotic process automation (RPA) platforms lack the ability to port bots between different platforms, leading to disconnected bot management and control tools, making it difficult for organizations to consolidate bots across multiple platforms.
Innovation Solution
A system and method for porting bots between RPA platforms by extracting bot configurations, transforming instruction sets, and deploying bots on new platforms, utilizing a bot control system with modules for porting, creation, deployment, and management, which includes machine learning algorithms for mapping and configuration adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If bot configurations are extracted and transformed between different RPA platforms, then adaptability and portability are improved, but device complexity and transformation process complexity increase
Solution Approach 1:
The patent introduces an intermediary transformation system that acts as a mediator between different RPA platforms. This system extracts bot configurations from source platforms, transforms them through a standardized intermediate format, and deploys them to target platforms. The intermediary approach enables portability without requiring direct integration between different platform-specific systems, thereby managing complexity through abstraction.
Solution Approach 2:
The bot configuration transformation process is segmented into distinct modular components: extraction module, transformation module, and deployment module. Each module handles a specific aspect of the porting process, allowing independent development, testing, and maintenance. This segmentation reduces overall system complexity by breaking down the complex transformation task into manageable, reusable components.
2Adaptability or versatility
If multiple RPA platforms are used for bot execution, then adaptability is improved, but management complexity and control difficulty increase
Solution Approach 1:
The transformation system implements universal interfaces and standardized configuration formats that work across multiple RPA platforms. By defining platform-agnostic bot configuration schemas and transformation rules, the system enables single bot definitions to be deployed to multiple different platforms without requiring separate management procedures for each platform, thereby reducing management complexity while maintaining platform flexibility.
3Adaptability or versatility
If bot porting between platforms is enabled, then consolidation capability is improved, but time and computational resources required increase
Solution Approach 1:
The system performs preliminary actions by pre-defining transformation rules, mapping configurations, and validation schemas before actual bot porting operations. These pre-configured transformation templates and platform-specific adapters are prepared in advance, allowing rapid bot porting without requiring complex real-time transformations. This preliminary preparation significantly reduces the time required for actual bot consolidation operations.
Data Source
AI summary
In an embodiment, a method of performance-enhanced machine-learning model creation is performed by a computer system. The method includes receiving a command to port a first bot from a first RPA platform to a second RPA platform, where the first bot executes a robotic process in a computing environment provided by a particular computer system using the first RPA platform. The method further includes extracting bot configurations for the first bot from the first RPA platform, where the bot configurations include an instruction set that at least partially defines the robotic process. The method also includes creating a second bot for the second RPA platform, where the creating includes transforming the instruction set to a format of the second RPA platform. In addition, the method includes deploying the second bot on the second RPA platform, wherein the deployed second bot executes the robotic process.