AI Software Platform Automating Requirements to Code
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Solution Overview
Problem
Current software development methodologies face challenges such as time-consuming and inaccurate requirements gathering, inflexibility, and the need for specialized technical skills, which hinder rapid and efficient software application development.
Innovation Solution
An AI-based Automated Software Application Development Platform that enables business analysts with no technical knowledge to visually model requirements, automatically design a persistent data layer, and generate a runnable software application, leveraging machine actionable abstract requirements models and machine learning for intelligence.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual requirements gathering using word processing and spreadsheet software is used, then requirements can be documented, but the process becomes highly manual and cumbersome, significantly increasing time consumption and requiring specialized technical skills
Solution Approach 1:
The patent replaces manual mechanical processes (word processing, spreadsheet software, flowcharting) with an AI-based automated system that uses machine learning models to gather, analyze, and translate requirements automatically, eliminating the need for manual documentation and technical translation steps
Solution Approach 2:
The patent introduces an AI-based intermediary system that acts as a mediator between business stakeholders and software developers, automatically translating business requirements into technical specifications and reducing the need for manual interpretation and communication overhead
2Adaptability or versatility
If packaged applications like ERP systems are used, then some requirements are captured, but significant customization is required which extends implementation time and increases cost
Solution Approach 1:
The patent enables dynamic customization of software applications through AI-generated code that can be automatically modified and adapted to specific business requirements, allowing the system to evolve and change rapidly without extensive reprogramming or lengthy implementation cycles
Solution Approach 2:
The patent allows rapid modification of application parameters and behavior through AI-driven requirements analysis, where changes in business requirements automatically translate to corresponding parameter adjustments in the software system, enabling flexible adaptation without extensive customization work
3Measurement precision
If traditional waterfall methodology is used, then comprehensive requirements documentation is created, but the process takes so long that requirements often become outdated or fail to meet actual business needs
Solution Approach 1:
The patent performs preliminary AI-based requirements analysis and validation early in the process, continuously gathering and refining requirements through automated interactions with stakeholders, ensuring requirements remain current and accurate throughout the development lifecycle without requiring lengthy documentation phases
Solution Approach 2:
The patent maintains continuous requirements gathering and refinement through automated AI processes that operate throughout the entire development lifecycle, rather than confining requirements work to a single upfront phase, ensuring requirements remain relevant and up-to-date continuously
4Productivity
If agile methodologies are used to reduce documentation focus, then iteration time is shortened, but the development lifecycle is not significantly reduced compared to waterfall approaches
Solution Approach 1:
The patent replaces manual agile iteration processes with AI-automated development workflows that continuously generate, test, and refine software code based on evolving requirements, dramatically accelerating development speed and reducing overall development time compared to traditional agile approaches
Data Source
AI summary
A system and method for an AI-based Automated Software Application Development Platform which intelligently gathers requirements from a business analyst and generates a runnable software application from those requirements. The AI-based platform enables the business analyst with no technical knowledge to visually model their requirements rapidly without requiring any programming Using the abstract requirements architecture and the platform, the analyst creates requirements models for the application's business processes and business tasks for each of the processes including defining the supporting information needs. The system intelligently assists the user in defining the information needs for each of the business processes and their tasks. Once the requirements models are created by the analyst with the help of the platform, the platform automatically designs and creates an appropriate persistent canonical data model for the application from the defined information needs. The platform then creates a runnable software application.