AI Flow builder
Problem: Creating workflows manually can be time-consuming and error-prone, especially for complex business processes. Businesses need a faster, more accurate way to generate workflows that align with their domain and data models.
Why It Matters: Manual workflow creation delays application development and increases the risk of misalignment with business objectives, leading to inefficiencies and higher costs.
Proposed Feature/Idea
Solution: Use AI to automatically generate workflows from user inputs, such as:
A prompt described in plain language (e.g., "Create a workflow to move inventory parts").
Existing business process or data model diagrams (e.g., BPMN, UML).
What It Does: AI analyzes the input to:
Understand the business logic.
Create workflows (like the one in the attached image) that can be directly used as a domain and data model in the low-code platform.
Example: Input a business prompt or upload a diagram, and the system generates a workflow like the "Move Inventory" process diagram in the attachment.
Business Impact
Time Savings: Reduces workflow creation time by up to 80%.
Error Reduction: Ensures workflows are consistent and accurate based on predefined business rules and domain models.
Scalability: Enables faster scaling of applications by automating repetitive workflow design tasks.
Key Features/Capabilities
Input Options:
Plain-language text prompts.
Uploaded business process or data model diagrams (e.g., JSON, XML).
AI-Powered Generation:
Natural language processing to interpret text.
Diagram parsing to identify workflows and relationships.
Workflow Outputs:
Fully editable workflows in the low-code platform.
Integration-ready domain and data models.
User Feedback Integration:
Allow users to edit and refine workflows with suggestions provided by AI.
Thank you for voting on this feature request. Our product team is currently reviewing it and evaluating its feasibility and potential impact. We will keep you updated on any progress.
-
Chat GPT just released GPTs. This would be an interesting way to work with our Flow data through generative AI. https://openai.com/blog/introducing-gpts
-
Has Novacura thought about utilizing this technology in FlowScript generation, similar to how Codex model is used in GitHub Copilot?
-
In the ever-evolving landscape of app development, speed and adaptability are paramount. Our proposal aims to empower Flow developers with a Generative AI Copilot, capable of swiftly building components of an app and facilitating real-time modifications, all through natural language conversations.
Key Benefits:
Rapid App Component Creation:
The Generative AI Copilot enables developers to efficiently construct app components, eliminating the need for time-consuming manual coding.
End-to-End App Creation:The Copilot can autonomously generate entire applications from scratch using OpenAI and Generative AI technologies, significantly reducing development timelines.
Adaptive Modification:Developers can request real-time adjustments to the app via natural language chat with the Copilot. Feedback and change requests can be seamlessly incorporated, making development agile and responsive.
Functionality:
This feature should encompass the following functionalities:Generative AI-Powered Copilot:
Conversational interface for app development.
Component generation based on developer instructions.
End-to-end app creation capabilities.
AI-driven code generation.
Real-time App Modification:Chat-based feedback and change requests.
Intelligent interpretation of developer inputs.
Automatic app adjustments based on conversational context.
Use Case:
Imagine a Flow developer tasked with creating a sales application. With the Generative AI Copilot, they can:Request the Copilot to construct a new component for tracking customer data with specific criteria, such as customers headquartered in the US.
Seamlessly integrate an Odata API to retrieve the required customer information, all generated automatically within the Flow Studio.
Continuously engage with the Copilot throughout the development process, refining and adapting the application based on evolving project requirements and feedback.
This feature empowers Flow developers to focus on the creative aspects of app development, while the Generative AI Copilot handles the technical implementation, drastically reducing development time and complexity.