LangChain

LangChain is an open-source framework for building applications on top of large language models. It provides building blocks for connecting models to your data, tools and workflows: document loaders, retrievers, prompt templates, agents and integrations with vector databases.

How we use LangChain

• Building retrieval-augmented generation (RAG) chatbots that answer from your documents.
• Creating AI workflows that call your APIs, look up records and draft responses.
• Connecting OpenAI, Claude and Gemini models through one consistent interface.
• Adding evaluation and logging so AI answers can be checked and improved.

When LangChain is the right choice

LangChain is useful for AI features with several steps, multiple data sources or tool use. For a simple, single-purpose AI feature, calling the model API directly is often clearer and easier to maintain, and we choose the lighter option when it is enough.

Related: AI development, Vector databases, Python. Talk to our team about your project.

Frequently asked questions

Do I need LangChain to build a chatbot?

No. Simple chatbots can call a model API directly. LangChain helps when a bot needs to search documents, use tools or follow multi-step workflows.

Can a chatbot look up orders or bookings?

Yes. With secure tool integrations, an assistant can query your systems, for example order status, and return the answer within permissions you define.

Is LangChain only for Python?

No. LangChain has Python and JavaScript versions, so it can be used in Python services or Node.js applications depending on your stack.