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AI Glossary
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LangChain

LangChain is an open-source framework for building AI agents and applications using large language models, with support for chaining tools, memory, and logic.

Short definition:

LangChain is a framework for building advanced AI applications that use language models (like GPT) alongside external tools, data sources, and APIs — allowing developers to create AI agents that reason, remember, and act.

In Plain Terms

Out of the box, a model like ChatGPT is powerful — but it can’t access your files, use your software, or call your company’s APIs.
LangChain helps developers connect language models to the real world by:

  • Letting the AI access databases, CRMs, or search engines
  • Storing memory across conversations
  • Chaining multiple steps or actions together
  • Calling tools, calculators, or other functions as needed

It’s like turning a smart chatbot into a fully capable digital teammate.

Real-World Analogy

Think of LangChain as the “plumbing” that connects a brilliant virtual assistant (like GPT) to all the apps and tools it needs to get real work done — like Google Drive, your calendar, or Slack.

Why It Matters for Business

  • Turns AI into business tools
    With LangChain, developers can build agents that read contracts, process orders, or update databases — not just write content.
  • Speeds up development
    LangChain gives dev teams ready-made components to build smarter AI apps faster.
  • Supports complex workflows
    Useful in industries like legal, logistics, finance, or operations where multi-step, rule-based processes need automation.

Real Use Case

A real estate agency builds an AI assistant using LangChain that:

  1. Reads property descriptions
  2. Queries market prices via API
  3. Sends recommendations to clients
  4. Logs activity in the company’s CRM

Without LangChain, this would take heavy custom code. With it, it’s modular, faster, and easier to maintain.

Related Concepts

  • AI Agents (LangChain is one of the most popular toolkits to build them)
  • Function Calling (LangChain makes it easier for AI to know when and how to use external tools)
  • Memory in AI (LangChain helps language models remember previous steps or context)
  • Tool Use / Action Chains (LangChain enables chaining multiple AI actions in one flow)
  • Vector Stores / Document Loaders(LangChain includes built-in tools for working with company documents)