AI Integration Engine for Natural-Language RPA API Generation
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Solution Overview
Problem
Existing robotic process automations (RPAs) are complex and require extra training or knowledge to leverage third-party services, which conventional technologies have not effectively addressed.
Innovation Solution
An integration service engine leverages artificial intelligence to generate application programmable interface (API) requests when integrating robotic process automation (RPA) into a computing environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If end-users are provided with access to third-party services through RPA, then service integration capability is improved, but user training requirements and complexity increase
Solution Approach 1:
An AI agent is introduced as an intermediary between the user and the RPA system. The agent receives natural language requests from users, translates them into appropriate RPA workflows, and handles the complexity of service integration automatically, eliminating the need for users to learn RPA programming or API details while still providing access to third-party services
Solution Approach 2:
The system enables self-service by allowing users to simply state their needs in natural language without requiring any technical knowledge. The AI agent autonomously handles the entire process of workflow generation, API request creation, and service integration, making the system accessible to non-technical users while maintaining full service integration capability
2Manufacturing precision
If detailed API documentation and programming knowledge are provided, then integration precision is improved, but time consumption and cost increase
Solution Approach 1:
The patent replaces the mechanical approach of manually reading documentation and writing code with an AI-based system that automatically generates integrated workflows. The AI agent processes natural language requests and translates them into precise RPA workflows and API requests, achieving integration precision without requiring users to engage in time-consuming learning processes
3Adaptability or versatility
If catalogs of services grow larger, then service versatility is improved, but complexity of integration increases
Solution Approach 1:
The AI agent serves as a mediator that manages the complexity of large service catalogs. It understands the relationships between numerous third-party services, selects appropriate workflows automatically, and handles the integration complexity transparently to users, allowing the service catalog to grow without increasing user-perceived complexity
Solution Approach 2:
The system changes the interaction parameter from technical API knowledge to natural language communication. Users interact with services through simple natural language requests rather than learning complex integration parameters, allowing the system to support expanding service catalogs without increasing integration complexity for users
Data Source
AI summary
Disclosed herein is an integration service engine implemented as a computer program within a computing environment. The integration service engine operates to receive a request to perform a task and performing a semantic analysis on the request, utilizing artificial intelligence. The integration service engine also operates to retrieve relevant connectors based on the semantic analysis, determine objects and required fields needed for the request, and generate a code of a robotic process automation to implement the request based on the relevant connectors, the objects, and the required fields.