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LlamaIndex
LlamaParse uses agentic OCR to process complex documents with tables, charts, and images into AI ready context.

About LlamaIndex
LlamaIndex is a web-based AI platform focused on document processing and AI workflow automation, centered on its LlamaParse document parsing product. It uses agentic OCR to convert complex, unstructured documents—including files with tables, charts, embedded images, and handwritten text—into clean, structured data ready for use with large language models (LLMs) and AI agents.
The platform provides a suite of document intelligence tools beyond core parsing, including schema-based structured extraction, document splitting, automatic classification, and enterprise-grade chunking and embedding pipelines for retrieval-augmented generation (RAG). It also offers LiteParse, an open-source, local document parsing tool that runs without cloud access or LLM token costs, supporting all major document formats. Enterprise users can deploy tools in a secure cloud or fully within their own virtual private cloud (VPC) to meet data residence requirements, with compliance certifications including HIPAA, GDPR, and SOC2.
Key features
- Agentic OCR for layout-aware parsing of complex documents
- Structured extraction of content using user-defined schemas
- Supports 50+ unstructured file types including handwriting
- Open-source LiteParse for local, no-cloud document parsing
- Enterprise deployment with HIPAA, GDPR, and SOC2 compliance
- Document splitting, classification, and RAG indexing tools
- 5x more accurate than competing document parsing APIs
- High accuracy for complex layouts including tables and charts
- Free tier with 10,000 monthly credits (~1,000 pages)
- Enterprise-grade security and compliance certifications
- Core LlamaParse product is not open-source
- Free tier limited to ~1,000 pages per month
LlamaIndex at a glance
- Website
- llamaindex.ai
- Category
- AI & Machine Learning › AI Agents & Automation
- Type
- Website
- Pricing
- Not confirmed. Check the site
- Platforms
- Web
- Open source
- Not stated
- Language
- English
- Last checked
- Oct 5, 2026 · Online when checked
- Listed
- Oct 5, 2026
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