Turning daily mood into personal insight through an AI-driven app
About the project
HowIFeel is Halo Lab’s internal AI-driven mobile product designed to transform how people track and manage their emotional well-being.
The app combines emoji-based mood logging with AI-generated insights, helping users articulate feelings, identify patterns across days and weeks, and understand what drives their state.
Challenge
The wellness market is full of apps that ask for too much and offer too little insight. We set out to build HowIFeel as a simpler, more useful alternative — one designed to reduce friction, deliver meaningful daily value, and grow into a credible MVP.
Our process
We took HowIFeel from concept to a subscription-ready MVP, building its product strategy, design system, AI layer, and technical infrastructure end to end.
{{dropdowns-1}}
Results
HowIFeel reached an internal MVP stage, with the core experience implemented and tested across mobile platforms. The product combines mood logging, AI-generated insights, secure authentication, and a subscription layer across the full user journey. Internal validation highlighted the calendar feature as especially valuable for tracking mood patterns over time. Next, the team plans to refine the product ahead of a Product Hunt and App Store launch, followed by a broader release supported by social media, partnerships, and targeted outreach.
Our approach
Our strategy centered on simplicity as a core principle. We made deliberate decisions to reduce friction so users could focus on understanding themselves, not navigating the app.
{{approach}}
01 · Discovery & product strategy
We benchmarked key competitors to locate gaps in daily retention and emotional depth. This shaped the MVP’s core features and stack: Apple authentication, AI journaling via OpenAI, subscriptions via RevenueCat, and a Supabase backend.
Deliverables
- 5 competitors analyzed
- Tech stack defined
- MVP scope outlined
02 · UX/UI design
Our team designed the app around a single interaction: a tap to log mood using an emoji set. We crafted a supportive interface built on a scalable component system designed to grow with future features like voice input and offline use.
Deliverables
- Key user flows
- AI insight screens
- UI component library
03 · Mobile development
We built the app in React Native with Expo, combining local SQLite storage with Supabase cloud sync and OpenAI mood analysis. EAS build profiles and GitHub Actions pipelines covered every environment from development to production.
Deliverables
- Android and iOS builds
- GitHub Actions CI/CD pipeline
- Environment configuration
04 · Documentation & delivery
Our specialists documented the component library, environment setup, and CI/CD workflows for a clean developer and QA handover. RevenueCat was chosen as the subscription layer, with a go-to-market strategy outlined for a smooth MVP launch.
Deliverables
- Developer & QA handover doc
- RevenueCat integration
Team
A cross-functional team worked in close sync, continuously adapting to new insights from classroom trials and robot behavior.
- 1 Project Manager
- 2 Brand Designers
- 2 UI/UX Designers
- 2 Web Designers
- 1 Front-end Developer
- 1 Back-end Developer
- 1 QA Engineer
Technologies
Our stack supported offline interaction, hardware communication, scalable content management, and smooth cross-platform UI.
Team
- 1 Project Manager
- 2 UI/UX Designers
- 1 Front-end Developer
- 1 React Native Developer
- 1 QA Engineer
Technologies
