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WhatsitAI: ID & Value Anything
WhatsitAI is an innovative mobile application developed by our company for the second-hand and antique market. The application uses advanced artificial intelligence technologies for instant identification and valuation of any items using a smartphone camera. The main concept of the product is to help users make informed decisions when buying and selling items at flea markets, thrift stores, garage sales, and other venues. The application has become an indispensable assistant for those who engage in thrifting as a hobby or as an additional source of income.
Key Features
Luxury Product Marketplace
Users can buy and sell high-end items like bags, shoes, watches, and accessories.
Advanced Search & Filters
Easily find items by category, brand, price, condition, and more.
Secure Buyer-Seller Interaction
In-app chat, profile verification, and meeting booking for trust and clarity.
Personalized Experience
Smart search, wishlists, push notifications, and tailored recommendations.
Our Role
Our team was responsible for the full development cycle of the WhatsitAI mobile application, using the Flutter framework to ensure cross-platform compatibility.
Technical Implementation
During the development of WhatsitAI, we applied a cross-platform approach that allowed us to simultaneously create the application for Android and iOS platforms using a single codebase in Flutter. This significantly optimized development time and ensured functionality consistency between platforms. We paid special attention to AI service integration, implementing complex machine learning and computer vision algorithms for accurate item identification. The team also focused on performance optimization, ensuring fast image processing and instant result delivery, which is critically important for user experience. Additionally, we created an intuitive and user-friendly UX/UI design adapted for different categories of users – from beginners to professional collectors.
Architectural Solutions
When developing the application architecture, we chose a modular approach that ensures ease of maintenance and system scalability in the future. Integration with cloud services became the foundation for implementing the server-side that processes AI requests and ensures high-speed operation of recognition algorithms. We also implemented a multi-tier monetization system with various subscription and in-app purchase options, providing flexibility for users and stable revenue for the business. Additionally, a comprehensive analytics and metrics system was integrated to track user behavior, allowing continuous product improvement based on real usage data.
Results and Achievements
Technical Achievements:
- Successful launch on two platforms: simultaneous publication in Google Play Store and Apple App Store
- High performance: optimized speed of recognition and image processing
- Operational stability: minimal number of crashes and high stability rating
Business Results:
- Positive user feedback: high ratings in both app stores
- Active user base: successful user acquisition and retention
- Monetization: effective implementation of multi-tier subscription system ($8.99/month, $49.99/year)
- Market position: establishment as a leader in the AI identification niche for thrifting
Conclusion
The WhatsitAI project demonstrates the ability of our team to create innovative, technologically complex mobile solutions that have a real impact on users’ lives and create new market opportunities. Using Flutter allowed us to ensure high product quality with optimal time and resource expenditure on development.