Xylo is an AI-powered decision intelligence software that helps financial advisors identify relationship risks and opportunities in real time.
CONTRIBUTION
Lead Product Design
UX Research
TEAM
CEO
Design Manager
Engineers*3
TOOLS
Figma
Zeplin
Jira
TIMELINE
4 Months
Context
Redesign the Xylo Dashboard to Transform Client Monitoring into Actionable Intelligence
In the summer of 2025, I worked at Xylo AI as the Product Design Intern, leading the redesign of the core dashboard experience, aiming to transform it from a traditional CRM-style interface into a proactive decision system.
The primary challenge was not the lack of data, but the overwhelming volume of fragmented signals. Advisors were managing dozens of client relationships across multiple systems, yet struggled to quickly determine which relationships required attention.
To address this, I reframed the product from a “data dashboard” into a “relationship monitoring and prioritization engine.” Through behavioral research, workflow observation, and iterative prototyping, I introduced a triage-based system that surfaces changes, risks, and urgency signals in real time.
This strategic shift significantly reduced cognitive load and repositioned the platform from passive data storage to active decision support.
My Role
I led the strategic redesign of the dashboard architecture, redefining how relationship intelligence is structured, prioritized, and surfaced to advisors.
I advanced core decision flows by shifting the information hierarchy from static client profiles to change-based monitoring and action prioritization.
Impact
Increased advisor workflow efficiency by 20% by reducing decision hesitation and manual signal analysis.
Improved prioritization clarity, leading to higher engagement with Top Actions and proactive outreach.
Understand
From Users: Information is abundant
but fragmented.
I conducted the user interviews with advisors, they described their workflow as mentally exhausting. They searched through emails, CRM notes, and call records to prepare for client conversations.They constantly switch between tools to answer three core questions: Who needs my attention right now? What has changed? What should I do next?
From Product: Xylo AI Relationship
Intelligence Platform
Xylo AI helps financial advisors monitor client engagement and identify relationship risks through AI-driven insights. However, I found that the current design presented usability challenges.
Information was scattered across multiple pages, navigation lacked clarity, and critical signals were buried within dense tables. Advisors had to manually search for insights, interpret static metrics, and switch between views to understand client context.
“The numbers are easy. The hard part is understanding what my clients need from me at the right moment and communicating it clearly.”
— Bob, Financial Advisor
Project Goal & Scope
Translate fragmented client signals into clear, confident actions, then reduce cognitive load.
Project Task 01
Redesigning the data dashboard experience into a relationship monitoring engine
Problems
The Dashboard Functioned as a Data Summary — Not a Decision Tool
The previous version of the Xylo Dashboard was designed as a summarized view of the existing CRM system. It consolidated metrics such as AUM, health scores, sentiment, fees, referral warmth, and contact history into a comprehensive table. While information was centralized, it did not translate into clarity.
The table contained too many static data points, requiring advisors to manually scan and interpret signals across multiple columns. Important changes, such as sentiment drops or engagement gaps were visually subtle and easy to miss.
Approach
Interviews and usability testing to identify true decision drivers and eliminate non-essential signals
To redesign the dashboard effectively, I first focused on understanding what actually drives advisors’ decisions rather than assuming which data points were important
I also conducted usability testing to validate the new prioritization logic
Design Decision
Prioritization by Change, Not by Status
I redesigned the dashboard to prioritize change-based signals rather than static summaries. Sentiment became “Sentiment ↓18% (7d)” instead of “87 (-18%).” Inactivity became a time-triggered alert. Risk states became visible clusters instead of subtle indicators.
However, surfacing change alone was not enough and signals needed to translate into action.
The original “Top Actions” module grouped alerts by category (Churn Risk, Opportunity, etc.), requiring advisors to interpret urgency themselves. I redesigned it around decision context instead of system taxonomy.
Each action now clearly answers: Who needs attention, Why now and How to act.
By adding explicit triggers (“47 days silence”) and suggested channels, the interface shifts from displaying alerts to guiding next steps by reducing ambiguity and accelerating decision-making.
Project Task 02
Evaluating the Personalized Relationship Intelligence
Problems
Fragmented relationship insight disrupting advisor workflow
The previous version of the Xylo dashboard separated Relationship and Personality into two independent pages. Advisors were required to review relationship context on one screen, then switch to another page to interpret communication style and behavioral traits.
Although the data existed within the system, it was not structurally connected. This separation introduced unnecessary context switching, increased cognitive load, and slowed down decision-making.
As a result, personalized communication relied heavily on manual interpretation rather than guided intelligence, limiting scalability and consistency across advisors.
Approach
Introducing HeartKey 360 to unify insight and action
To streamline the workflow and reduce friction, I introduced concept "HeartKey 360", a unified relationship intelligence layer powered by Xylo AI.
Instead of separating who the client is from how to engage them, HeartKey 360 consolidates behavioral signals, sentiment trends, and communication patterns into a single decision surface.
Through AI analysis, the system generates a structured communication strategy and provides recommended actions directly within the same view.
Design Decision
Reframing Relationship Insight as an Action-Oriented System
Rather than refining two separate pages, we made a structural decision to redesign the experience around a unified client profile.
The previous architecture treated relationship data and personality traits as parallel information layers. While both were valuable, they required advisors to manually connect context before taking action.
We consolidated these layers into a single Client Profile Page, anchored by the HeartKey 360 model. This allowed insight, interpretation, and action to exist within one continuous flow.
Design System
Building a Scalable Identity While Aligning Design + Engineering
When I began this project, the product was already built using Google Material Design. While functional, the interface lacked Xylo branding and personality. The system felt generic and did not reflect the intelligence-driven positioning of the platform.
As a summer intern, rebuilding a design system from scratch was not feasible within the project timeline. Instead of starting over, I explored how we could introduce brand differentiation while maintaining engineering efficiency. After discussions with the front-end team, we decided to adopt Hero UI as a flexible foundation.
From there, I established new color tokens, typography hierarchy, and component variations aligned with Xylo’s brand direction, while ensuring seamless integration with development workflows.
Impact
Success Metrics & Results
After four months of cross-functional collaboration, we successfully launched the Xylo MVP. The redesign increased advisor workflow efficiency by 20% by reducing decision hesitation and manual signal analysis.
Beyond usability gains, the MVP attracted interest from 50+ financial advisors and supported the company in securing $10M in funding, reinforcing Xylo’s positioning as a relationship intelligence platform rather than a traditional CRM dashboard.
Design is constrained by systems, not just screens
Effective solutions depend on backend capabilities and data structure
Early alignment with engineering is critical to avoid rework
Driving adoption is as important as designing the solution
Reducing adoption friction is key to implementation
Demonstrating value is more effective than enforcing standards
Consistency requires cross-functional alignment, not just design rules
Without a shared system, implementation becomes fragmented
Design systems succeed through adoption, not enforcement
