Introduction
Chooze — AI Beverage Recommendations. A health-focused mobile app recommending beverages based on user health data and preferences. I implemented the back-end API server, handling user profiles, recommendation engine logic, and configuration inputs. The system utilized a rule-based engine to tailor results and supported content management for health articles and tips.
The Challenge & Solution
As the Senior Software Engineer, I steered the technical direction, defining system boundaries and ensuring the solution adhered to best practices in distributed systems design. Artificial Intelligence algorithms were integrated to personalize user experiences and optimize decision-making engines.
Technologies & Architecture
We utilized Node.js, TypeScript, PostgreSQL, Redis to construct the solution. Node.js enabled us to share logic between frontend and backend, fostering a unified development ecosystem. TypeScript brought type safety to the codebase, significantly reducing runtime errors and improving developer productivity. PostgreSQL offered the reliability and advanced querying capabilities needed for our structured data. Redis was utilized as a high-performance caching layer to offload database pressure and speed up read operations.
Key Highlights
- User taste profiles
- Feedback loops
- Ranking models
Impact
This project not only met its initial requirements but also laid the groundwork for future scalability.