Enterprise Application Workflows from Unstructured Conversation
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Solution Overview
Problem
Generating enterprise applications is a cumbersome, time-consuming, and expensive process that requires specialized personnel and resources, especially for smaller enterprises lacking expertise in software development, leading to inefficient and unsuitable solutions.
Innovation Solution
Utilizing simple and unstructured conversational inputs to generate workflows and applications through a generative AI system, leveraging a transformer model and knowledge base to intuitively learn and create customized workflows and persona templates tailored to specific enterprise needs, without requiring detailed architectural or coding instructions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional methods are used to generate enterprise applications with specialized personnel and detailed architectural design, then application quality and functionality are improved, but development time and cost increase significantly
Solution Approach 1:
The system performs preliminary actions by pre-defining persona templates with standard workflows, data models, and application structures. When a user selects a persona template, the application is automatically generated based on these pre-configured elements, eliminating the need for time-consuming architectural design and coding from scratch while maintaining consistent quality standards.
Solution Approach 2:
The system uses copying by providing persona templates that represent proven application patterns and structures. These templates can be copied and adapted for different enterprise needs, allowing rapid deployment of high-quality applications without reinventing the wheel for each project.
2Reliability
If traditional application development with specialized personnel is used, then application functionality and quality are improved, but resource requirements and cost increase
Solution Approach 1:
The system enables self-service by allowing enterprise users to generate applications independently using persona templates and conversational input. Users without specialized programming knowledge can select appropriate templates, provide basic requirements, and receive functional applications automatically, eliminating the need for external developers or specialized personnel.
Solution Approach 2:
The system achieves universality by creating a platform that serves multiple purposes: it generates various types of enterprise applications, supports different persona templates for different functional needs, and works with users of varying technical expertise. This multi-functional approach reduces resource requirements by consolidating multiple specialized roles into a single user-friendly system.
3Adaptability or versatility
If custom application development is pursued for specific enterprise needs, then application suitability and functionality are improved, but development complexity and effort increase
Solution Approach 1:
The system applies local quality by allowing users to customize specific aspects of applications based on their local enterprise needs while maintaining the overall structure provided by persona templates. Users can modify data models, workflows, and interfaces to match their specific requirements without having to redesign the entire application architecture.
Solution Approach 2:
The system incorporates dynamics by making persona templates configurable and adaptable. The templates are not static but can be adjusted through conversational input and configuration options, allowing the application structure to dynamically adapt to specific enterprise needs while maintaining the benefits of pre-defined quality standards.
4Reliability
If enterprises hire outside consultants or third parties to develop applications, then application development expertise is obtained, but cost and loss of control over the development process increase
Solution Approach 1:
The system empowers enterprises to perform application development themselves using persona templates and conversational input. This self-service capability eliminates the need to hire outside consultants or third parties, giving enterprises full control over the development process while maintaining access to professional-grade application patterns and structures through the templates.
Data Source
AI summary
Systems and methods for using simple and unstructured conversational input, which is a part of an interactive conversation between a user and a system, to automatically generate a workflow for performing an enterprise task is described. The methods include generating a configurable application that includes the workflow, which when executed, performs the enterprise task. A simple conversational input, which is unstructured data, is processed to determine a task to be performed and a persona that will be performing such a task. Deep learning techniques are applied to leverage related data in the same domain from a knowledge base, that is associated with a foundational transformer model. A workflow involving a plurality of steps is automatically generated in-real time, based on the leveraged learning, while the interactive conversation is still in progress. A user interface that displays both the generated workflow and the input conversation is generated.