LangChain is a widely used open-source framework for building applications powered by large language models, and it has grown into a full platform for what the company calls agent engineering. The core library provides abstractions for chains, agents, memory, retrieval, and tool use that dramatically reduce the boilerplate of building LLM-powered software.
The broader stack has three main parts: the LangChain framework for composing LLM workflows, LangGraph for building stateful, multi-agent orchestration, and LangSmith for observability, evaluation, and monitoring of agents in production. Together these move teams from quick prototypes to reliable, production-grade AI agents with testing and tracing built in.
LangChain was founded in 2022 by Harrison Chase and rapidly became one of the most popular open-source projects in AI, accumulating well over 100,000 GitHub stars and very large monthly download volumes. Its open-source momentum created a strong distribution funnel into the commercial LangSmith and LangGraph products.
On funding, LangChain closed a $125 million Series B in October 2025 at a $1.25 billion valuation, entering unicorn territory roughly two and a half years after launching as an open-source project. The round was led by IVP alongside existing backers Sequoia, Benchmark, and Amplify, plus new investors CapitalG and Sapphire Ventures. The company reported annualized recurring revenue in the low-to-mid tens of millions at the time, with broad enterprise adoption including a large share of the Fortune 500.
LangChain's differentiation is the combination of ubiquitous open-source adoption with a commercial observability and orchestration layer. Rather than being only a framework, it offers an end-to-end path — build with LangChain, orchestrate with LangGraph, and evaluate and monitor with LangSmith — competing with both open-source agent frameworks and proprietary LLM-ops platforms.