Smart AI Tool
Searching Platform

A web application designed to simplify the process of discovering AI tools tailored to users customized requirements.

Project overview

AI Tool Discovery Platform — A web application that leverages AI to help users find the right AI tools based on their unique needs.
Instead of relying on exact keywords, the product uses intelligent suggestions and interactive guidance to transform vague user queries into meaningful, personalized results.

The Challenge

Discovering AI tools sounds simple, but in reality users often:
  1. Struggle to generate effective keywords
  2. Face decision-making overload when comparing too many results
  3. Need guidance to refine their search journey
  4. Prefer seamless, interactive exploration instead of manual trial-and-error

Problem Statement

How might we design an intelligent, AI-powered search process that understands user intent and reduces cognitive effort?

Information

Type
Web app Design
Duration
2024.01-2024.03
My Role
Project Management & Design Lead
Design Methods
User Surveys | Personas | Competitive Analysis | Journey Maps | Content Strategy Map
Deliverables
Core interaction flows | Prioritized feature set | High-fidelity prototypes | Design System
When I first approached this project, the challenge wasn’t simply building another search interface.

Users don’t struggle to find AI tools because they don’t exist—they struggle because the search process itself is unintelligent. From keyword difficulty to decision overload, the original design left users with friction at every step. This project was about rethinking that journey: how can we leverage AI not just as content, but as the core mechanism that guides discovery and reduces cognitive effort?

Research Process

01 Original Design Critique

01 Difficulty in Generating Keywords

Users struggled to come up with effective keywords to find the tools they needed.

02 Need for Guidance

The abundance of options made it hard for users to make decisions on which tools to choose.

03 Decision-Making Overload

A lot of must-seen information are missing / hidden in deeper navigation

04 Desire for Clickable Suggestions

Users wanted interactive, clickable suggestions to refine their search more easily.
To understand where the design was falling short, I began by critiquing the existing flow. The issues—keyword struggles, lack of guidance, and decision overload—made it clear that solving this problem required a deeper look at user behaviors and expectations.

02 User Research

Tech-savvy Professional in AI

Practical AI Newcomer

Research revealed two distinct personas: tech-savvy professionals exploring advanced capabilities, and newcomers seeking plug-and-play solutions. To translate these personas into actionable design requirements, I mapped out user scenarios to study how different types of users approach discovery and where AI could step in to provide guidance.

03 User Scenario Study

From these scenarios, it became clear that the product needed to support multiple entry points: exploration without a clear goal, task-driven discovery, and feature-specific queries. I translated these needs into an information architecture that balanced flexibility with clarity, ensuring AI-driven suggestions were at the heart of the experience.

04 Information Architecture

Design showcase

Based on the conclusions from our research, we redesigned the entire interface flow from order management to container tracking, effectively addressing the needs of the stakeholders.

Design Solutions

Main Function: Discovery

How Might We increase both registration and retention rates by making our platform more engaging and valuable?

Solution01-User Profile feature

Solution02-Submit AI Tool & API

Solution03-Expect Share and User Feedback

Design Results