LangGraph has integrated Redis' powerful memory capabilities to build more effective AI agents with persistent memory across conversations and sessions. This collaboration enables developers to leverage thread-level persistence and cross-thread memory, allowing agents to remember context, learn from experiences, and make better decisions over time. The `langgraph-checkpoint-redis` package provides two core capabilities: RedisSaver for thread-level persistence and RedisStore for cross-thread memory. These features support both synchronous and asynchronous APIs, making it easy to adopt the integration into various application architectures. With simplicity and clarity in mind, this package gives developers straightforward, performant memory solutions that can be composed into sophisticated agent architectures. By combining LangGraph's agentic workflows with Redis' powerful memory capabilities, developers can build AI agents that feel more natural, responsive, and personalized.