LangGraph Platform vs LlamaIndex
An honest, context-aware comparison. No affiliate links. No paid placements. Just the data that helps you decide.
LangGraph Platform
Managed deployment for LangGraph stateful agents — persistence, streaming, and human-in-the-loop hosting.
LlamaIndex
The data framework for building production RAG applications and AI agents over your own data.
Side-by-Side Comparison
Objective metrics, no spin.
Engineering teams that picked LangGraph for complex stateful agents and want managed deployment without running Postgres, queues, and auth themselves.
Teams not already on LangGraph — switching frameworks for the hosting isn't worth it. Consider Modal or custom infra.
Developers building question-answering systems over enterprise documents, databases, or APIs. The go-to for production RAG pipelines.
Simple single-document Q&A — a direct Claude or GPT API call with the document in context is simpler.
Shared Integrations (2)
Both tools connect to these — you won't lose workflow continuity whichever you pick.
Both suited for: small, medium, large companies
Since both tools target small and medium and large companies, your decision should hinge on the specific use case above rather than company fit. Try the AI Advisor to get a recommendation tailored to your exact stack.
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Other AI Agents & Orchestration Tools to Consider
If neither is the right fit, these are the next best alternatives in the same category.
CrewAI
freeMulti-agent AI framework — build crews of specialized AI agents that collaborate to complete complex tasks.
Microsoft AutoGen
freeMicrosoft's open-source multi-agent framework — agents that converse, code, and execute to solve problems.
Flowise
freeNo-code AI agent builder — drag-and-drop LLM workflows and chatbots without writing code.