LangChain Development

Expert LangChain AI Development

We build production-grade LangChain and LangGraph applications — from autonomous agents and RAG systems to multi-model pipelines and enterprise AI backends. Expert developers, battle-tested code.

LangChain · LangGraph · LangSmith · Python · GPT-4o · Claude · Starting at $1,500

LangChainLangGraphLangSmithGPT-4oClaude 3Llama 3PineconePython

What We Build with LangChain

LangGraph Agent Orchestration

Build stateful, multi-step AI agents using LangGraph — with conditional edges, memory, interrupts, and human-in-the-loop nodes.

RAG Pipeline Engineering

Production-grade retrieval systems using LangChain's document loaders, text splitters, vector stores, and retrieval chains.

Multi-Model LLM Integration

Connect GPT-4o, Claude 3, Gemini, Llama 3, and Mistral via LangChain's unified interface. Switch models without rewriting logic.

Tool-Calling & Function Use

Build agents that use web search, code execution, database queries, API calls, and custom tools to complete real-world tasks.

Production-Grade Reliability

We build with LangSmith tracing, error handling, rate limiting, fallback chains, and structured output parsing for production stability.

Streaming & Real-Time Output

Implement streaming responses, token-by-token output, and real-time tool-call visibility for end-user-facing LangChain applications.

LangChain Use Cases We Deliver

Custom AI research agents that search the web and compile structured reports
Enterprise RAG systems trained on SharePoint, Confluence, and internal databases
AI code assistants trained on your proprietary codebase using LangChain + Chroma
Document analysis pipelines for contracts, invoices, and compliance documents
Multi-agent systems where specialized agents collaborate to complete complex tasks
AI backends for SaaS products — from prototype to scalable production API

LangChain Development FAQs

Why use LangChain instead of calling the OpenAI API directly?

LangChain provides memory management, tool-calling abstractions, retrieval chains, agent orchestration, and production tooling (LangSmith) that would take months to build from scratch. It's the right foundation for any serious AI application.

What's the difference between LangChain and LangGraph?

LangChain is the core framework for building LLM applications. LangGraph is built on top of it and adds stateful graph-based agent orchestration — essential for complex multi-step agents with memory, branching, and human-in-the-loop.

Do you build the frontend for LangChain applications too?

Yes — we build full-stack LangChain applications with Next.js frontends, FastAPI Python backends, and streaming UI components. You get a complete, production-ready application.

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Build Your LangChain AI Application

Tell us your use case and stack. We'll design the LangChain architecture and show you a working prototype — free.

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Reach us

Location

Remote team serving US, UK, Europe & Australia

Reply Time

Within 24 hours

Global Coverage

Remote-first agency serving US (EST/PST), UK (GMT), and AUS (AEDT) timezones. We adapt to your schedule.