AI-Powered SaaS Music Platform / Recurring Revenue

Broker presents a cutting-edge AI-powered social media platform designed for Musicians, Labels, and Independent Artists. This platform offers a revolutionary way for artists to connect directly with fans, monetize their content, and gain exposure through an intelligent recommendation system and gamified interactions.

The platform features an in-built recommendation system that generates personalized home feeds and content/media-wise recommendations. It also includes a gamified rewarding system that tracks and automatically rewards users with in-app currencies and levels. The robust back-end infrastructure leverages serverless functions, standalone APIs, CDN, and extensive caching.

The scalable infrastructure can handle 5 million media files and support 2-3 million active users at any given time without significant cloud costs. A buyer will receive full access to the current infrastructure, along with six months of development support that includes a dedicated team of five engineers who built the system.

The platform’s core strength lies in its sophisticated infrastructure, allowing for seamless scalability and customization. The platform’s front-end collects and processes key user engagement metrics, including user session data, optimized content loading, scroll tracking, content read detection, and content interaction analysis. Firestore NoSQL database is used for efficient data storage, with adaptive push strategies to minimize redundant writes and optimize performance. Technologies used include React, JavaScript, Node.js, Firestore Database, and Serverless Functions.

User segmentation and grouping are performed in real-time, with user data streamed from Firestore to BigQuery for categorization based on product/content interactions. Optimized querying and cached data reduce computational load and improve recommendation accuracy. The recommendation system generates contextual recommendations based on session data, time of day, and past interactions, with feed personalization dynamically generated based on recent engagement. Efficient computation is achieved through vector embedding search with caching for performance optimization. Technologies used include Python API, TensorFlow, Torch, Sentiment Analysis Model, KeyBERT, and SentenceTransformers.

The gamification system enhances user engagement by tracking user interactions with trending content, total active time, and overall activity, allowing for dynamic role/level upgrades and in-app currency rewards. Content delivery is optimized through distributed load handling, with heavy computation tasks managed by standalone Python APIs, BigQuery, and Firestore.

Adaptive media delivery ensures seamless performance, with images client-side compressed and served based on device capabilities, while audio/video files are stored in HLS format for smooth streaming. Google Cloud CDN secures content access with token-based authentication and cookie-based access control. Technologies used include Google Cloud Storage, Google Cloud CDN, and Firestore.


Listing ID: SF453