IRVO
A personal performance tracking app that helps you understand how your daily habits affect how you feel and function. Log tasks, energy, focus, and stress. Let the data show you the patterns.
Project landing pageType
Health App
Platform
iOS & Android
Stack
React Native • Expo • Express • Redis
The Problem
- Existing habit trackers count streaks, not why you feel off
- No way to connect daily inputs (sleep, meals, tasks) to performance
- Users sense patterns but have no data to confirm them
- Turning structured self-tracking into actionable insights is hard
- Result: vague feelings, no concrete answers, no way to improve
What We Built
A cross-platform mobile app for structured self-tracking, available on iOS and Android.
- Task + mood logging: energy, focus, and stress throughout the day
- Optional physical symptom tracking
- Pattern detection that surfaces correlations when they repeat
- Async processing via BullMQ + Redis for reliable background analysis
- TypeScript across mobile and backend for a maintainable codebase
Task + Mood Logging
Log planned tasks alongside real-time energy, focus, and stress levels throughout the day.
Pattern Detection
The app identifies meaningful patterns in your data and surfaces them when they repeat.
Physical Symptoms Tracking
Optional symptom logging for users who want to connect physical state with performance.
Async Processing with BullMQ
Background jobs handle data analysis and insight generation without slowing the app down.
Tech Stack
We picked a stack that handles cross-platform mobile well and can process behavioral data reliably in the background.
React Native + Expo
Cross-platform development targeting both iOS and Android from a single codebase. Expo handles builds and updates cleanly.
TypeScript
Type safety across both the mobile app and the backend. Catches issues early and makes the codebase easier to maintain as it grows.
Express.js + TypeScript
Backend API for data sync, authentication, and processing user entries. Clean and fast.
BullMQ + Redis
Async job queue for reliable background processing. Pattern analysis and insight generation run as background jobs without impacting app performance.
The Result
- Runs on iOS and Android from a single codebase
- Quick daily logging: behavioral picture builds in the background
- Patterns surface automatically, no manual analysis required
- Async pipeline handles growing data without impacting app performance
- TypeScript backend is easy to extend with new insight types
From vague feelings to concrete, data-backed insights about what drives your performance.
Common questions
Answers about self-tracking, performance apps, and the tech behind IRVO.
Building a mobile app?
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