Inspired by how often people underestimate how long tasks really take, TimePilot helps you manage your schedule intelligently. It learns from your past tasks to understand how long things actually took, and when you create a similar task without enough time, it proactively warns you before you fall behind. TimePilot also factors in travel time by using task locations, ensuring your schedule reflects real-world constraints. We built the project by combining task history analysis, scheduling logic, travel-time awareness, and an AI-powered input feature that lets users create tasks effortlessly without manual entry. Along the way, we faced challenges in accurately predicting task durations and balancing automation with user control, but we’re proud of creating a system that feels genuinely helpful rather than overwhelming. Through this project, we learned a lot about user-centered design, data-driven prediction, and integrating AI in a practical way. Next for TimePilot, we plan to improve prediction accuracy, expand AI-assisted planning, and make the experience even more personalized—so users can stay on track with confidence.
Built With
- git
- github
- react
- supabase
- typescript
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