Personalized Audio App

Overview

A fast-scaling audio streaming startup aimed to offer deeply personalized listening experiences to its diverse user base. They partnered with UpRaqx to develop an AI-driven recommendation engine that adapts to individual preferences in real-time. The goal was to improve retention, listening duration, and overall engagement. The product needed to scale across devices and offer dynamic playlisting with minimal latency. Our team led full-cycle product development — from architecture to launch — optimizing the core logic using GenAI.

Tech Stack

Industry

Audio Streaming / Entertainment

Regions

North America

Duration

5 Months

Key Highlights

GenAI Recommendation Core

Built a proprietary engine using GenAI models that learns from user mood, genre affinity, and contextual behavior.

Smart Playlist Curation

Enabled real-time dynamic playlists based on time-of-day and user activity (e.g., workout, relax).

Mobile-First Design

Delivered a lightweight, intuitive React Native app with offline listening and smooth UX.

Latency Optimization

Reduced recommendation latency from 2.5s to 400ms using AWS Lambda and edge caching.

Increased Engagement

32% boost in listening time and 18% improvement in daily active users within the first 60 days.

Challenges

Cold Start Problem

Lack of historical data for new users made personalization difficult in early usage.

Scalable Architecture

Needed a system that could scale horizontally with user base growth.

Data Processing Lag

Real-time preference updates caused slow refresh in playlist adaptation.

Platform Consistency

Ensuring identical experience across iOS, Android, and desktop.

Privacy Compliance

Handling behavioral data while staying compliant with regional privacy laws.

Content Diversity

Recommender needed to balance popular content and new artist discovery.

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30 +

Years of
Business Experience

1458+

Happy
Customers

12+

Countries with
Happy Customers

1050+

Agile enabled
employees

The Transformation

From generic playlists to hyper-personalized listening journeys.

By reengineering their content delivery pipeline with GenAI, we transformed a static app into a dynamic recommendation powerhouse. Through iterative sprints and continuous data feedback loops, we fine-tuned the algorithm to align with user moods and scenarios.

Introduced contextual GenAI-based user models.
Implemented multi-label genre mapping for accurate recommendations.
Integrated hybrid recommendation system (collaborative + content-based).
Built analytics dashboard for playlist performance tracking.
Automated model retraining pipeline every 72 hours.

Results Achieved

Testimonial

UpRaqx didn’t just build an app — they helped shape our product vision with deep technical insight. Their GenAI expertise changed the way our users interact with content. Retention is up, and the feedback has been phenomenal.

Ethan Williams

Co-founder

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