NLP Business Rule Management for Faster Enterprise Rule Updates
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Business rules in process enterprises require frequent updates due to market and environmental changes, necessitating technical knowledge and dependency on technical teams, leading to delays and non-user-friendly updates.
Innovation Solution
A system utilizing Natural Language Processing (NLP) to parse business user inputs, map business keywords to technical keywords, and update business rules accordingly, enabling business users to manage rules without technical knowledge.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If business rules are stored in form of rule-based logic requiring technical knowledge for updates, then the rules can be precisely managed and maintained, but the turnaround time for updating business rules increases and business users cannot directly control the rules
Solution Approach 1:
The patent introduces an intermediary layer consisting of natural language processing interfaces and keyword mapping systems that translate business users' natural language inputs into technical rule-based logic. This intermediary enables business users to update rules without technical knowledge while maintaining precision through structured translation layers.
Solution Approach 2:
The patent replaces the mechanical system of direct technical editing with an automated natural language processing system. Instead of requiring manual technical editing, the system uses NLP models to automatically interpret and implement rule updates from natural language inputs, significantly reducing update time while maintaining precision.
2Reliability
If business users depend on technical teams for rule updates, then technical accuracy is maintained, but the ease of operation for business users deteriorates and user-friendliness is reduced
Solution Approach 1:
The patent enables business users to perform self-service updates of business rules through natural language interfaces. Users can directly input their requirements in natural language, and the system automatically translates and implements the updates without requiring technical team intervention, thereby improving ease of operation while maintaining reliability through automated validation.
Solution Approach 2:
The system introduces an intermediary translation layer that converts natural language inputs into technically accurate rule updates. This intermediary maintains reliability by ensuring accurate translation while improving ease of operation by accepting simple natural language inputs instead of requiring technical expertise.
3Device complexity
If business rules require technical knowledge for modification, then the complexity of the system is reduced, but the adaptability of the system to business changes deteriorates
Solution Approach 1:
The patent replaces the complex mechanical process of technical rule editing with an automated natural language processing system. This substitution reduces the perceived complexity for business users while enhancing adaptability, as users can quickly modify rules in response to market changes using simple natural language inputs without needing to understand the underlying technical complexity.
Solution Approach 2:
The intermediary NLP layer shields business users from system complexity by handling the translation and technical processing automatically. This maintains low perceived complexity for users while enabling high adaptability, as the system can rapidly implement rule changes based on natural language inputs without requiring users to navigate complex technical interfaces.
4Manufacturing precision
If technical teams manually update business rules, then the manufacturing precision of rule implementation is maintained, but the productivity of the enterprise deteriorates due to delays in rule updates
Solution Approach 1:
The patent replaces the manual mechanical process of technical team editing with an automated natural language processing system. This substitution dramatically improves productivity by enabling instant or near-instant rule updates while maintaining manufacturing precision through automated validation and structured translation processes that ensure accurate implementation.
Solution Approach 2:
The system enables continuous rule updates by eliminating the discontinuous manual process of technical team involvement. Business users can continuously update rules as needed without waiting for technical team availability, maintaining uninterrupted business operations and improving overall productivity while preserving implementation precision through automated processing.
Data Source
AI summary
The present disclosure relates to method and system for managing business rules in a process enterprise. Firstly, an input from a user is received for managing one or more business rules from a plurality of business rules associated with the process enterprise. The input is parses for extracting one or more business keywords. Further, one or more technical keywords corresponding to the one or more business keywords are identified based on a pre-stored mapping information, using a Natural Language Processing (NLP) model. Then, at least one business rule is identified from the plurality of business rules based on the one or more technical keywords. Further, one or more actions to be performed on the at least one business rule is identified based on the input. Finally, the at least one business rule is updated, based on the one or more actions.