
Project Overview
Client Name
Symon Adeji
Project Name
PalmR8D
Industry
Social Networking
Project Duration
Ongoing
Team size
3-4 engineers
Website
Client Profile
The Challenge
Key Challenges
Challenge 1
Creating an intuitive, user-friendly platform that seamlessly integrates social networking, personalized food discovery, and commerce
Challenge 2
Developing a sophisticated AI recommendation engine that considers dietary preferences, restrictions, and user behavior
Challenge 3
Building a scalable architecture to support rapid growth and diverse user roles
Challenge 4
Implementing a fair and engaging rating system that benefits both consumers and businesses
Challenge 5
Creating monetization opportunities for content creators while maintaining platform integrity
The Solution
Our Approach
Developed a comprehensive, multi-role ecosystem comprising.
Key Features Delivered
Technical Stack
React Native
Node js
Firebase Firestore
Google Vertex AI
Firebase Authentication
Stripe
Google Analytics 4 and Firebase Analytics
Google Cloud Platform
Firebase Realtime Database
Implementation Process
01
Discovery & Architecture Planning
User research and persona development
Technical architecture design
AI recommendation strategy
Multi-role system planning
Core Platform Development
User authentication and profile management
Role-based interface development
Content creation and sharing functionality
Rating system implementation
02
03
Advanced Features Integration
AI recommendation engine development
Leaderboard algorithms implementation
Commerce functionality integration
Curator tools and monetization system
Testing & Optimization
User acceptance testing across different roles
Performance optimization
AI recommendation tuning
Security testing
04
05
Deployment & Launch Support
Production deployment
Monitoring and performance tuning
User onboarding
Post-launch support and optimization
Architecture & Technical Innovations
Serverless Architecture
40% lower infrastructure costs (pay-per-use)
Reliable with built-in redundancy
Enables rapid feature deployment
Auto-scalable for viral traffic
AI Recommendation Engine
Personalized suggestions via multi-factor algorithm
Learns from user behavior for smarter results
Explains why items are recommended
Real-time, efficient processing
Multi-Role System
Hierarchical data model for complex relationships
Role-based permissions and smooth switching
One account, multiple roles
Integration Ready
Built to scale and integrate with third-party services
API-first design and webhook support
Works across devices