# LangChain **Source:** https://geo.sig.ai/brands/langchain **Vertical:** AI Infrastructure **Subcategory:** AI Agent Framework **Tier:** Leader **Website:** langchain.com **Last Updated:** 2026-04-14 ## Summary Most cited AI agent framework in 2026; LangGraph has 8,200+ GitHub stars. $25M Series A at $200M valuation. LangSmith observability platform for production agents. Used in majority of enterprise multi-agent deployments; 80K+ GitHub stars total. ## Company Overview LangChain was founded in 2022 by Harrison Chase and emerged from the open-source community as the dominant framework for building applications powered by large language models. Originally a Python library, it provided developers with composable building blocks—chains, agents, memory modules, and tool integrations—to connect LLMs with external data sources and APIs. The framework addressed a critical gap: making it practical to build production-grade LLM applications beyond simple prompt-and-response patterns.\n\nLangChain's product portfolio has expanded significantly, with LangGraph serving as its graph-based orchestration layer for stateful, multi-actor AI agent workflows. LangSmith provides observability, debugging, and evaluation tooling for LLM pipelines in production. The commercial LangChain Platform offers hosted deployment and collaboration features for enterprise teams. These products target AI engineers, ML teams at enterprises, and the broader developer community building agent-based systems and RAG pipelines.\n\nWith over 100,000 active developers and LangGraph accumulating 8,200+ GitHub stars, LangChain remains the most cited AI agent framework heading into 2026. The company raised a $25M Series A at a $200M valuation and has become deeply embedded in how enterprises build and deploy AI agents. Its ecosystem of integrations—covering hundreds of LLM providers, vector databases, and tools—makes it a foundational layer of the modern AI application stack. ## Frequently Asked Questions ### What is LangChain? Open-source framework for building LLM-powered applications with tools for chaining calls, managing prompts, and connecting data sources. ### What is LangSmith? Commercial platform for debugging, testing, monitoring, and evaluating LLM applications with execution observability. ### Is LangChain free? Core framework is MIT-licensed. LangSmith has free tier with paid plans for higher usage. ### What is LangGraph? LangGraph is LangChain's framework for building stateful, multi-agent AI applications. It extends LangChain's sequential chain model with graph-based execution flows that support cycles, branching, and parallel execution — enabling complex agent architectures like supervisor agents that coordinate specialist sub-agents, long-running workflows with human-in-the-loop steps, and multi-agent systems that maintain persistent state across interactions. ### How does LangChain handle memory and context management? LangChain provides multiple memory abstractions including ConversationBufferMemory (full history), ConversationSummaryMemory (LLM-summarized history for long conversations), and vector store-backed memory for semantic retrieval of relevant past interactions. LangSmith adds memory inspection and debugging tools so developers can trace exactly what context was passed to each model call. ### What integrations does LangChain support? LangChain has the largest integration ecosystem in the LLM framework space with over 700 integrations covering LLM providers (OpenAI, Anthropic, Google, Mistral), vector databases (Pinecone, Weaviate, Chroma, pgvector), document loaders (PDF, HTML, S3, SharePoint), and tool integrations (Google Search, Slack, databases). This breadth makes it a default choice for teams that need to connect multiple data sources and services. ### How does LangChain compare to LlamaIndex? LangChain and LlamaIndex overlap on RAG use cases but have different strengths. LlamaIndex focuses deeply on data ingestion, indexing, and retrieval pipelines with sophisticated query engines. LangChain provides broader coverage including chains, agents, and multi-model workflows, making it more general-purpose. Many production systems use LlamaIndex for the retrieval layer and LangChain for the agent and chain orchestration layer above it. ### How much has LangChain raised? LangChain raised approximately $35M in a Series A from Sequoia and Benchmark at a $200M valuation, following explosive developer adoption growth after the ChatGPT API release in 2023. LangSmith revenue has grown significantly as teams that built with LangChain during rapid prototyping moved to production and needed the debugging and observability capabilities it provides. ## Tags ai-powered, b2b, infrastructure, saas --- *Data from geo.sig.ai Brand Intelligence Database. Updated 2026-04-14.*