Automatic Workflow Template Generation from Natural Language Requirements
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Solution Overview
Problem
Existing workflow management and automation tools require users to describe workflows in a step-by-step manner, which is inefficient and not compatible with iterative and automated workflow creation processes, especially for users unfamiliar with the tool's capabilities.
Innovation Solution
A workflow management and automation tool that automatically generates a workflow based on a user-specified business requirement using a clustering machine learning model to identify workflow pattern clusters and generate a template, which can be refined iteratively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If users describe workflows in a step-by-step manner using existing tools, then the workflow can be created with detailed control, but the process becomes inefficient and has a steep learning curve
Solution Approach 1:
The system performs automatic workflow generation where the AI model autonomously creates workflows from natural language business requirements without requiring users to manually define each step. This self-service approach eliminates the need for users to learn complex step-by-step configuration processes while maintaining high productivity.
Solution Approach 2:
The patent replaces the mechanical manual configuration process with an AI-based automated system. Instead of requiring users to interactively build workflows step-by-step, the system uses machine learning models to automatically generate workflows from text descriptions, substituting human manual effort with intelligent automation.
2Extent of automation
If users manually configure workflows step-by-step, then complete control over workflow details is achieved, but the process is not compatible with automated workflow creation
Solution Approach 1:
The system replaces manual workflow configuration with automated AI-driven generation. The machine learning model automatically creates workflows from natural language inputs, eliminating the need for users to navigate complex configuration interfaces and making the process compatible with automated creation pipelines.
Solution Approach 2:
The patent introduces an AI language model as an intermediary between the user's natural language requirement and the workflow system. This intermediary translates business requirements into structured workflow definitions automatically, bridging the gap between simple text input and complex workflow configuration without requiring users to directly manipulate workflow elements.
3Manufacturing precision
If existing tools require detailed step-by-step workflow descriptions, then precise workflow specification is achieved, but novice users find the process difficult and time-consuming
Solution Approach 1:
The AI system autonomously generates precise workflow specifications from natural language inputs without requiring users to manually define each step. This self-service capability maintains high specification precision while dramatically reducing the time investment required from users, as the system handles the detailed configuration work automatically.
Solution Approach 2:
The system performs preliminary workflow generation based on natural language business requirements before user review. The AI model pre-configures the workflow structure, tasks, and dependencies based on the input description, providing a ready-to-review template that reduces both creation time and the effort needed for finalization while maintaining precision.
Data Source
AI summary
A workflow management and automation tool is disclosed. A plurality of workflow patterns is clustered into one or more workflow pattern clusters based at least in part on a plurality of existing workflows and associated specifications. A specification of a desired workflow is received. A template for the desired workflow is generated via a workflow predictive model. The generating of the template includes identifying one of the one or more of workflow pattern clusters corresponding to the specification of the desired workflow. The generating of the template includes using a portion of the workflow predictive model trained using the identified one workflow pattern cluster to generate the template for the desired workflow.