Artus AI

Introduction

Artus AI is an AI-powered SaaS career intelligence platform that helps users navigate career paths with data-driven insights.

Problem Statement

Career tools were either generic or expensive; the platform needed an intuitive UI to turn AI insights into actionable guidance.

Scope

Multi-step onboarding, dashboard interfaces, tier-based UI (free vs premium), and a reusable component library across 15+ views.

Target Audience

Professionals seeking AI-powered career guidance.

Functional Requirements

• Multi-step onboarding with progress tracking
• AI insights dashboard with recommendations
• Tier-based UI for free vs premium users
• Performance optimization for AI content
• Reusable component library
• Structured flow: onboarding → dashboard → insights

Challenges

• Designing onboarding that users complete
• Presenting AI outputs in an actionable format
• Implementing feature gating cleanly
• Maintaining performance with data-heavy AI responses

Solution

Designed structured onboarding and modular architecture with clean feature gating and performance-focused UI patterns.

Technical Overview

React frontend using Tailwind + shadcn/ui. State handling for onboarding + AI data. Lazy loading and memoization for perceived performance.

Advantages

Limitations

• AI response latency affects dashboard loading
• AI UI requires ongoing UX iteration
• Tier gating adds component complexity

Outcome

Artus AI shipped as a production-ready SaaS frontend with scalable architecture. The structured onboarding flow achieved 85%+ completion.

Key Learnings

• Onboarding UX directly impacts activation
• AI UIs need intentional loading states
• Modular architecture decisions compound over time
• Performance patterns should be built early