Crafting CodeAnt AI VS Code Extension
Crafting CodeAnt AI VS Code Extension
Internship Work | B2B SAAS Product | Developer Tool
Internship Work | B2B SAAS Product | Developer Tool
CASE STUDY COVER IMAGE
CASE STUDY COVER IMAGE
My Role
My Role
Research, Interaction Design, Prototyping, UI Design
Research, Interaction Design, Prototyping, UI Design
Research, Interaction Design, User Flows, Wireframing, UI Design, Prototype
Research, Interaction Design, Prototyping, UI Design
Team
Team
1 Designers, 1 Manager and 2 Developers
1 Designers, 1 Manager and 2 Developers
1 Designers, 1 Manager and 2 Developers
Timeline
Timeline
1 July 2024 - 15 July 2024
1 July 2024 - 15 July 2024
1 July 2024 - 15 July 2024
Overview
Overview
CodeAnt AI is a DevTool that helps companies find and auto-fix code issues and security vulnerabilities. CodeAnt helps enforce code governance and custom best practices throughout the development life cycle and integrate from IDEs to Pull Requests.
CodeAnt AI is a DevTool that helps companies find and auto-fix code issues and security vulnerabilities. CodeAnt helps enforce code governance and custom best practices throughout the development life cycle and integrate from IDEs to Pull Requests.
CodeAnt AI is a DevTool that helps companies find and auto-fix code issues and security vulnerabilities. CodeAnt helps enforce code governance and custom best practices throughout the development life cycle and integrate from IDEs to Pull Requests.
CodeAnt AI is a DevTool that helps companies find and auto-fix code issues and security vulnerabilities. CodeAnt helps enforce code governance and custom best practices throughout the development life cycle and integrate from IDEs to Pull Requests.
At Code Ant AI, our primary focus is on developing cutting-edge AI-driven solutions to streamline and enhance various aspects of software development. Among our innovative products, we designed the CodeAnt AI VS Code extension, an auxiliary tool aimed at helping developers maintain clean, optimized, and readable code effortlessly. This case study details the research, design, and implementation processes behind CodeAnt AI, reflecting our commitment to improving developer productivity and code quality.
At Code Ant AI, our primary focus is on developing cutting-edge AI-driven solutions to streamline and enhance various aspects of software development. Among our innovative products, we designed the CodeAnt AI VS Code extension, an auxiliary tool aimed at helping developers maintain clean, optimized, and readable code effortlessly. This case study details the research, design, and implementation processes behind CodeAnt AI, reflecting our commitment to improving developer productivity and code quality.
At Code Ant AI, our primary focus is on developing cutting-edge AI-driven solutions to streamline and enhance various aspects of software development. Among our innovative products, we designed the CodeAnt AI VS Code extension, an auxiliary tool aimed at helping developers maintain clean, optimized, and readable code effortlessly. This case study details the research, design, and implementation processes behind CodeAnt AI, reflecting our commitment to improving developer productivity and code quality.
At Code Ant AI, our primary focus is on developing cutting-edge AI-driven solutions to streamline and enhance various aspects of software development. Among our innovative products, we designed the CodeAnt AI VS Code extension, an auxiliary tool aimed at helping developers maintain clean, optimized, and readable code effortlessly. This case study details the research, design, and implementation processes behind CodeAnt AI, reflecting our commitment to improving developer productivity and code quality.
What Exactly was the Problem
What Exactly was the Problem
In the modern software development landscape, developers often face significant challenges related to code quality and maintainability. These challenges include:
In the modern software development landscape, developers often face significant challenges related to code quality and maintainability. These challenges include:
In the modern software development landscape, developers often face significant challenges related to code quality and maintainability. These challenges include:
In the modern software development landscape, developers often face significant challenges related to code quality and maintainability. These challenges include:
Code Efficiency: Writing code that is not only functional but also efficient and optimized.
Code Readability: Ensuring that code is easily understandable by other developers, which is critical for collaboration and future maintenance.
Documentation: Maintaining comprehensive and up-to-date documentation to assist in understanding and using the codebase.
Testing: Creating extensive and effective test cases to ensure code reliability and robustness.
Code Smells: Identifying and correcting common issues that can degrade code quality over time.
Type Safety: Incorporating accurate type hints to reduce errors and improve code readability, especially in dynamically-typed languages like Python.
Code Efficiency: Writing code that is not only functional but also efficient and optimized.
Code Readability: Ensuring that code is easily understandable by other developers, which is critical for collaboration and future maintenance.
Documentation: Maintaining comprehensive and up-to-date documentation to assist in understanding and using the codebase.
Testing: Creating extensive and effective test cases to ensure code reliability and robustness.
Code Smells: Identifying and correcting common issues that can degrade code quality over time.
Type Safety: Incorporating accurate type hints to reduce errors and improve code readability, especially in dynamically-typed languages like Python.
Code Efficiency: Writing code that is not only functional but also efficient and optimized.
Code Readability: Ensuring that code is easily understandable by other developers, which is critical for collaboration and future maintenance.
Documentation: Maintaining comprehensive and up-to-date documentation to assist in understanding and using the codebase.
Testing: Creating extensive and effective test cases to ensure code reliability and robustness.
Code Smells: Identifying and correcting common issues that can degrade code quality over time.
Type Safety: Incorporating accurate type hints to reduce errors and improve code readability, especially in dynamically-typed languages like Python.
Code Efficiency: Writing code that is not only functional but also efficient and optimized.
Code Readability: Ensuring that code is easily understandable by other developers, which is critical for collaboration and future maintenance.
Documentation: Maintaining comprehensive and up-to-date documentation to assist in understanding and using the codebase.
Testing: Creating extensive and effective test cases to ensure code reliability and robustness.
Code Smells: Identifying and correcting common issues that can degrade code quality over time.
Type Safety: Incorporating accurate type hints to reduce errors and improve code readability, especially in dynamically-typed languages like Python.
These challenges often result in increased time spent on fixing and cleaning up code rather than focusing on new logic and features. CodeAnt AI was designed to address these pain points, providing developers with tools to enforce clean code, optimize performance, and maintain high standards of code quality effortlessly.
These challenges often result in increased time spent on fixing and cleaning up code rather than focusing on new logic and features. CodeAnt AI was designed to address these pain points, providing developers with tools to enforce clean code, optimize performance, and maintain high standards of code quality effortlessly.
These challenges often result in increased time spent on fixing and cleaning up code rather than focusing on new logic and features. CodeAnt AI was designed to address these pain points, providing developers with tools to enforce clean code, optimize performance, and maintain high standards of code quality effortlessly.
These challenges often result in increased time spent on fixing and cleaning up code rather than focusing on new logic and features. CodeAnt AI was designed to address these pain points, providing developers with tools to enforce clean code, optimize performance, and maintain high standards of code quality effortlessly.
Target User
Target User
The primary users of CodeAnt AI are software developers and engineers who use VS Code as their integrated development environment. These users range from junior developers to senior engineers and technical leads who require efficient tools to maintain high code quality and productivity. They value tools that integrate seamlessly into their workflow and provide actionable insights without disrupting their coding process.
The primary users of CodeAnt AI are software developers and engineers who use VS Code as their integrated development environment. These users range from junior developers to senior engineers and technical leads who require efficient tools to maintain high code quality and productivity. They value tools that integrate seamlessly into their workflow and provide actionable insights without disrupting their coding process.
The primary users of CodeAnt AI are software developers and engineers who use VS Code as their integrated development environment. These users range from junior developers to senior engineers and technical leads who require efficient tools to maintain high code quality and productivity. They value tools that integrate seamlessly into their workflow and provide actionable insights without disrupting their coding process.
The primary users of CodeAnt AI are software developers and engineers who use VS Code as their integrated development environment. These users range from junior developers to senior engineers and technical leads who require efficient tools to maintain high code quality and productivity. They value tools that integrate seamlessly into their workflow and provide actionable insights without disrupting their coding process.
Research
Research
To build an effective and user-friendly extension, extensive secondary research was conducted. This involved studying various aspects of code quality management, documentation practices, and testing methodologies. Key areas of research included:
To build an effective and user-friendly extension, extensive secondary research was conducted. This involved studying various aspects of code quality management, documentation practices, and testing methodologies. Key areas of research included:
To build an effective and user-friendly extension, extensive secondary research was conducted. This involved studying various aspects of code quality management, documentation practices, and testing methodologies. Key areas of research included:
To build an effective and user-friendly extension, extensive secondary research was conducted. This involved studying various aspects of code quality management, documentation practices, and testing methodologies. Key areas of research included:
Market Trends
Market Trends
Code Quality Importance: High-quality, maintainable code is essential for long-term project success and developer productivity.
Tool Integration: Strong preference for tools that integrate seamlessly with development environments like VS Code.
AI and Automation: AI-driven tools that automate tasks such as code reviews and documentation are increasingly popular.
Code Quality Importance: High-quality, maintainable code is essential for long-term project success and developer productivity.
Tool Integration: Strong preference for tools that integrate seamlessly with development environments like VS Code.
AI and Automation: AI-driven tools that automate tasks such as code reviews and documentation are increasingly popular.
Code Quality Importance: High-quality, maintainable code is essential for long-term project success and developer productivity.
Tool Integration: Strong preference for tools that integrate seamlessly with development environments like VS Code.
AI and Automation: AI-driven tools that automate tasks such as code reviews and documentation are increasingly popular.
Code Quality Importance: High-quality, maintainable code is essential for long-term project success and developer productivity.
Tool Integration: Strong preference for tools that integrate seamlessly with development environments like VS Code.
AI and Automation: AI-driven tools that automate tasks such as code reviews and documentation are increasingly popular.
User Needs
User Needs
Real-Time Feedback: Developers prefer tools that provide immediate, non-disruptive feedback and suggestions.
Ease of Use: Simple, intuitive interfaces and functionalities are highly valued.
Comprehensive Features: Preference for tools offering a range of features, such as code optimization, documentation generation, and test case creation.
Privacy and Security: Strong emphasis on privacy and data security, with a preference for tools that do not store or share user code.
Real-Time Feedback: Developers prefer tools that provide immediate, non-disruptive feedback and suggestions.
Ease of Use: Simple, intuitive interfaces and functionalities are highly valued.
Comprehensive Features: Preference for tools offering a range of features, such as code optimization, documentation generation, and test case creation.
Privacy and Security: Strong emphasis on privacy and data security, with a preference for tools that do not store or share user code.
Real-Time Feedback: Developers prefer tools that provide immediate, non-disruptive feedback and suggestions.
Ease of Use: Simple, intuitive interfaces and functionalities are highly valued.
Comprehensive Features: Preference for tools offering a range of features, such as code optimization, documentation generation, and test case creation.
Privacy and Security: Strong emphasis on privacy and data security, with a preference for tools that do not store or share user code.
Real-Time Feedback: Developers prefer tools that provide immediate, non-disruptive feedback and suggestions.
Ease of Use: Simple, intuitive interfaces and functionalities are highly valued.
Comprehensive Features: Preference for tools offering a range of features, such as code optimization, documentation generation, and test case creation.
Privacy and Security: Strong emphasis on privacy and data security, with a preference for tools that do not store or share user code.
Developer Challenges
Developer Challenges
Code Complexity: Managing complex codebases and maintaining their quality over time.
Documentation: Keeping code documentation up-to-date and consistent.
Test Coverage: Ensuring comprehensive test coverage, including edge cases.
Code Smells: Identifying and fixing common code smells to enhance code maintainability.
Code Complexity: Managing complex codebases and maintaining their quality over time.
Documentation: Keeping code documentation up-to-date and consistent.
Test Coverage: Ensuring comprehensive test coverage, including edge cases.
Code Smells: Identifying and fixing common code smells to enhance code maintainability.
Code Complexity: Managing complex codebases and maintaining their quality over time.
Documentation: Keeping code documentation up-to-date and consistent.
Test Coverage: Ensuring comprehensive test coverage, including edge cases.
Code Smells: Identifying and fixing common code smells to enhance code maintainability.
Code Complexity: Managing complex codebases and maintaining their quality over time.
Documentation: Keeping code documentation up-to-date and consistent.
Test Coverage: Ensuring comprehensive test coverage, including edge cases.
Code Smells: Identifying and fixing common code smells to enhance code maintainability.
Competitor Analysis
Competitor Analysis
Codiumate: Offers real-time suggestions and code smells detection but lacks comprehensive features and has performance issues.
Codeium: Strong VS Code integration and positive user feedback but limited in features and privacy measures.
Codiumate: Offers real-time suggestions and code smells detection but lacks comprehensive features and has performance issues.
Codeium: Strong VS Code integration and positive user feedback but limited in features and privacy measures.
Codiumate: Offers real-time suggestions and code smells detection but lacks comprehensive features and has performance issues.
Codeium: Strong VS Code integration and positive user feedback but limited in features and privacy measures.
Codiumate: Offers real-time suggestions and code smells detection but lacks comprehensive features and has performance issues.
Codeium: Strong VS Code integration and positive user feedback but limited in features and privacy measures.
Reading VS Code Guidelines
Reading VS Code Guidelines
A critical aspect of the design process was adhering to the official guidelines for building VS Code extensions. This ensured that the UI and functionality of CodeAnt AI were intuitive, consistent, and seamlessly integrated with the VS Code environment. Key considerations included:
A critical aspect of the design process was adhering to the official guidelines for building VS Code extensions. This ensured that the UI and functionality of CodeAnt AI were intuitive, consistent, and seamlessly integrated with the VS Code environment. Key considerations included:
A critical aspect of the design process was adhering to the official guidelines for building VS Code extensions. This ensured that the UI and functionality of CodeAnt AI were intuitive, consistent, and seamlessly integrated with the VS Code environment. Key considerations included:
A critical aspect of the design process was adhering to the official guidelines for building VS Code extensions. This ensured that the UI and functionality of CodeAnt AI were intuitive, consistent, and seamlessly integrated with the VS Code environment. Key considerations included:
UI Consistency: Ensuring that the extension's UI elements matched the look and feel of VS Code.
Accessibility: Designing the extension to be accessible to all users, including those with disabilities.
Performance: Optimizing the extension to ensure it did not negatively impact the performance of VS Code.
UI Consistency: Ensuring that the extension's UI elements matched the look and feel of VS Code.
Accessibility: Designing the extension to be accessible to all users, including those with disabilities.
Performance: Optimizing the extension to ensure it did not negatively impact the performance of VS Code.
UI Consistency: Ensuring that the extension's UI elements matched the look and feel of VS Code.
Accessibility: Designing the extension to be accessible to all users, including those with disabilities.
Performance: Optimizing the extension to ensure it did not negatively impact the performance of VS Code.
UI Consistency: Ensuring that the extension's UI elements matched the look and feel of VS Code.
Accessibility: Designing the extension to be accessible to all users, including those with disabilities.
Performance: Optimizing the extension to ensure it did not negatively impact the performance of VS Code.
Solutioning
Solutioning
Based on the research insights and guidelines, the solutioning phase focused on creating a comprehensive design that addressed the identified challenges.
Based on the research insights and guidelines, the solutioning phase focused on creating a comprehensive design that addressed the identified challenges.
Based on the research insights and guidelines, the solutioning phase focused on creating a comprehensive design that addressed the identified challenges.
Based on the research insights and guidelines, the solutioning phase focused on creating a comprehensive design that addressed the identified challenges.
Inline Suggestions: Receive real-time suggestions for enhancing code efficiency as you write.
Summary Insights: Get concise explanations of issues within the current code directly in your workflow.
One-Click Fixes: Instantly correct identified anti-patterns with a single click.
Docstring Generation: Customize the style of your docstrings and generate them with a single click. Test
Test Cases Generation: Generate comprehensive test cases, including edge-case scenarios, quickly and efficiently.
Code Smells Removal: Enhance code readability, maintainability, and efficiency with quick fixes.
Type Hints Generation: Automatically generate accurate type hints for Python with a single click.
Inline Suggestions: Receive real-time suggestions for enhancing code efficiency as you write.
Summary Insights: Get concise explanations of issues within the current code directly in your workflow.
One-Click Fixes: Instantly correct identified anti-patterns with a single click.
Docstring Generation: Customize the style of your docstrings and generate them with a single click. Test
Test Cases Generation: Generate comprehensive test cases, including edge-case scenarios, quickly and efficiently.
Code Smells Removal: Enhance code readability, maintainability, and efficiency with quick fixes.
Type Hints Generation: Automatically generate accurate type hints for Python with a single click.
Inline Suggestions: Receive real-time suggestions for enhancing code efficiency as you write.
Summary Insights: Get concise explanations of issues within the current code directly in your workflow.
One-Click Fixes: Instantly correct identified anti-patterns with a single click.
Docstring Generation: Customize the style of your docstrings and generate them with a single click. Test
Test Cases Generation: Generate comprehensive test cases, including edge-case scenarios, quickly and efficiently.
Code Smells Removal: Enhance code readability, maintainability, and efficiency with quick fixes.
Type Hints Generation: Automatically generate accurate type hints for Python with a single click.
Inline Suggestions: Receive real-time suggestions for enhancing code efficiency as you write.
Summary Insights: Get concise explanations of issues within the current code directly in your workflow.
One-Click Fixes: Instantly correct identified anti-patterns with a single click.
Docstring Generation: Customize the style of your docstrings and generate them with a single click. Test
Test Cases Generation: Generate comprehensive test cases, including edge-case scenarios, quickly and efficiently.
Code Smells Removal: Enhance code readability, maintainability, and efficiency with quick fixes.
Type Hints Generation: Automatically generate accurate type hints for Python with a single click.
Inline Suggestions
Inline Suggestions
Inline suggestions are one of the core features of CodeAnt AI. As developers write code, the extension provides real-time suggestions to enhance code efficiency and quality. These suggestions appear inline, seamlessly integrating into the developer's workflow without causing interruptions.
Inline suggestions are one of the core features of CodeAnt AI. As developers write code, the extension provides real-time suggestions to enhance code efficiency and quality. These suggestions appear inline, seamlessly integrating into the developer's workflow without causing interruptions.
Inline suggestions are one of the core features of CodeAnt AI. As developers write code, the extension provides real-time suggestions to enhance code efficiency and quality. These suggestions appear inline, seamlessly integrating into the developer's workflow without causing interruptions.
Inline suggestions are one of the core features of CodeAnt AI. As developers write code, the extension provides real-time suggestions to enhance code efficiency and quality. These suggestions appear inline, seamlessly integrating into the developer's workflow without causing interruptions.
Inline Suggestion
Inline Suggestion
Summary Insights
Summary Insights
Summary insights offer concise explanations of issues within the current code, helping developers understand and resolve problems quickly. This feature integrates directly into the workflow, providing valuable insights without requiring developers to leave their IDE.
Summary insights offer concise explanations of issues within the current code, helping developers understand and resolve problems quickly. This feature integrates directly into the workflow, providing valuable insights without requiring developers to leave their IDE.
Summary insights offer concise explanations of issues within the current code, helping developers understand and resolve problems quickly. This feature integrates directly into the workflow, providing valuable insights without requiring developers to leave their IDE.
Summary insights offer concise explanations of issues within the current code, helping developers understand and resolve problems quickly. This feature integrates directly into the workflow, providing valuable insights without requiring developers to leave their IDE.
Summary Insights
Summary Insights
Home Page
Home Page
Paste your function and enhance code quality with CodeAnt AI. Generate test cases, docstrings, fix code smells, and add type hints—all with just a few clicks.
Paste your function and enhance code quality with CodeAnt AI. Generate test cases, docstrings, fix code smells, and add type hints—all with just a few clicks.
Paste your function and enhance code quality with CodeAnt AI. Generate test cases, docstrings, fix code smells, and add type hints—all with just a few clicks.
Paste your function and enhance code quality with CodeAnt AI. Generate test cases, docstrings, fix code smells, and add type hints—all with just a few clicks.
Home Page
Home Page
Test Cases Generation
Test Cases Generation
Test case generation provides comprehensive coverage, including both standard and edge-case scenarios. This feature allows developers to quickly create multiple test cases tailored to specific requirements, enhancing code reliability and robustness.
Test case generation provides comprehensive coverage, including both standard and edge-case scenarios. This feature allows developers to quickly create multiple test cases tailored to specific requirements, enhancing code reliability and robustness.
Test case generation provides comprehensive coverage, including both standard and edge-case scenarios. This feature allows developers to quickly create multiple test cases tailored to specific requirements, enhancing code reliability and robustness.
Test case generation provides comprehensive coverage, including both standard and edge-case scenarios. This feature allows developers to quickly create multiple test cases tailored to specific requirements, enhancing code reliability and robustness.
Test Case Generator
Test Case Generator
Docstring Generation
Docstring Generation
Docstring generation helps developers maintain comprehensive and consistent documentation for their code. This feature allows customization of docstring styles and context-sensitive generation, ensuring that docstrings are relevant and accurate.
Docstring generation helps developers maintain comprehensive and consistent documentation for their code. This feature allows customization of docstring styles and context-sensitive generation, ensuring that docstrings are relevant and accurate.
Docstring generation helps developers maintain comprehensive and consistent documentation for their code. This feature allows customization of docstring styles and context-sensitive generation, ensuring that docstrings are relevant and accurate.
Docstring generation helps developers maintain comprehensive and consistent documentation for their code. This feature allows customization of docstring styles and context-sensitive generation, ensuring that docstrings are relevant and accurate.
Docstring Generation
Docstring Generation
Code Smells Removal
Code Smells Removal
Code smells removal focuses on enhancing code readability, maintainability, and efficiency. This feature identifies and corrects common code smells, ensuring that the codebase remains clean and efficient.
Code smells removal focuses on enhancing code readability, maintainability, and efficiency. This feature identifies and corrects common code smells, ensuring that the codebase remains clean and efficient.
Code smells removal focuses on enhancing code readability, maintainability, and efficiency. This feature identifies and corrects common code smells, ensuring that the codebase remains clean and efficient.
Code smells removal focuses on enhancing code readability, maintainability, and efficiency. This feature identifies and corrects common code smells, ensuring that the codebase remains clean and efficient.
COde Smell Remover
COde Smell Remover
Type Hints Generation
Type Hints Generation
Type hints generation automatically creates accurate type hints for Python code. This feature helps improve code readability and reduces the likelihood of type-related errors, enhancing overall code quality.
Type hints generation automatically creates accurate type hints for Python code. This feature helps improve code readability and reduces the likelihood of type-related errors, enhancing overall code quality.
Type hints generation automatically creates accurate type hints for Python code. This feature helps improve code readability and reduces the likelihood of type-related errors, enhancing overall code quality.
Type hints generation automatically creates accurate type hints for Python code. This feature helps improve code readability and reduces the likelihood of type-related errors, enhancing overall code quality.
Type Hints Generator
Type Hints Generator
How to Use
How to Use
First-time users receive comprehensive guidance through a detailed video tutorial and thorough text documentation, ensuring a smooth onboarding experience and quick understanding of CodeAnt AI's features and functionalities.
First-time users receive comprehensive guidance through a detailed video tutorial and thorough text documentation, ensuring a smooth onboarding experience and quick understanding of CodeAnt AI's features and functionalities.
First-time users receive comprehensive guidance through a detailed video tutorial and thorough text documentation, ensuring a smooth onboarding experience and quick understanding of CodeAnt AI's features and functionalities.
First-time users receive comprehensive guidance through a detailed video tutorial and thorough text documentation, ensuring a smooth onboarding experience and quick understanding of CodeAnt AI's features and functionalities.
How to Use Page
How to Use Page
Settings Page
Settings Page
Users can customize docstring formats and disable the extension via the settings page for a tailored and flexible experience with CodeAnt AI.
Users can customize docstring formats and disable the extension via the settings page for a tailored and flexible experience with CodeAnt AI.
Users can customize docstring formats and disable the extension via the settings page for a tailored and flexible experience with CodeAnt AI.
Users can customize docstring formats and disable the extension via the settings page for a tailored and flexible experience with CodeAnt AI.
Settings Page
Settings Page
Outcome
Outcome
Achieved over 3K downloads on VS Code Marketplace.
Maintains a 5-star rating from users.
Positive feedback from developers who love the product.
Achieved over 3K downloads on VS Code Marketplace.
Maintains a 5-star rating from users.
Positive feedback from developers who love the product.
Achieved over 3K downloads on VS Code Marketplace.
Maintains a 5-star rating from users.
Positive feedback from developers who love the product.
Achieved over 3K downloads on VS Code Marketplace.
Maintains a 5-star rating from users.
Positive feedback from developers who love the product.
More Work
More Work
More Work
More Work
Hackathon
Mobile App
Adobe Designathon Runner up
Adobe Designathon Runner up
Adobe Designathon Runnerup
Adobe Designathon Runner up
Second Rank in Adobe Designathon. I designed UX for an app enhancing visitor experience in botanical gardens through interactive guides.
Second Rank in Adobe Designathon. I designed UX for an app enhancing visitor experience in botanical gardens through interactive guides.
Second Rank in Adobe Designathon. I designed UX for an app enhancing visitor experience in botanical gardens through interactive guides.
Second Rank in Adobe Designathon. I designed UX for an app enhancing visitor experience in botanical gardens through interactive guides.
Internship
Fintech B2B
xPay Design System
xPay Design System
xPay Design System
Established a design system for xPay, improving design-to-dev handoff by 25%, enhancing efficiency and consistency.
Established a design system for xPay, improving design-to-dev handoff by 25%, enhancing efficiency and consistency.
Established a design system for xPay, improving design-to-dev handoff by 25%, enhancing efficiency and consistency.
Established a design system for xPay, improving design-to-dev handoff by 25%, enhancing efficiency and consistency.
