Frameworks · ReferenceFramework
LlamaIndex
Retrieval-centric framework; connectors and indexes turn proprietary documents into agent context.
01
Suitability
Best for
RAG and document-driven agents grounded in proprietary data.
Watch out
Retrieval throughput depends on the chosen vector store.
02
Architecture & integrations
Data connectors + indexing pipelines + query engines; agent workflows layered on retrieval. Knowledge assistants, enterprise search, document-heavy RAG.
03
Technical profile
Approach
Retrieval-first: connectors, indexes, query engines, with agents on top.
Control & learning curve
Flat–medium; query engines are high-level, agent workflows lower-level.
Performance
Strong for document-heavy/RAG workloads; throughput depends on the vector store.
Keep exploring