Intelligent real-time recommendation system

This is a submission for the Redis AI Challenge: Real-Time AI Innovators.

This project demonstrates the use of Redis as the foundation for an intelligent recommendation system that operates in real time. The project uses Redis vector search, semantic caching, and streaming data processing to generate personalized recommendations.

Project features

• Redis Vector Search: Using Redis Vector Search for semantic search and recommendations based on vector embeddings.
• Semantic Caching: Optimizing LLM performance by caching semantically similar queries.
• Streaming data processing: Using Redis Streams for real-time data processing.
• Personalized recommendations: Generating personalized recommendations based on user interaction history.
• Real-time analytics: Tracking and analyzing user interactions in real time.

Technical stack

What I Built

Demo

How I Used Redis 8