Jewellery App with Personalised Recommendations
A swipe-based matching app whose recommendation algorithm reaches over 85 % match accuracy. Taken from proof of concept to production in 16 months.
The Challenge
A lifestyle startup wanted to develop a mobile app that delivers personalized jewelry recommendations based on individual style preferences. The core challenge was building a recommendation algorithm that learns from user behavior and generates relevant suggestions.
Our Approach
As lead engineer, we developed a swipe-based matching app with a personalized recommendation system. The architecture comprised a modern frontend with intuitive UI/UX, a Directus-based backend for data management, and an AI-powered algorithm that analyzes and refines preferences in real time.
The Results
After 16 months of development, a fully functional matching app with personalized recommendations was delivered. The algorithm achieved a match accuracy of over 85% and was taken from prototype to production-ready solution.
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