Alvaria
Enterprise workforce platform at scale
AI
B2B
Aspect Intelligence
Contribution
Strategy; Prototyping; Testing; Design Sprint
Duration
7 month
Date
2025-2026
TL; DR : My impact in a nutshell
👩🏻💻 Craft & Strategy
Worked directly with ML engineers to understand how predictions model were generated, then translated that complexity into UX that
builds trust with AI.Turned complex AI forecasting data into a clear, intuitive
visualizationwithout overwhelming users.
🤝 Collaboration
Led discovery callsand partnered closely with ML, front end, and product teams to shape the experience from concept to launch.Hosted design hand-off hours to
enhance designer-engineer collaboration.
📈 Results
500+agents supported, with enterprise teams at Comcast, Zillow, Best Buy, and more65%reduction in time spent analyzing forecasts25%improvement in forecast accuracy2.4×increase in engagement with AI forecastsSource: 2025 Annual Report
The Challenge: Robust data still fails adoption.
Aspect had 20 years of workforce data powering a highly robust forecasting system. But more information does not create more confidence. Trust does. Instead it created more friction. Users felt overwhelmed, couldn’t see how predictions were generated, and struggled to trust the AI.
How I shaped the product:
#1 Less surface, more signal
Partnered with front end engineers to turn dense forecasting data into intuitive visualizations.
Signal → Context → Confidence → Action
#2 Trust compounds; adoption follows.
Worked closely with ML engineers to understand how predictions were generated, translating the complexity into clear, transparent UX. The experience included a “How AI works” page and FAQs to help users understand the AI and build trust in its predictions.
#3 Shaped the product around users
We are a team that constantly talking to our users, and turning insights into product direction, shifting forecasting from a data heavy tool toward an AI native experience.
Watch Zilliow's story here to see how our forecasting transformed their planning process.
