LlamaIndex

Founded by Jerry Liu in 2023

Parse complex documents and tables into clean data for language models

Pricing model

Free Tier, Paid

Rating

★ People love it

Time to value

Quick Setup (< 1 hour)

You can use LlamaIndex to convert unstructured documents like PDFs, scans, and financial spreadsheets into structured context for language models. It provides specialized agents to parse messy tables, charts, and handwritten text with high precision. You can extract structured schemas directly from documents without training custom machine learning models. The system also chunks, embeds, and indexes data so your retrieval-augmented generation pipelines fetch relevant answers quickly. Additionally, you can run lightweight document parsing locally on your own infrastructure without making external cloud API calls.

What LlamaIndex does

Parse nested tables from PDF reports into clean MarkdownExtract chart data into structured formatsConvert handwritten doctor notes into plain textSegment long documents based on natural language descriptionsChunk and embed documents for retrieval-augmented generation pipelinesClassify incoming documents automatically by layout and topicParse local files on private infrastructure without cloud dependenciesAgentic OCR that handles complex multi-column layouts and nested tablesAutomatic extraction of structured JSON from documents using custom schemasBuilt-in parsing for handwritten text and low-quality scansAutomated error-correction loops to verify document parsing accuracyFast open-source local parsing without external API tokens via LiteParseEnterprise chunking and embedding pipelines for RAG applicationsSupport for more than 50 unstructured file typesDocument splitting and natural language classification rules