LlamaIndex

LlamaIndex is an open-source data framework designed to make it easy to connect large language models (LLMs) with external and private data.

What is it?

LlamaIndex is a data ingestion and indexing framework that structures, indexes, and retrieves data so it can be efficiently used by LLMs. It focuses on enabling context-aware AI by bridging the gap between raw data and language models.

What does it do?

LlamaIndex allows developers to ingest documents, databases, APIs, and knowledge bases, then query them using LLMs through retrieval-augmented generation (RAG). It handles indexing, embeddings, querying, and context management.

Where is it used?

LlamaIndex is used in enterprise knowledge assistants, document search tools, internal copilots, question-answering systems, customer support automation, and AI applications that require accurate, data-grounded responses.

When & why it emerged

LlamaIndex emerged in 2022 alongside the rise of LLM-powered applications. It was created to address the challenge of grounding language models in private, structured, and unstructured data sources.

Why we use it at Internative

At Internative, we use LlamaIndex to build data-aware AI systems, RAG pipelines, and enterprise knowledge solutions. Its strong data abstraction layer allows us to reliably connect LLMs to real-world business data.