Build a Cost-Optimized AI API with Redis & Model Routing

In this video, we’ll build a production-style AI API that intelligently reduces LLM costs using Redis caching and model routing. Instead of sending every request to an expensive AI model, we’ll design an API that can: ⚡ Cache repeated AI responses with Redis 💰 Reduce unnecessary LLM API costs 🧠 Route requests to different models based on the task 🔄 Use cheaper models for simpler requests 🚀 Use more capable models when higher-quality reasoning is required 🔌 Integrate everything into a FastAPI-based backend 🏗️ Design the architecture with production use cases in mind You’ll learn how caching + intelligent model selection can make AI applications faster, cheaper, and more scalable. If you're learning FastAPI, GenAI, LLM APIs, Redis, AI agents, and backend development, this project will help you understand how these technologies fit together in a real-world architecture. 👍 Like the video 💬 Comment your questions 🔔 Subscribe for more backend + GenAI projects #FastAPI #Redis #GenAI #LLM #Python #AgenticAI #LLM #AI #aicosts