Redis AI video collection
Watch video tutorials and demos showcasing Redis in AI applications, from vector search to RAG implementations.
Explore our collection of video tutorials and demonstrations showcasing how Redis powers AI applications. From vector search fundamentals to advanced RAG implementations, these videos provide practical insights and hands-on examples.
| Long-Term Memory with LangGraph | Short-Term Memory with LangGraph | What is semantic search? |
| Learn how to implement long-term memory capabilities in AI agents using LangGraph. This video shows you how to build AI systems that can retain and recall information across extended interactions. | Want your AI agents to remember what users tell them? Short-term memory is the key to natural conversations, and in this tutorial, you'll learn how to implement it with LangGraph. | Traditional search matches words — but what if your AI app could match meaning instead? This video explains how semantic search works and why it's essential for modern AI applications. |
| What is a semantic cache? | Building a RAG Pipeline from Scratch with RedisVL | What is a vector database? |
| What if you could skip redundant LLM calls and make your AI app faster, cheaper, and smarter? This video breaks down semantic caching and shows how it can transform your AI applications. | Unlock the Power of Retrieval-Augmented Generation (RAG) with RedisVL. This tutorial will show you how to build a complete RAG pipeline from scratch using Redis as your vector database. | Vector databases have been trending recently as they power modern search, recommendations, and AI-driven applications. Learn what vector databases are and how they work. |
| Building the future Architecting AI Agents with AWS, LlamaIndex and Redis | Building AI Apps using LangChain | Resources to Learn AI with Redis |
| The ins and outs of AI agents: understand their role in breaking down tasks into manageable components for better performance. Learn how to architect AI agents using AWS, LlamaIndex, and Redis. | This series of videos dives into the integration between LangChain and Redis to power AI applications that need runtime speed, scalability, and intelligent data management. | This video shows which resources you can use to learn AI with Redis and build powerful AI applications. |
Additional Resources
| LLM Session Management with Redis | A Semantic Cache using LangChain | Similarity Search using Vector Store |
| Developers building AI applications require a way to store the conversation history between an LLM and a user. This is important to provide context and maintain coherent conversations across sessions. | One common concern of developers building AI applications is how quickly answers from LLMs will be served to their end users, as well as how much it will cost. Learn how to implement semantic caching using LangChain and Redis. | Similarity search is one of the most popular use cases for developers building AI applications. It allows users to perform searches that can find semantically similar content using vector embeddings. |
| Create a New Database on Redis Cloud | Redis Insight: A Developer's Deep Dive | Redis + Amazon SageMaker for real-time fraud detection demo |
| Learn how to create a new database on Redis Cloud in this step-by-step tutorial. Perfect for developers getting started with Redis Cloud for their AI and data applications. | This video breaks down Redis Insight and shows developers how to use this powerful tool for database management and development. | See how Redis integrates with Amazon SageMaker to build real-time fraud detection systems. This demo shows practical applications of Redis in machine learning and AI-powered fraud prevention. |
| Redis + Amazon Bedrock in two minutes | ||
| AWS has announced Redis Cloud as one of the few supported vector databases supported for Amazon Bedrock. Learn how to integrate Redis with Amazon Bedrock for your generative AI applications. |
Getting Started
Ready to start building AI applications with Redis? Check out our: