LangChain
Build, test, and deploy reliable AI agents
Founded
2022
Starting Price
\u00240
Category
AI Chatbots & Agents
Last updated March 8, 2026
About LangChain
LangChain is an open-source framework and engineering platform for building AI-powered applications. It provides standardized, model-agnostic interfaces for connecting LLMs with data sources and APIs, enabling developers to create sophisticated agents, RAG pipelines, and multi-step workflows with composable components.
Pros & Cons
Pros
- Simplifies building complex AI applications by connecting LLMs with data and APIs through standardized interfaces
- Massive ecosystem with 700+ integrations for LLM providers, vector stores, tools, and data sources
- LangGraph enables sophisticated multi-agent orchestration with full control and observability
- Model-agnostic design allows easy switching between LLM providers without code rewrites
- LangSmith provides excellent production observability with tracing, evaluation, and debugging tools
Key Features
LangChain Framework
Open-source Python and JavaScript libraries with composable components for building LLM applications
LangGraph
Framework for building stateful, multi-agent AI applications with full control over agent behavior and orchestration
LangSmith
Observability and evaluation platform for tracing, debugging, testing, and monitoring LLM applications in production
RAG Support
Built-in support for Retrieval-Augmented Generation with document loaders, vector stores, and retrieval chains
Model Agnostic
Standardized interface supporting OpenAI, Anthropic, Google, and dozens of other LLM providers
Memory Management
Advanced conversation memory and state management for building context-aware AI agents
Tool Integration
Connect LLMs to external tools, APIs, databases, and custom functions through a unified interface
Pricing
Developer
\u00240
- 5,000 traces/month
- 14-day data retention
- 1 seat
- Basic evaluations
- Community support
Best For
Conversational AI Agents
Build sophisticated chatbots and virtual assistants with memory, tool use, and multi-step reasoning capabilities
RAG Applications
Create retrieval-augmented generation systems that ground LLM responses in your organization's proprietary data
Enterprise Copilots
Develop AI copilots for internal workflows like code review, document analysis, and customer support automation
Multi-Agent Systems
Orchestrate multiple AI agents working together on complex tasks using LangGraph's stateful workflow engine
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