Pluto is an AI-powered investment research platform that was aquired by Robinhood in December 2023. Pluto used large language models to process and interpret real-time market data to surface insights faster and deliver highly personalized investment strategies.

Client
Pluto
2023
Position
Product Designer
Company Size
6 People
Responsibilites
User Experience
Design System
Prototyping
Interface Design
Problem
Pluto’s early product tried to combine AI research, rule-based strategy automations, and portfolio/trading into one platform, but the experience didn’t give users a clear workflow or mental model for how these parts connect. As a result, users had to hunt for where to start, interpret dense dashboards and long AI outputs.
Brief
Pluto has strong building blocks but they don’t resolve into a single, trustworthy workflow. Users can generate outputs, but struggle to understand what matters, what to do next, and how/why automations behave.
Previous Screens
Creating detailed wireframes that helped make navigation seamless and straightforward.
Interviews
To better understand and build empathy for Pluto’s target users, I conducted discovery research using three complementary methods: semi-structured interviews, personal inventory, and persona synthesis.
Semi-structured Interviews
I ran semi-structured interviews to uncover how people actually research, decide, and act in markets—then mapped where Pluto added value vs. introduced confusion. The interviews were designed to stay open-ended while consistently covering: investing goals, risk tolerance, research routines, decision triggers, trust requirements, and the handoff from “insight” to “action.”
Personal Inventory
To complement what users said, I used a personal inventory exercise to understand what they use. Participants walked through the tools and artifacts they rely on to make decisions, explaining why each tool earned a place in their workflow.
Usability Testing
To move from opinions to observable u, I ran usability testing sessions focused on critical flows — especially where the product needed to bridge insight to action.
Users often stalled at the start
After landing in Pluto, many users hesitated because it wasn’t immediately obvious what Pluto needed from them to personalize the experience.
Users struggled with what to do next
After receiving an AI answer, many users weren’t sure how to turn it into an actual decision or next step.
Automations were hard to trust
When an automation suggested an action or pushed a notification, users couldn’t easily tell what data it was based on, or how reliable it was.
User Personas
The Guided Investor
Wants simple, confident direction. Needs a clear start, plain-language explanations, and low-risk actions.
The Automation Power User
Wants simple, confident direction. NWants systematic execution. Needs rule transparency, backtest/preview,
The Active Investor
Moves fast and filters aggressively. Needs real-time relevance, tight alerts, and actionable summaries.
The Thesis Builder
Uses research to form a point of view. Needs structured canvases, repeatable frameworks, sources, and “what would change my mind?”
Product Goals
Actionability
Make every analysis end with a clear outcome: key takeaway, confidence level, and a recommended next step.
Control
Let users tune risk, time horizon, and notification intensity so the product adapts to them—not the other way around.
Clarity
Unify into one mental model so users always know where they are.
© 2026

D.BOY — ©2026