LlamaIndex
AI / LLMA data framework for connecting LLMs to private and enterprise data — ingestion, indexing, retrieval, and agent workflows over your own content.
Overview
LlamaIndex specializes in the retrieval half of AI applications: getting documents, databases, and APIs into a form an LLM can reason over reliably. It covers ingestion, chunking, indexing, and query strategies, and has grown agent and workflow features on top. For enterprises building RAG over internal knowledge, it is one of the two reference frameworks alongside LangChain. The managed LlamaCloud handles parsing and indexing of messy documents at scale. Retrieval quality remains your problem — the framework gives you the tools, not the evals.
Pros & Cons
Pros
- Deep, well-documented retrieval toolkit
- Handles complex and messy document types
- Managed LlamaCloud option for scale
- Large ecosystem of connectors
Cons
- Retrieval quality still depends on your tuning and evals
- Overlapping features with LangChain can confuse
- Fast-moving API surface
Workflows that use LlamaIndex
Get a new AI workflow each week — many feature LlamaIndex and other tools in this category.