LangChain
Framework for LLM application development. We help organisations build production AI applications using LangChain for chains, agents, retrieval-augmented generation and complex workflows.
What makes LangChain different
LangChain provides composable building blocks for LLM applications, making it faster to build, test and deploy complex AI workflows.
Composable chains
Build complex LLM workflows by chaining together prompts, models, tools and retrieval steps in a modular, testable architecture.
Model agnostic
Swap between OpenAI, Anthropic, Google and open-source models without rewriting application logic. Avoid vendor lock-in.
Rich ecosystem
Active community and extensive documentation. Integrations with vector databases, tools, APIs and data sources out of the box.
Use cases for LangChain
RAG applications
Build retrieval-augmented generation systems that ground AI responses in your proprietary data and documents.
AI agents
Create autonomous agents that use tools, make decisions and execute multi-step workflows with LangChain's agent framework.
Chatbots with memory
Conversational AI that maintains context across interactions with configurable memory and retrieval strategies.
Document processing
Extract, transform and analyse documents using LangChain's document loaders, splitters and chain patterns.
Structured output generation
Generate structured data from unstructured inputs using output parsers and validation chains.
Multi-model orchestration
Route tasks to different models based on complexity, cost and capability requirements within a single application.
Frequently Asked Questions
What is LangChain?
LangChain is an open-source framework for building applications with large language models. It provides composable components for chains, agents, retrieval and memory.
How can The Bot Forge help with implementation?
Our team provides end-to-end support, from initial architecture and setup to custom development and ongoing maintenance. We help you build production-ready LangChain applications.
What are the typical use cases?
LangChain is commonly used for RAG applications, AI agents, conversational AI with memory, document processing and multi-model orchestration in production systems.
Build with LangChain
Ready to build production LLM applications? We can help you architect, develop and deploy with LangChain.