LangChain / LangGraph
advancedThe developer framework for building production AI agents and pipelines.
LangChain is the most widely adopted open-source framework for building applications powered by large language models. LangGraph extends it with stateful, multi-actor agent orchestration — enabling complex AI systems where multiple agents collaborate, use tools, and maintain memory. Together with LangSmith for observability and debugging, they form a complete development stack for production AI applications. PxlPeak uses LangChain/LangGraph to build custom AI systems that go beyond what no-code platforms can handle — RAG pipelines, multi-agent workflows, custom tool chains, and enterprise AI applications.
90K+
GitHub stars
100K+
Developers using LangChain
#1
Most popular LLM framework
MIT
Open-source license
Key Features
Modular framework for chains, agents, tools, and retrieval systems
LangGraph for stateful multi-agent orchestration with cycles and branching
LangSmith for tracing, debugging, evaluation, and monitoring
Support for all major LLM providers (OpenAI, Anthropic, Google, open-source)
RAG (Retrieval-Augmented Generation) with vector stores and document loaders
Open-source with permissive MIT license
Use Cases We Implement
Build RAG systems for enterprise knowledge bases and document Q&A
Create multi-agent systems for complex business process automation
Develop custom AI-powered tools and internal applications
Prototype and iterate on LLM applications with rapid experimentation
How We Implement LangChain / LangGraph
Assess
We analyze your business needs and how LangChain / LangGraph fits into your workflow.
Configure
Set up LangChain / LangGraph with custom settings, integrations, and data connections.
Integrate
Connect to your existing tools — CRM, helpdesk, email, and more.
Train & Launch
Train your team, document everything, and provide ongoing support.
Services That Use LangChain / LangGraph
AI Workflow Automation
Eliminate repetitive tasks with intelligent automation workflows that connect your tools and run your business on autopilot.
AI Chatbots & Agents
Custom AI chatbots trained on your business data that qualify leads, book appointments, and handle support 24/7.
AI Integration
Connect AI tools to your existing tech stack — CRM, helpdesk, email, payments, and more — for seamless operations.
Compare LangChain / LangGraph
Frequently Asked Questions
When should I use LangChain instead of n8n or Zapier?
Use LangChain when you need custom AI logic that goes beyond visual automation — RAG systems, multi-agent orchestration, custom tool chains, or deep integration with proprietary systems. n8n and Zapier are better for standard business automation with AI enhancement.
Do we need developers to use LangChain?
Yes. LangChain is a developer framework (Python and JavaScript). PxlPeak provides the engineering team to build, deploy, and maintain LangChain-based applications — so you get custom AI without needing in-house AI engineers.
What is the difference between LangChain and LangGraph?
LangChain provides the building blocks (chains, tools, retrievers). LangGraph adds stateful orchestration for multi-agent systems with cycles, branching, and human-in-the-loop patterns. PxlPeak uses both together for production AI systems.
How long does a LangChain project take?
PxlPeak delivers LangChain/LangGraph projects in 3-6 weeks depending on complexity. Simple RAG systems take 3 weeks. Multi-agent systems with custom tools and integrations take 4-6 weeks.
What is LangSmith and do we need it?
LangSmith is LangChain's observability platform for tracing, debugging, and evaluating AI applications. PxlPeak considers it essential for production deployments — it provides the visibility needed to monitor accuracy, debug issues, and optimize performance.
