Question
How might an AI research companion help traders move from noisy crypto information to a clearer, more personalized workflow?
Context
Why this mattered
A team-built crypto research and trading assistant developed for the HP & NVIDIA Developer Challenge. The application was built by my husband and the broader team; my contribution focused on research, product definition, and UX prototyping.
Approach
From ambiguity to evidence
Conducted trader research to understand information, workflow, and trust needs.
Translated research into product definition, prioritization, and a UX prototype.
Worked with the team to connect research insights to the deployed crypto-intelligence experience.
Findings
What the analysis surfaced
Trader workflows benefit from combining market context, research, and portfolio decisions.
Personalization and explainable context matter when AI supports high-stakes financial decisions.
The prototype demonstrates a product direction and does not claim investment performance.
Contribution
What I owned
Product researcher and UX/product-definition lead; partnered with my husband and the build team.