---
LinkTitle: LangChain
Title: Redis with LangChain
categories:
- docs
- integrate
- oss
- rs
- rc
description: Build AI applications with Redis and LangChain
group: ai
stack: true
summary: Use Redis as a vector database and memory store for LangChain AI applications.
title: LangChain
type: integration
weight: 30
---

Integrate Redis with LangChain to build powerful AI applications with vector search, semantic caching, and conversation memory.

## Overview

Redis integration with LangChain enables you to build sophisticated AI applications with persistent memory, vector search capabilities, and semantic caching. Perfect for chatbots, recommendation systems, and AI-powered applications requiring fast data retrieval.

## Key Features

- **Vector Search**: High-performance similarity search for embeddings and AI models
- **Conversation Memory**: Persistent chat history and context for AI conversations
- **Semantic Caching**: Cache AI model responses for faster inference and cost reduction
- **Document Storage**: Store and retrieve documents for retrieval-augmented generation (RAG)
- **Real-time Updates**: Live data updates for dynamic AI applications
- **Scalable Architecture**: Handle large-scale AI workloads with Redis performance
- **Multi-modal Support**: Support for text, image, and other data types
- **LangChain Integration**: Native integration with LangChain's ecosystem and tools

## Getting Started

Learn how to [build AI chatbots with Redis and LangChain](https://redis.io/learn/howtos/solutions/vector/gen-ai-chatbot) for enhanced AI experiences.