Arktera AI : Empower beginner traders with simplified AI insights & community support

Designed a mobile platform that helps retail investors cut through data noise, gain real-time AI guidance, and trade confidently—without needing expert-level knowledge.

PROJECT TYPE

Fintech mobile app

TEAM

CEO,  Quantitative analysts, AI/ML engineers

MY ROLE

Product & Visual designer

DURATION

Sep 2023 - April 2024

IMPACT
1000+
Downloads 1st month post launch
100+
Daily active user
-58
Information consumption time
200+
Design components
Overview
Many retail investors feel overwhelmed by stock data and scattered tools. While platforms like Robinhood offer raw info, they lack guided, simplified insights. After conducting user interviews, we identified three major pain points:
Information overload from endless market data
Disjointed experience across multiple platforms
Lack of quick, AI-based analysis tools
Differentiate from competitors
Unlike platforms with complex data or user-generated tips, Arktera offers an all-in-one solution with AI market insights, analysis assistant, and community features to solve investors’ challenges.
User research
Understanding first-time traders
From pain point to design opportunities
Challenge
How might we simplify financial data so it’s clear, actionable, and engaging for retail investors?
Final Solution
The design integrates multiple modules to address investor's pain points.
Pain point 01 : Information Overload
Traders often struggle with information overload and complex terminology, spending too much time sifting through news, reports, and data.
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Feature 01 : Market Insight AI Playlist
Transforms stock insights into quick 2-minute podcast-style updates.
Pain point 02 :Confused by complex terms
For those new to trading, understanding stock trends, analysis, and market signals can be overwhelming.
Feature 02 :AI Analysis Assistant
A 24/7 assistant that simplifies financial data, answers user questions, and offers custom trading tips.
Pain point 03 :FOMO when trade in silo.
Many investors struggle with trading in silos, missing out on key insights and real-time market trends.
Feature 03 :Trader Community Hub
Connects users with curated discussions, alerts, and group trading insights to prevent FOMO.
Design challenge
Define structure: Leverage AI model to create recommendations and insights

To address the challenge of information transparency and digestion difficulty, We leveraged an AI model by defines the inputs—from real-time market data, financial reports, and news feeds—to the outputs that power our user interface. By doing so, we ensure accurate data capture and present users with a clear and  structured insight report, reducing information difficulty and reading time.

Design iteration
Transition from standard market watchlist to playlist style AI insight podcast.

After our initial launch, the most common question we received was, "How is this different from Yahoo Finance or Robinhood?" And honestly, aside from having a chat feature, we didn’t stand out much.

To differentiate ourselves both as a product and in how investors engage with market insights, we leveraged notebook LM capabilities and gathered user feedback. The result? A playlist-style AI-powered insight podcast that delivers key market takeaways in just three minutes.

Initial Launch
  • Not enough differentiate from competitors
  • Users struggle with complicated terms.
  • Takes too long to scan through

Updated Design
  • Innovative insight page that
  • Watches financial news.
  • Checks company earnings & analysis
Reflection & Next Step
Establish design system to help iterate fast.  
Design the framework first before diving deep in details.
Always push for innovative way user experience and integrate new tech.