AI-Driven Content Recommendation Engine for Streaming Platform

Our streaming platform is looking to enhance its user engagement by implementing an AI-driven content recommendation system. As a scale-up company, we aim to integrate sophisticated algorithms that personalize user experiences based on viewing history, preferences, and real-time interactions. This project will employ microservices architecture, allowing it to seamlessly scale and adapt to fluctuating user demands. The solution will utilize Kubernetes for efficient deployment and management of containerized applications, Redis for fast caching solutions, ElasticSearch for powerful search capabilities, and WebSockets for real-time data exchange. Additionally, the project will include secure payment integrations using Stripe for premium features and Auth0 for robust user authentication. The successful implementation of this project will position our platform as a leader in personalized streaming experiences, attracting and retaining a larger user base and increasing revenue through enhanced engagement.