LlamaIndex
Data-oriented agent and workflow framework for building LLM agents over private data, tools, retrieval, and workflows.
Best for
Deployment targets
Source boundary
LlamaIndex documentation describes agents, workflows, tools, and data-connected agent patterns.
| Source | Type | Verified | Citation |
|---|---|---|---|
| LlamaIndex docs | docs | 2026-09-15 | Official documentation for LlamaIndex agents and workflows. |
| LlamaIndex GitHub | github | 2026-09-15 | Public repository for the LlamaIndex framework. |
Relationships
| Type | Source | Target | Confidence |
|---|
Compatibility
| Type | Target | Status | Evidence |
|---|---|---|---|
| runtime_deployment | serverless-container-runtime | supported | LlamaIndex agent and workflow applications can run as service or container deployments for data-connected agent workflows. |
Which constraints matter most for data-analysis agents?
Data-analysis agents should prioritize structured output, dataset access boundaries, evaluation hooks, and explicit review for filesystem or API side effects.
When should teams choose LangChain / LangGraph over LlamaIndex?
Choose LangChain / LangGraph when graph-style control flow and broad integrations dominate. Choose LlamaIndex when document context, private data, and retrieval-first workflows are the center of the system.
What is the practical difference between LlamaIndex and Haystack?
LlamaIndex is a strong fit when data-connected agent workflows and document context are central. Haystack is a strong fit when production RAG pipelines and component composition are the dominant shape.
What makes a RAG workflow agent-ready?
A RAG workflow is agent-ready when retrieval context, source provenance, evaluation, deployment shape, and data access risk can be inspected from shared structured metadata.
What should a research-agent stack verify before implementation?
Verify retrieval sources, browser automation boundaries, citation handling, and whether the selected framework can keep source provenance visible across multi-step synthesis.