What is LangChain?
LangChain is the leading framework for building AI-powered applications. It provides the plumbing to connect language models to your data, tools, and workflows — handling retrieval, memory, chaining, and agent logic so your AI application can do more than answer questions.
How We Use It
We use LangChain (and LangGraph for complex agent workflows) to build production AI applications that combine multiple models, data sources, and tools into cohesive systems. Think: an AI that reads your documentation, queries your database, uses your APIs, and produces structured outputs — all orchestrated reliably.
What You Can Build
RAG-Powered Knowledge Systems
Build AI that answers questions using your actual documents, manuals, and knowledge base. Accurate, grounded responses with source citations — not hallucinations.
Multi-Step AI Agents
Create agents that break down complex tasks into steps, use tools, and make decisions. Research, analyze, summarize, and act — all autonomously.
Document Processing Pipelines
Ingest, parse, and extract structured data from documents at scale using LangChain's document loaders and processing chains.
AI Workflow Orchestration
Connect multiple AI models and tools into a single workflow — use GPT for generation, Claude for analysis, embeddings for retrieval, all coordinated by LangChain.
Why LangChain?
Production-grade RAG pipelines with vector databases and retrieval optimization
Multi-model orchestration — use the right AI for each task
Built-in memory and conversation management for stateful applications
LangGraph enables complex agent workflows with branching and human-in-the-loop