Build Agentic RAG with TypeScript (Memory Agents)
Retrieval Augmented Generation (RAG) is a powerful way to build AI applications that use your data effectively. In this hands-on workshop, you'll learn how to create advanced RAG systems that do more than just the basics.
Memory agents are AI agents that have human like long-term memory. You can train AI agents with your data and knowledge base without having to manage vector storage, servers, or infrastructure.
Langbase memory agents represent the next frontier in semantic retrieval-augmented generation (RAG) as a serverless and infinitely scalable API designed for developers. 30-50x less expensive than the competition, with industry-leading accuracy in advanced agentic routing and intelligent reranking.
You will acquire the skills to:
Implement AI memory architectures
Integrate and utilize custom embedding models
Ingest and manage documents within AI memory structures
Execute advanced retrieval operations to obtain augmented data chunks
Generate comprehensive responses using LLMs
Everyone is welcome to join this event, whether you're an experienced developer or an aspiring AI engineer—no matter your background. Feel free to share the invite link with others.
To get the most out of the session, make sure you have a code editor and Node v20+ installed beforehand. You should also be familiar with basic JavaScript and using the command line.
This isn't just a presentation—it's a hands-on workshop where you'll leave with building a scalable RAG system.