Natural Language Sub-Skill Logic With Iterative Validation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing workflow automation systems require extensive coding expertise and lack a comprehensive natural language-based interface, limiting accessibility and efficiency.
Innovation Solution
A system and method for generating executable logic of a sub-skill using a processor that receives user-defined goal and requirement information, generates a machine-readable meta-plan, and iteratively refines the logic through validation operations to align with user expectations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional software solutions with coding requirements are used, then system functionality is achieved, but user accessibility and efficiency deteriorate due to steep learning curves and technical complexities
Solution Approach 1:
The patent introduces a natural language processing intermediary layer between the user and the workflow automation system. Users interact through conversational language rather than code, and the system translates this natural language into executable workflows automatically. This mediator eliminates the need for users to learn programming while maintaining full system functionality.
Solution Approach 2:
The patent replaces the mechanical coding process with an automated natural language interpretation system. Instead of requiring manual code writing and compilation, the system uses AI-driven natural language understanding to automatically generate and execute workflow logic, substituting the traditional mechanical development process with an intelligent automated system.
2Productivity
If traditional coding methodologies are used, then precise control over system operations is achieved, but productivity deteriorates due to time-consuming development and maintenance
Solution Approach 1:
The patent implements preliminary action by pre-defining workflow templates, common operations, and standardized process patterns within the system. When users describe their needs in natural language, the system matches these against pre-configured templates and automatically assembles workflows from proven components, eliminating the need to build everything from scratch and dramatically reducing development time.
Solution Approach 2:
The patent enables copying and reusing of workflow patterns, templates, and successful process configurations. Once a workflow is created or validated, it can be replicated and adapted for similar tasks, allowing organizations to build upon existing work rather than recreating solutions, thereby significantly improving productivity and reducing repetitive development effort.
3Adaptability or versatility
If comprehensive natural language interface is implemented, then user accessibility improves, but system complexity and processing requirements worsen
Solution Approach 1:
The patent segments the natural language processing system into distinct functional modules: intent recognition, entity extraction, workflow template matching, and automated assembly. Each module handles a specific aspect of the translation from natural language to executable workflow, making the overall complex system manageable through clear separation of concerns and specialized processing for each function.
Data Source
AI summary
A system for generation of a sub-skill is disclosed. The system includes a processor that is configured to: receive an input comprising goal information to achieve a first sub-skill, and requirement information to achieve the goal for the first sub-skill; generate a machine readable meta-plan based on the input. The processor is further configured to generate a first executable logic based on the generated machine readable meta-plan; and iteratively refine the generated first executable logic to obtain a refined executable logic based on a validation operation. In the validation operation, when the first executable logic is executed, an output dataset is generated and compared with an outcome specified by the goal and the requirement information such that in each iteration of the refinement of the generated first executable logic, one or more errors or inconsistencies in the first executable logic is removed.