Neuromind is a planning partner that adapts to a student's energy, schedule, and habits instead of demanding rigid adherence to a plan. Every feature targets cognitive-load reduction, aiming to work with the user rather than against them.
How it works
- Built MVVM with Jetpack Compose and Material 3, StateFlow-driven ViewModels, and a Room-backed local database: task management with swipe-to-complete/swipe-to-delete, priority colour stripes, and an agenda-style timetable for recurring and one-time events.
- A 25-minute Focus Mode Pomodoro timer runs alongside an End-of-Day Review that logs mood, energy, and free-text notes, feeding a weekly task-completion chart and a wellness score derived from recent mood/energy history.
- A SmartInputHelper regex parser understands natural phrases like ‘remind me to study tomorrow at 5pm’ without calling out to an LLM for basic scheduling.
- The app is organized around 15 design pillars tracked in its own roadmap; most of the daily-use pillars (Focus Mode, timetable, task cards, End-of-Day Review) are implemented.
Where it stands
Currently at v4.0-rc1: the next milestone is wiring the AI Intelligence Loop, connecting the feedback data pipeline and SmartInputHelper to the UI and building the Cognitive Profile settings that would actually drive adaptive scheduling. The adaptive-energy framing describes the target architecture, with the adaptive loop itself still in progress.
Built with
- Kotlin
- Jetpack Compose
- Room
- WorkManager