Macro Bot Rule Database for Cross-Platform RPA Updates
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Solution Overview
Problem
In a networked system with disparate applications and bots, implementing system-wide updates is inefficient due to compatibility issues and the need for individual code updates across different programming languages and platforms.
Innovation Solution
A macro bot system that detects and modifies execution data within data towers associated with bots, allowing for platform-agnostic automation of bot behavior without altering the bots' code, and provides reporting functions to manage and query bot activities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If individual code updates are applied to bots and applications across different platforms and programming languages, then system-wide rule implementation is achieved, but the complexity of management and time required for updates increase significantly
Solution Approach 1:
The patent introduces a central rules database as an intermediary layer between the macro bot and individual bot applications. This rules database stores execution data that bots can access without requiring direct code modifications. The macro bot acts as a mediator that updates rules in the central database, which then automatically propagates to all connected bots, eliminating the need for manual code updates across multiple platforms and languages.
Solution Approach 2:
The patent creates a universal rules database that serves multiple bot applications across different platforms and programming languages through a common interface. This centralized system allows a single rule update to affect all bots uniformly, providing multi-functional capability that replaces numerous individual update processes with one universal update mechanism.
2Reliability
If individual code updates are applied to bots and applications, then system-wide rule changes are implemented, but the time required for updates and system downtime increase
Solution Approach 1:
The patent implements preliminary action by having bots continuously access and cache execution data from the rules database before actual rule changes are needed. When rule updates occur in the database, bots can quickly retrieve updated rules without requiring full application restarts or lengthy code deployment processes, significantly reducing update time and downtime.
Solution Approach 2:
The central rules database serves as a mediator that enables rapid rule propagation. Instead of updating individual bot codes sequentially across multiple systems, the rules database receives updates once and automatically makes them available to all bots simultaneously, dramatically reducing the total time required for system-wide rule implementation.
3Reliability
If bots are updated across different programming languages and platforms, then comprehensive rule coverage is achieved, but computational resources and processing overhead increase
Solution Approach 1:
The patent extracts the rule management functionality from individual bot codebases and consolidates it into a separate, centralized rules database. This extraction allows bots to access rules as external data rather than embedded code, reducing the computational overhead of rule processing in each bot while maintaining comprehensive rule coverage across all platforms and languages.
Solution Approach 2:
The patent uses copying by having bots retrieve and cache copies of execution data from the central rules database. Instead of each bot independently processing and interpreting rules from multiple sources, bots receive standardized copies of rules through the unified interface, reducing redundant computational work while ensuring comprehensive rule coverage across diverse platforms.
Data Source
AI summary
A system for managing process automation with a macro bot is provided. By allowing for modifications to RPA bot behavior without changing the code of the RPA bots and providing for an efficient querying and reporting function, the system addresses a number of computer technology-centric challenges. The system allows the entity to push updates to bot behavior through a rules database without individually reconfiguring each bot. This ensures that the functionality of the bots may be updated for future entity needs and objectives while minimizing bot downtime. Furthermore, providing updates without changing the code of the bots allows the system to increase computing efficiency by reducing the demands on computer resources associated with applying a system-wide update, such as processing power, memory space, storage space, cache space, electric power, and networking bandwidth.