Track routines, analyze behavior patterns, and improve consistency with intelligent habit insights.
Log habits and detect patterns automatically with AI analysis.
Receive recommendations to improve consistency.
Maintain streaks and track long-term progress.
NeuroHabit is an AI-powered habit tracker designed to bridge the gap between intention and action. Most habit trackers treat every habit the same a checkbox, done or not done. We think that's too simple.
We built NeuroHabit to support both static habits (binary done/not done) and dynamic habits (quantitative goals like reading 20 minutes or eating 150g of protein). The result is a system that maps more accurately to real life.
Built for a hackathon, NeuroHabit combines a clean futuristic interface with meaningful data tracking giving users a dashboard that actually helps them improve.
Most people fail at habits not because of lack of motivation but because their tools don't reflect how habits actually work.
Add static habits like "Go to gym" or dynamic habits like "Read 20 min" with a target value. NeuroHabit adapts to how you naturally think about goals.
Check off static habits or enter your actual value for dynamic ones. Progress bars and completion percentages update in real time so you always know where you stand.
NeuroHabit tracks consecutive days of completion. Dynamic habits count a streak only when you hit your target keeping standards high without punishing partial effort.
The AI panel analyzes your patterns and surfaces actionable suggestions like which habits you're closest to completing or when you tend to be most consistent.
A small team that wanted better tools for building better habits.
Designed the futuristic dark-theme interface and built the landing page and dashboard layout.
Architected the habit data model, streak logic, and localStorage persistence layer.
Developed the AI insights engine and dynamic habit progress tracking system.