Predicting multi-modal ETAs.
Bengaluru Vega
Year
2025
Role
Machine Learning
Overview
A machine learning system that predicts accurate arrival times across buses, metro, and road travel for Bengaluru's transit network — fusing multiple data sources into one reliable estimate.
Every screen was refined until it disappeared — letting the content and the work speak for itself. The result is a calm, confident product that respects the people who use it.
The challenge
Distill a complex problem space into an interface that feels obvious — where the right action is always the easiest one.
The approach
Start with motion and hierarchy. Prototype early, test often, and let the smallest details carry the experience.
The outcome
A product that people genuinely enjoy using, with measurable gains in engagement, retention, and team velocity.
