
LangChain is an open-source framework for building applications powered by large language models, enabling chaining, memory, agents, and integrations for advanced AI workflows.
LangChain is an open-source framework designed to simplify the development of applications powered by large language models (LLMs).
What is it?
LangChain is a developer framework that provides abstractions and tools for connecting language models with external data sources, APIs, tools, and application logic. It focuses on orchestrating complex LLM workflows rather than just model inference.
What does it do?
LangChain enables developers to build AI applications using concepts such as chains, agents, memory, retrieval-augmented generation (RAG), and tool calling. It helps manage prompts, context, reasoning steps, and integrations with databases and APIs.
Where is it used?
LangChain is widely used in AI assistants, chatbots, knowledge-base systems, document analysis tools, autonomous agents, internal enterprise copilots, and LLM-powered SaaS products.
When & why it emerged
LangChain emerged in 2022 as large language models became widely accessible via APIs. It was created to address the need for structured, maintainable, and scalable ways to build real-world LLM applications beyond simple prompt-response interactions.
Why we use it at Internative
At Internative, we use LangChain to design and orchestrate complex AI workflows, including RAG systems, AI agents, and enterprise assistants. Its modular architecture allows us to rapidly prototype and scale LLM-based products with clean system design.