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Business Goals
- The client wanted to increase market share for which they proposed to build an AI-driven workout assistant.
- Another aim was to not only provide workout assistants but also ensure users interact with the app. Their idea was to offer feedback-rich features like pose-detection and AI chatbot.
- On technical level, the client waned to build an app that runs on both Android & iOS platforms without writing double codebase and reach millions of users quickly.
- The initial idea was to offer a freemium version alongside a paid-plan that is AI-backed.
- With backend integration like Firestore, the client aimed to collect anonymized usage data to fine-tune exercise recommendations and chatbot behavior over time.
Business Challenges
The client wanted to build an app that offers real-time pose detection during strenuous exercises to get the optimum benefits out of it.
Users tends to stay for a longer period if they like to get engaged or the app is worth engaging. Without much engagement or interactions, the app couldn’t survive the cut-throat competition.
The client had a demand to enable entirely new chatbot prompts and configurations without depending on constant redeployment.
Real-time user data, progress monitoring, and profile updates wanted consistent syncing across sessions and devices.
The client required a smooth pipeline to release updates quickly.
Technical Solution
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On-Device Pose Detection Using Google ML Kit
Our software development team integrated Google’s ML Kit Pose Detection API, which offers on-device machine learning for identifying body joints in real-time. This allowed the app to analyze user movements with minimal latency, delivering immediate posture correction and eliminating the need for constant internet connectivity.
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AI-Powered Conversational Chatbot with Google Gemini
With the help of Google Gemini API, our software developers implemented a chatbot powered by AI that can handle contextual conversations and deliver customized responses The chatbot would answer fitness freak questions, guide users with routines, and create with two-way fitness experience that brings back users and hook the for life.
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Firebase Remote Configuration for Instant Content Updates
We utilized Firebase Remote Configuration that made users believe that they can update prompts, UI content, and feature toggles directly from firebase console. As a result, the users were able to get access to full editorial control over app behavior without many changes in code.
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Real-Time Data Sync with Cloud Firestore
Another solutions we offered was by integrating Firebase Cloud Firestore, which is a scalable NoSQL database that shares and stores synchronized data. There will be profile updates, preferences, and workout stats that becomes instantly available and consistent.
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CI/CD Automation Using GitHUB Actions
We enabled a robust CI/CD pipeline using GitHub Actions, which automated functions like building, testing, and deploying both Android and iOS versions. Every time with the code push, the system starts performing quality checks. As a result, it maintains high codebase and accelerate release cycles.
Project Glimpse
Key Features
Real-Time Pose Detection
AI Chatbot Integration
Curated Exercise Library
Dynamic Chatbot Configurations
Secure Authentication
User Profile Management
Sync of exercises, preferences, and data
Cross-platform Mobile App
Camera Access Handling
CI/CD for automatic build and deployment
Result
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01.
85% user accuracy in pose detection during workouts
With the app, you can receive motion tracking to uplift exercise effectiveness.
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02.
3x increase in daily engagement thanks to the chatbot support
This was achieved using the interactive chatbot support driving consistent user activity.
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03.
Reduced update cycles by 60% using Firebase Remote Config
Optimized rollout speed using Firebase Remote Config for faster iterations.
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04.
Improved user satisfaction due to intuitive UI and real-time feedback
It enhances usability and responsiveness that boosts user confidence.