Mobile applications
iOS and Android in Flutter, covering onboarding, workout plans, progress, activity tracking, paid access, notifications, and the daily member experience.
NWFit · AI fitness · iOS · Android · Web
An AI fitness platform scaled to 140K+ users.
We built and scaled NWFit as one product across mobile and web, connecting personalized workout recommendations, subscriptions, payments, activity data, analytics, and the systems required to operate the platform as usage grew.
140K+users in under two yearsAugust 2023 to 2025 · iOS · Android · Web
- Timeline
- August 2023 to 2025
- Project scope
- USD 100K+
- Platforms
- iOS · Android · Web
Product context
One fitness experience across three platforms and several operating systems.
NWFit needed to feel consistent whether a member opened the mobile app or the web product. Behind that experience, the platform had to manage workout recommendations, paid access, activity integrations, notifications, analytics, advertising attribution, and daily product operations.
Those pieces could not be treated as separate integrations. A subscription decision affected access. Activity data affected progress. Recommendation logic affected the next workout. Analytics and support needed to see enough of the same data to understand what a member experienced.
Product scope
A cross-platform product foundation built to evolve.
The delivery connected customer-facing surfaces to shared product state and the operating services behind them.
Web application
A Next.js web product connected to Stripe payments and subscriptions and the account access model.
Backend and APIs
Express.js and MongoDB services handled product data, user state, mobile and web APIs, and shared integrations.
AI workout recommendations
A Python and FastAPI service powered personalized workout recommendations and stayed separate enough to improve without rebuilding the whole application.
Subscriptions and paywalls
Stripe supported web payments, while RevenueCat and Superwall supported mobile subscriptions, paywalls, and product testing.
Activity and analytics
HealthKit, Google ML Kit, Firebase, attribution, analytics, and session insight connected device data, product behavior, and growth operations.
Engineering structure
Each surface could change without losing the shared product model.
- Mobile
- Flutter applications for iOS and Android
- Web
- Next.js application with Stripe checkout and account access
- Core backend
- Express.js APIs with MongoDB
- Recommendation service
- Python and FastAPI
- Mobile subscriptions
- RevenueCat and Superwall
- Activity
- HealthKit, Google ML Kit, and fitness tracking
- Product operations
- Firebase, push notifications, analytics, attribution, and session insight
What mattered during delivery
Keep the product model coherent as the surface area grows.
Keep paid access consistent
Web and mobile used different payment systems, but members needed one understandable access state.
Make recommendations part of the product
The AI layer connected to member state and workout delivery rather than becoming a detached chatbot.
Connect growth data to product behavior
Attribution, analytics, notifications, and session insight helped the team understand acquisition, activation, engagement, and support.
Build for continued change
Shared services and clear integration boundaries made new workouts, paywalls, experiments, and campaigns easier to reason about.
Outcome
140K+ users in under two years.
NWFit grew across iOS, Android, and web while the product combined AI workout recommendations, activity data, subscriptions, payments, analytics, and daily operations in one platform.
Technology Flutter · Next.js · Express.js · MongoDB · Python · FastAPI · Stripe · RevenueCat · Superwall · HealthKit · Firebase
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