Role: Product Designer

Duration: August 2025 - November 2025

Tool: Figma, Google Suite

Team Members: Jane Hu, Wenbo Guo

LeapIn is an AI Talent Intelligence Platform for global enterprises. They were facing a challenge of integrating AI into their designated workflow. Meanwhile, all users need a human tutor on the side to get their hands on jobs.

Background

LeapIn is an AI Talent Intelligence Platform for global enterprises. They were at a pivot moment of deciding to implement their AI model into actual usage on the platform for their global enterprises. The owner reached out to our design team and asked for a solution.

Project Goal

The LeapIn Platform serves as a command center for HR to manage current and any potential future employees.
The platform needs to manage different tasks all at once while maintaining a clear workflow for target users - Human Resources (HR). By introducing AI tools, the platform aims to reduce cognitive load and increase efficiency in completing tasks.

Project Highlights

Defining the level of AI usage across the platform is the most challenging part of this project.
After aligning the goal of the tool and the brand image, I proudly introduced a three-level AI integration on LeapIn platform. We inherited users’ most familiar AI interactive experience across the market to make sure users can comfortably incoprate in their daily tasks.

Level 1- General AI Assistant

The 1st-level AI Assistant is the broadest. Using a classic prompt interaction, users can quickly acquire information or complete a task based on their wishes.

The AI Assistant will locate and serve as the landing page of the platform. Including custom widgets for different enterprises, the landing page will greet the users while providing a data overview and summary for a more easier access to certain information.

Features Lists:

  • Custom Widgets for different enterprises

  • Three types of functioning selections utilizing different source libraries at the backend

  • Automatic Position creation flow, along with active users’ input for accurate final results

Level 2- Task-Based AI Assistant

The 2nd-level AI Assistant is helping users with current tasks. Using a classic conversation-based interaction, users can easily get access to the back-end data.

The AI Assistant will forever live at the bottom of the main menu bar with two different sizes fit for either collapse or fully opened menu form. Users will be able to have fast and quick access in a Q&A format to gain the data and information they need.

Features Lists:

  • Dialog-based interface for easier resource check and acquisition

  • Pre-set task-based CTA button for quick start

  • Feedback system to help the AI Assistant improve further for a better future experience

Level 3- Step-Based AI Assistant

The 3rd-level AI Assistant is helping users in a specific step. Using a CTA button interaction, users can command AI to automaticly fill-in the information.

While users are filling out some information or selecting some evaluation model for candidates and employees, this AI assistant will be able to provide quick suggestions or auto-filling based onthe corresponding past history. This type of AI Assistant significantly boosts the users performance in managing and solving complex problems.

Features Lists:

  • Utilizing historical data to automate repetitive tasks

  • Automatic matching corresponded to evaluation tasks for more accurate results

Design Library

Along with defining AI Assistant integration for the platform, LeapIn also got a major visual and UX improvement from us.

The product contains a complex information hierarchy with rich content. To improve task flow clarity, we broke down and reorganized the information structure using different design elements. For example, we used Steppers, Tabs, and Switch Tabs to clearly define and present each level of information.

With heuristic evaluation along with users’ feedback, my team and I are redesigning the major workflow and redefining the content display logic to provide a clearer and easier pipeline management for the users.

Summary

Leading a definition of the level of AI integration for a platform with a complex user flow and adaptive content management was a great challenge at that time. By completing the design works, I equipped myself with a better understanding of the AI tools’ backend logic. Therefore, I will be able to transcribe the AI into a better form of front-end interaction with users in my future design work. At the same time, creating and managing a design library in Figma significantly united our stakeholder’s brand image and improved the development cycle for all their future features and products.