Formation - Drag Drop and AI Copilot
Formation - Drag Drop and AI Copilot
Effortlessly build and backtest trading algorithms without writing code.
Effortlessly build and backtest trading algorithms without writing code.
Formation
Formation
Client
Client
UI/UX Design, UX Research
UI/UX Design, UX Research
Services
Services
2024
2024
Year
Year
Overview
Overview
Traditional algorithmic trading requires technical and financial expertise, making it inaccessible and expensive for many aspiring traders. Additionally, manual trading is time-consuming and prone to human error, limiting efficiency.
A no-code algorithmic trading platform democratizes access by enabling users to create and implement automated strategies without technical knowledge.
Designed to simplify complex trading strategy creation, the AI Copilot offers personalized guidance, helping users refine their strategies using natural language input. Meanwhile, the drag-and-drop interface allows users of all skill levels to visually build and customize trading algorithms effortlessly. This solution bridges the gap between experienced traders and beginners, enabling seamless strategy execution with minimal technical barriers.
Traditional algorithmic trading requires technical and financial expertise, making it inaccessible and expensive for many aspiring traders. Additionally, manual trading is time-consuming and prone to human error, limiting efficiency.
A no-code algorithmic trading platform democratizes access by enabling users to create and implement automated strategies without technical knowledge.
Designed to simplify complex trading strategy creation, the AI Copilot offers personalized guidance, helping users refine their strategies using natural language input. Meanwhile, the drag-and-drop interface allows users of all skill levels to visually build and customize trading algorithms effortlessly. This solution bridges the gap between experienced traders and beginners, enabling seamless strategy execution with minimal technical barriers.
Key Features Designed
Key Features Designed
Drag & Drop Canvas - A simple canvas that lets users create and customize trading strategies by arranging blocks, making algorithmic trading intuitive and accessible for everyone.
AI Copilot - An intelligent assistant that simplifies trading by offering personalized guidance, natural language strategy creation, and real-time insights to empower users at every skill level.
Drag & Drop Canvas - A simple canvas that lets users create and customize trading strategies by arranging blocks, making algorithmic trading intuitive and accessible for everyone.
AI Copilot - An intelligent assistant that simplifies trading by offering personalized guidance, natural language strategy creation, and real-time insights to empower users at every skill level.
Design Goals
Design Goals
Focus on making complex trading actions and key actions like strategy making as simple as possible for traders/users of different levels.
Create a minimalistic design which enhances intuitiveness for the user.
Focus on making complex trading actions and key actions like strategy making as simple as possible for traders/users of different levels.
Create a minimalistic design which enhances intuitiveness for the user.
Drag Drop Canvas - Key Features
Drag Drop Canvas - Key Features
Intuitive Design: A user-friendly interface that resembles building blocks or flowcharts.
Pre-Configured Blocks: Includes ready-to-use blocks like Assets, Shapes, Weight, If/Else Conditions and Sort/Filter.
Error Detection: Highlights logical errors in the strategy flow to prevent invalid configurations.
Save and Publish: Save as Drafts to be able to reuse them or publish them to the community for public access.
Cross-Device Compatibility: Works seamlessly on desktops, tablets, and mobile devices.
AI Assistant for Drag Drop Strategy
AI Assistant for Drag Drop Strategy
Automatically get suggestions, improvements or optimizations using AI assistant action buttons like Create Sequence, Replace, Refine, and Fill Up.
Automatically get suggestions, improvements or optimizations using AI assistant action buttons like Create Sequence, Replace, Refine, and Fill Up.
AI Copilot - Key Features
AI Copilot - Key Features
Natural Language Understanding: Users can interact with the AI using simple conversational text.
Context-Aware Suggestions: The AI understands the user’s actions and provides relevant, actionable tips.
Pre-Configured Action Buttons: Includes ready-to-use action buttons like Generate, Debug, Refine, and Replace.
Cross-Device Compatibility: Works seamlessly on desktops, tablets, and mobile devices.
Mobile Responsiveness
Mobile Responsiveness
The platform is designed to offer a seamless experience across all devices.
The platform is designed to offer a seamless experience across all devices.
Lessons Learned
Lessons Learned
Mistakes were made in the early stages of the design for this product. The product manager pointed out one major mistake I made, which was copying too much from the inspiration sources provided.
Feedback was very instrumental in the cycle of this product. Insights for iterations (which were mostly based on feedback) were key to improving the user experience and interface of the product.
What I took from this, is that it is so important to get feedback at different stages of the design process.
Because of this, I share artifacts like prototypes, wireframes and more with my team at different stages of the design process.
Mistakes were made in the early stages of the design for this product. The product manager pointed out one major mistake I made, which was copying too much from the inspiration sources provided.
Feedback was very instrumental in the cycle of this product. Insights for iterations (which were mostly based on feedback) were key to improving the user experience and interface of the product.
What I took from this, is that it is so important to get feedback at different stages of the design process.
Because of this, I share artifacts like prototypes, wireframes and more with my team at different stages of the design process.
Related works
Related works
Projects
Projects
© 2024
© 2024
© 2024