Description:A SYSTEM FOR THE DESIGN AND GENERATION OF USER INTERFACE COMPONENTS FROM NATURAL LANGUAGE & METHOD THEREOF

TECHNICAL FIELD
[0001] The present invention relates to the field of user interface (UI) design and development, specifically to systems and methods for automating the generation of UI components. More particularly, the invention implements Artificial Intelligence (AI) and Natural Language Processing (NLP) to facilitate the creation of customizable UI elements. By employing advanced machine learning techniques, the invention streamlines the generation of initial UI component designs, enhances adaptability to user requirements, and optimizes the overall UI development lifecycle.

BACKGROUND OF THE INVENTION
[0002] Background description includes information that may be useful in understanding the present invention. It is an admission that any of the information provided herein is prior art or relevant to the presently claimed invention, or that any publication specifically or implicitly referenced is prior art.
[0003] Developers and designers face significant challenges in creating user interface (UI) components that are consistent, efficient, and accessible while adhering to specific design guidelines. Traditional UI development methods require extensive manual effort, often leading to inconsistencies, inefficiencies, and accessibility gaps.
[0004] In conventional workflows, developers and designers spend considerable time manually crafting and refining UI components to meet design specifications, which can delay product development timelines. Maintaining consistency across UI components is particularly challenging in large-scale projects involving multiple teams, increasing the likelihood of deviations from established design standards. Additionally, traditional UI libraries often lack adaptability to diverse design systems, making it difficult to scale or customize components based on project-specific requirements.
[0005] Another critical limitation of existing approaches is the complex and error-prone process of integrating UI components with APIs, databases, and dynamic content. Manual linking of these components introduces inconsistencies and increases development overhead. Despite advancements in artificial intelligence (AI), the integration of Natural Language Processing (NLP) into UI generation remains underutilized, restricting intuitive and efficient UI creation through natural language-driven inputs.
[0006] Furthermore, accessibility remains a major concern, as many UI components fail to comply with established accessibility standards such as the Web Content Accessibility Guidelines (WCAG). This results in applications that are not fully inclusive, limiting their usability for individuals with disabilities.
[0007] Existing UI libraries also require substantial manual effort for customization, making the development process time-intensive and prone to errors. Developers must manually integrate data sources, APIs, and interaction logic, reducing efficiency. Many solutions lack the flexibility to align with diverse design systems, branding guidelines, or user preferences, leading to inconsistencies in adherence to organizational standards.
[0008] Collaboration between cross-functional teams, such as developers and designers, is often inefficient due to the lack of automated tools that bridge technical and creative workflows. Additionally, traditional UI libraries provide limited flexibility, offering static solutions rather than dynamic, adaptable components that can cater to multiple design preferences while maintaining functional consistency.
[0009] These challenges highlight the need for an intelligent, AI-powered solution that automates the generation of UI components, ensuring consistency, accessibility, and seamless integration with design systems. By leveraging NLP and advanced AI techniques, such a solution can enable users to create customizable UI elements more efficiently, reducing manual effort, improving collaboration, and accelerating the overall UI development lifecycle.

OBJECTS OF THE INVENTION
[0010] A primary objective of the present invention is to develop a system and method for automating the generation of user interface (UI) components, enabling developers and designers to create efficient, consistent, and high-quality user interfaces.
[0011] Another objective of the present invention is to reduce the time and effort required for UI development by automating manual tasks and optimizing the UI component creation process.
[0012] A further objective of the present invention is to enhance the consistency and quality of UI components by ensuring adherence to design systems, branding guidelines, and accessibility standards such as WCAG.
[0013] The present invention also aims to improve the flexibility and adaptability of UI development by enabling the generation of multiple design variations and supporting seamless customization.
[0014] Another objective of the present invention is to enhance the integration of UI components with dynamic data sources and functionality by automating data binding and interaction logic generation.
[0015] Additionally, the present invention seeks to empower users by enabling UI component creation through intuitive, language-driven inputs using Natural Language Processing (NLP), thereby making UI design more accessible and efficient.
[0016] These and other objects of the present invention will become readily apparent from the following detailed description taken in conjunction with the accompanying drawings.

SUMMARY OF THE INVENTION
[0017] In one aspect, the present invention provides a system for AI-assisted user interface (UI) component generation, wherein the system comprises: A Natural Language Processing (NLP) Engine configured to process user input provided via text or voice commands and extract component requirements based on linguistic analysis. A Contextual AI Engine configured to retrieve and apply design guidelines, branding specifications, and context-specific configurations to ensure compliance with predefined standards. A Component Generation Engine configured to generate multiple UI component design variations by synthesizing extracted component requirements with retrieved design guidelines, wherein the generated components include structured markup, styling definitions, and interaction logic. A Live Preview Module configured to render the generated UI component designs in real time, enabling user interaction and modification prior to finalization. An Accessibility and Responsiveness Validator configured to analyze and validate generated UI components for conformance with accessibility standards, including WCAG guidelines, and ensure responsiveness across different display environments. A Data Binding and Logic Automation Module configured to integrate UI components with dynamic data sources and automatically generate interaction logic, reducing manual coding effort.
[0018] In some embodiments, the system further comprises a Recommendation Engine configured to analyze user behaviour, historical usage patterns, and contextual requirements to suggest relevant UI components, styles, and layouts.
[0019] In another aspect, the invention provides a method for generating user interface components, the method comprising: Receiving user input in natural language and extracting component requirements using an NLP Engine. Retrieving design guidelines, branding rules, and contextual configurations using a Contextual AI Engine. Generating a plurality of UI component design options using a Component Generation Engine, wherein the generated components include HTML structure, CSS styling, and JavaScript/TypeScript interaction logic. Displaying the generated UI component design variations through a Live Preview Module and enabling real-time modifications. Validating the generated UI components for accessibility compliance and responsive adaptability using an Accessibility and Responsiveness Validator. Binding the generated UI components to data sources and automating interaction logic using a Data Binding and Logic Automation Module.
[0020] The system and method disclosed herein provide a streamlined approach to UI development, reducing manual effort, ensuring consistency in adherence to design systems, and enabling dynamic adaptation to diverse project requirements. The integration of NLP-driven UI generation facilitates an intuitive design process, while automated validation and data binding enhance usability, scalability, and accessibility.
[0021] Various objects, features, aspects and advantages of the inventive subject matter will become more apparent from the following detailed description of preferred embodiments, along with the accompanying drawing figures in which like numerals represent like components.
BRIEF DESCRIPTION OF THE DRAWINGS
[0022] The accompanying drawings are included to provide a further understanding of the present invention, and are incorporated in and constitute a part of this specification. The drawings illustrate exemplary embodiments of the present invention and, together with the description, serve to explain the principles of the present invention.
[0023] FIG. 1 illustrates the AI-based Natural Language to Custom UI Components Generator Studio.
[0024] FIG. 2 illustrates the UI Component Generation Method.
DETAILED DESCRIPTION OF THE INVENTION
[0025] The following is a detailed description of embodiments of the invention depicted in the accompanying drawings. The embodiments are in such details as to clearly communicate the invention. However, the amount of detail offered is not intended to limit the anticipated variations of embodiments; on the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the present invention as defined by the appended claims.
[0026] If the specification states a component or feature “may”, “can”, “could”, or “might” be included or have a characteristic, that particular component or feature is not required to be included or have the characteristic.
[0027] Exemplary embodiments will now be described more fully hereinafter with reference to the accompanying drawings, in which exemplary embodiments are shown. This invention may however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. These embodiments are provided so that this invention will be thorough and complete and will fully convey the scope of the invention to those of ordinary skill in the art. Moreover, all statements herein reciting embodiments of the invention, as well as specific examples thereof, are intended to encompass both structural and functional equivalents thereof. Additionally, it is intended that such equivalents include both currently known equivalents as well as equivalents developed in the future (i.e., any elements developed that perform the same function, regardless of structure).
[0028] Various terms as used herein. To the extent a term used in a claim is not defined below, it should be given the broadest definition persons in the pertinent art have given that term as reflected in printed publications and issued patents at the time of filing.
[0029] As used in the description herein and throughout the claims that follow, the meaning of “a,” “an,” and “the” includes plural reference unless the context clearly dictates otherwise. Also, as used in the description herein, the meaning of “in” includes “in” and “on” unless the context clearly dictates otherwise.
[0030] The recitation of ranges of values herein is merely intended to serve as a shorthand method of referring individually to each separate value falling within the range. Unless otherwise indicated herein, each individual value is incorporated into the specification as if it were individually recited herein. All methods described herein can be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. The use of any and all examples, or exemplary language (e.g. “such as”) provided with respect to certain embodiments herein is intended merely to better illuminate the invention and does not pose a limitation on the scope of the invention otherwise claimed. No language in the specification should be construed as indicating any non-claimed element essential to the practice of the invention.
[0031] The present invention is an intelligent system designed to streamline the creation of user interface (UI) components, particularly for individuals with varying levels of technical expertise. This system leverages the power of Natural Language Processing (NLP), Contextual Artificial Intelligence (AI), and automated processes to translate user needs, expressed in natural language, into functional and aesthetically consistent UI elements. The following description sets forth numerous specific details to provide a comprehensive understanding of the present invention. However, it will be apparent to one skilled in the art that the present invention may be practiced without these specific details. In other instances, well-known features and concepts related to UI development, AI, and software systems have not been described in detail so as not to obscure the core aspects of the invention.
[0032] The present invention pertains to a technical system for generating user interface components, which is practically realized through a combination of hardware and software components. The innovative functionalities of this system are embodied in a tangible and operational apparatus comprising computing devices and specialized software modules. These software modules, when executed by the computing devices, orchestrate the processes of natural language processing, contextual analysis, component generation, live preview, validation, and data binding as described herein. The software components may be stored on various tangible computer-readable media, including but not limited to, memory devices (e.g., RAM, ROM, flash memory), magnetic storage devices (e.g., hard disks), and optical storage devices (e.g., CD-ROMs, DVDs). The invention thus resides in the specific configuration and interaction of these hardware and software components to achieve a novel technical effect in the field of user interface development.
[0033] The core of the present invention resides in a system (100) comprising several interconnected modules that work collaboratively to generate UI components. These modules include an NLP Engine (102), a Contextual AI Engine (103), a Component Generation Engine (105), a Live Preview Module (106), a Validation Module (107), and a Data Binding and Logic Automation Module (108). In some embodiments, the system (100) further includes a Recommendation Engine (104). The interaction and functionality of these modules are detailed below.
[0034] Natural Language Processing (NLP) Engine (102)
Function: The NLP Engine (102) serves as the primary interface for users to interact with the system (100). It is configured to receive user input expressed in natural language, whether through text or voice commands. The engine employs various NLP techniques, including lexical analysis, syntactic parsing, semantic analysis, and intent recognition, to understand the user's requirements for UI components.
[0035] By processing natural language input, the NLP Engine (102) extracts key component specifications, such as the type of component needed (e.g., button, form, list), its intended functionality (e.g., submit data, display information), and any specific attributes or constraints mentioned by the user. This eliminates the need for users to possess coding skills or technical knowledge of UI development paradigms, making UI creation accessible to a broader audience, including non-programmers. The extracted component requirements are then passed on to other modules within the system for further processing.
[0036] Contextual AI Engine (103)
The Contextual AI Engine (103) is responsible for retrieving and applying relevant contextual information that influences the design and behaviour of the generated UI components. This information includes predefined design guidelines, specific branding rules (e.g., color schemes, typography), and context-specific configurations relevant to the application or the user's current project.
[0037] This engine ensures that the generated UI components are not only functional but also visually consistent with the overall application's design language and any specific requirements set forth by the user or the project. By automatically adapting components to match these contextual parameters, the Contextual AI Engine (103) eliminates the need for manual adjustments and ensures seamless integration and adherence to established standards without manual intervention.
[0038] Recommendation Engine (104)
The Recommendation Engine (104), is configured to provide intelligent suggestions to the user. These suggestions may include entire UI components, specific styles, and overall layout options. The engine bases its recommendations on an analysis of user behaviour patterns, historical usage data within the system, and the current contextual needs identified by the Contextual AI Engine (103).
[0039] By proactively suggesting relevant UI elements and design choices, the Recommendation Engine (104) aims to reduce decision fatigue for the user and accelerate the UI creation process. It can anticipate user needs based on past interactions and project context, thereby enhancing efficiency and potentially introducing users to design patterns or components they might not have considered otherwise.
[0040] Component Generation Engine (105)
[0041] The Component Generation Engine (105) is the core of the UI creation process. It takes the component requirements extracted by the NLP Engine (102) and the contextual information retrieved by the Contextual AI Engine (103) as inputs. Based on these inputs, it is configured to generate a plurality of UI component design options (as stated in claim 1. These options achieve the same functional result but may differ in their visual presentation, underlying code structure, or interaction patterns.
[0042] The Component Generation Engine (105) leverages its internal knowledge base of UI patterns, design principles, and coding best practices to produce multiple viable design alternatives. As specified in claim 5, these options typically include the underlying HTML structure for the component's content and semantics, CSS for styling its visual appearance, and JavaScript or TypeScript for implementing its interactive behaviour. By providing multiple design options, the system offers developers flexibility and enhances the potential for user experience customization.
[0043] Live Preview Module (106)
[0044] The Live Preview Module (106) is configured to display the various UI component design options generated by the Component Generation Engine (105). Crucially, it also enables real-time modifications to these generated components by the user.
[0045] This module provides instant visual feedback on the generated UI components, allowing users to see how they would appear and behave in a running application. The real-time modification capability allows for iterative design and refinement directly within the system, without the need to switch to a separate code editor or rebuild the application. Users can adjust properties, layouts, and styles and immediately see the results, facilitating a more intuitive and efficient design process.
[0046] Validation Module (107)
The Validation Module (107) is responsible for ensuring the quality and usability of the generated UI components. It is configured to automatically validate these components for compliance with accessibility standards and responsiveness across various devices and screen sizes (as mentioned in claim 1 and novel feature 6). As further specified in claim 4 and claim 11, this validation includes checking for adherence to Web Content Accessibility Guidelines (WCAG).
[0047] By performing automated validation, the system helps developers create inclusive and user-friendly interfaces. Ensuring compliance with accessibility standards makes the UI usable by individuals with disabilities, while validating responsiveness guarantees a consistent and optimal experience across different devices, from desktops to mobile phones. This built-in validation reduces the risk of accessibility issues and layout problems that might otherwise require manual testing and debugging.
[0048] Data Binding and Logic Automation Module (108)
[0049] The Data Binding and Logic Automation Module (108) is configured to connect the generated UI components to relevant data sources and to automatically generate the necessary interaction logic. As specified in claim 7, this includes automatically binding the UI components to data sources, Application Programming Interfaces (APIs), and backend systems.
[0050] This module significantly simplifies the process of making UI components dynamic and interactive. By automating the binding of UI elements to data and generating common interaction patterns, it reduces the amount of manual coding required. This allows developers to focus on the higher-level application logic rather than the boilerplate code for data synchronization and basic UI interactions. The ability to bind to various data sources and generate interaction logic without manual coding is a key novel aspect of the present invention.
[0051] Step-by-Step Workflow of the Invention (Method 200)
[0052] The present invention also encompasses a method (200) for generating UI components, which outlines the sequence of operations performed by the system (100). This method comprises the following steps:
[0053] Receiving User Input and Extracting Component Requirements (202): This initial step involves the NLP Engine (102) receiving user input in natural language (as per claim 8). As detailed in claim 10, this input can be provided via text or voice commands (201). The NLP Engine then processes this input to understand the user's intent and extract the specific requirements for the desired UI component.
[0054] Retrieving Design Guidelines and Context (203): In this step, the Contextual AI Engine (103) retrieves relevant information necessary for generating contextually appropriate UI components (as per claim 8). This includes design guidelines, branding rules, and any other context-specific configurations that may be applicable to the current project or user. Claim 9 further specifies that the Recommendation Engine (104) may also contribute in this stage by suggesting UI components, styles, and layouts based on user behaviour, historical usage, and contextual needs.
[0055] Generating UI Component Design Options (204): Based on the extracted component requirements and the retrieved design guidelines, the Component Generation Engine (105) generates a plurality of UI component design options (as per claim 8). These options, as previously described, offer different ways to achieve the same functional outcome, providing the user with choices in terms of visual appearance and underlying implementation.
[0056] Displaying and Modifying UI Components (205): The Live Preview Module (106) then displays the generated UI component design options to the user (as per claim 8). Critically, this module allows the user to make real-time modifications to these components directly within the preview environment, providing immediate visual feedback on their changes.
[0057] Validating Generated UI Components (206): The Validation Module (107) automatically validates the generated UI components (as per claim 8). This validation process checks for compliance with accessibility standards and ensures that the components are responsive across various devices. As specified in claim 11, this includes validating the components for adherence to WCAG guidelines.
[0058] Binding Data and Automating Logic (207): Finally, the Data Binding and Logic Automation Module (108) takes the validated UI components and automatically binds them to specified data sources and generates the necessary interaction logic (as per claim 8). This step connects the UI components to the application's data and enables them to respond to user interactions without requiring manual coding of these functionalities.
[0059] The foregoing description of the specific embodiments will so fully reveal the general nature of the embodiments herein that others can, by applying current knowledge, readily modify and/or adapt for various applications such specific embodiments without departing from the generic concept, and, therefore, such adaptations and modifications should and are intended to be comprehended within the meaning and range of equivalents of the disclosed embodiments. It is to be understood that the phraseology or terminology employed herein is for the purpose of description and not of limitation. Therefore, while the embodiments herein have been described in terms of preferred embodiments, those skilled in the art will recognize that the embodiments herein can be practiced with modification within the spirit and scope of the appended claims.
[0060] While the foregoing describes various embodiments of the invention, other and further embodiments of the invention may be devised without departing from the basic scope thereof. The scope of the invention is determined by the claims that follow. The invention is not limited to the described embodiments, versions or examples, which are included to enable a person having ordinary skill in the art to make and use the invention when combined with information and knowledge available to the person having ordinary skill in the art.
TECHNICAL ADVANTAGES
[0061] The present invention provides a system and method for generating user interface (UI) components that offer significant advantages over existing approaches, including but not limited to the following:
[0062] Accelerated UI Development: AI-driven automation significantly reduces manual coding and design efforts, leading to faster UI creation and deployment.
[0063] Automated Design Consistency: Enforces adherence to design systems and branding across all components, eliminating manual inconsistencies.
[0064] Dynamic Scalability and Customization: AI-powered adaptation enables flexible component scaling and customization to various design needs without extensive manual work.
[0065] Simplified Data and Interaction Integration: Automates the binding of UI components to data sources and the generation of interaction logic, reducing integration complexity.
[0066] Empowered Non-Technical UI Creation: Natural language processing allows users without coding skills to create and modify UI components intuitively.
[0067] Built-in Accessibility Compliance: Ensures all generated components automatically meet WCAG standards for inclusive design.
[0068] Streamlined Collaboration: Facilitates efficient workflows between designers and developers through automation and intuitive input methods.
[0069] Intelligent Design Assistance: AI recommendations guide component selection and layout, reducing decision fatigue and improving design quality.
[0070] Rapid Iteration with Real-Time Feedback: Live previews enable immediate visualization and refinement of UI components, accelerating the design iteration process.

, Claims:We claim:
1. A system (100) for generating user interface (UI) components, the system comprising:
an NLP Engine (102) configured to receive user input in natural language and extract component requirements;
a Contextual AI Engine (103) configured to retrieve design guidelines, branding rules, and context-specific configurations;
a Component Generation Engine (105) configured to generate a plurality of UI component design options based on the extracted component requirements;
a Live Preview Module (106) configured to display the generated UI component design options and enable real-time modifications by the user;
a Validation Module (107) configured to validate the generated UI components for compliance with accessibility standards and responsiveness across devices; and
a Data Binding and Logic Automation Module (108) configured to bind the generated UI components to data sources and generate interaction logic.

2. The system (100) as claimed in claim 1, further comprising:
a Recommendation Engine (104) configured to suggest UI components, styles, and layouts based on user behaviour, historical usage, and contextual needs.

3. The system (100) of claim 1, wherein the NLP Engine (102) is further configured to:
process user input provided via text or voice commands.
4. The system (100) as claimed in claim 1, wherein the Validation Module (107) is further configured to:
validate the generated UI components for compliance with WCAG guidelines.
5. The system (100) as claimed in claim 1, wherein the Component Generation Engine (105) is configured to generate the plurality of UI component design options, including:
HTML structure;
CSS for styling; and
JavaScript/TypeScript for interaction logic.

6. The system (100) as claimed in claim 1, wherein the Live Preview Module (106) is configured to:
enable real-time adjustments to the generated UI components by the user.

7. The system (100) as claimed in claim 1, wherein the Data Binding and Logic Automation Module (108) is configured to:
automatically bind the generated UI components to data sources, APIs, and backend systems.

8. The system (100) as claimed in claim 1, further comprising:
an AI-driven recommendation engine (104) configured to suggest components, styles, and layouts based on user behaviour, historical usage, and contextual needs.

9. The system (100) as claimed in claim 1, wherein the system (100) is configured to:
dynamically adapt to any chosen design guidelines, themes, and branding requirements, ensuring seamless integration and adherence without manual intervention.

10. The system (100) as claimed in claim 1, wherein the system (100) is configured to:
provide multiple design options for achieving the same functional result, giving developers flexibility and enhancing user experience customization.

11. The system (100) as claimed in claim 1, wherein the Natural Language Processing (NLP) Engine (102) is configured to:
enable users (101) to create user interface components by describing their requirements in natural language, eliminating the need for coding or technical knowledge.

12. A method (200) for generating user interface (UI) components, comprising:
receiving user input in natural language and extracting component requirements (202) using an NLP engine (102);
retrieving design guidelines, branding rules, and context-specific configurations (203) using a Contextual AI engine (103);
generating a plurality of UI component design options based on the extracted component requirements and the retrieved design guidelines (204) using a Component Generation Engine (105);
displaying the generated UI component design options and enabling real-time modifications by the user through a Live Preview Module (205);
validating the generated UI components for compliance with accessibility standards and responsiveness across devices (206) using a Validation Module (107); and
binding the generated UI components to data sources and generating interaction logic (207) using a Data Binding and Logic Automation Module (108).

13. The method (200) as claimed in claim 12, further comprising:
suggesting UI components, styles, and layouts based on user behaviour, historical usage, and contextual needs (203) using a Recommendation Engine (104).

14. The method (200) as claimed in claim 12, wherein receiving user input in natural language comprises:
processing input provided via text or voice commands (201).

15. The method (200) as claimed in claim 12, wherein validating the generated UI components comprises:
validating the generated UI components for compliance with WCAG guidelines (206).

Dated this 15th June, 2025