LlamaIndex Framework

freemium

LlamaIndex delivers agentic OCR and AI-powered document workflows for developers. Parse PDFs, extract structured data, and deploy intelligent document agents at enterprise scale.

AI Frameworks

Document AI Tools

OCR Tools

About

LlamaIndex is the new standard for complex document processing and AI agent development. The platform brings together two core products: LlamaParse, an enterprise-grade agentic OCR engine that accurately parses PDFs, spreadsheets, images, and 90+ unstructured file types including embedded images, multi-page tables, and handwritten notes; and LlamaIndex Core, an open framework providing the building blocks to construct, orchestrate, and deploy AI agents at scale. Developers can use the low-code workflow builder to define control flow for generative AI applications, enabling agents to read, reason over, and act on complex documents while adapting to custom business logic. The platform supports full modular composition — from parsing and extraction to indexing, retrieval, and deployment — so teams can tailor document agents to their data and infrastructure. With over 500 million documents processed, 25 million monthly package downloads, and 300,000+ LlamaParse users, LlamaIndex is widely adopted across enterprise use cases including financial due diligence, invoice processing, technical document search, and customer support automation. The free plan offers 10,000 credits per month (~1,000 pages), making it accessible to individual developers and startups, while enterprise tiers scale to hundreds of millions of documents. LlamaIndex is the go-to choice for developers who need accurate, reliable, and production-ready document intelligence.

Key Features

Agentic OCR with LlamaParse: Industry-leading document parsing for 90+ unstructured file types, handling complex layouts, embedded images, multi-page tables, and even handwritten notes with high accuracy.
Low-Code Workflow Builder: Visual control-flow orchestration for GenAI apps, enabling developers to build and deploy end-to-end document agents with custom business logic and minimal code.
Structured Data Extraction: Automatically extract defined schemas from raw documents, turning unstructured content into structured, queryable data ready for downstream AI or business systems.
Modular AI Agent Framework: LlamaIndex Core provides open-source building blocks for composing AI agents — from retrieval and indexing to reasoning — fully adaptable to any data source or infrastructure.
Enterprise-Scale Document Processing: Proven at 500M+ documents processed, with scalable infrastructure supporting industries like finance, insurance, healthcare, and manufacturing.

Use Cases

Automating financial due diligence by parsing and extracting key data from complex legal and financial documents at scale.
Building invoice processing pipelines that automatically extract line items, totals, and vendor details from diverse invoice formats.
Creating internal knowledge base search tools that let employees query technical documentation using natural language.
Deploying AI-powered customer support agents that retrieve accurate answers from product manuals, contracts, and support docs.
Accelerating clinical research workflows by extracting structured insights from medical literature, trial reports, and pharma documents.

Pros

Best-in-class document parsing accuracy: LlamaParse consistently ranks as the most accurate OCR and parsing engine for complex documents, handling edge cases like multi-column layouts and handwritten text.
Generous free tier for developers: The free plan provides 10,000 credits per month (~1,000 pages), making it easy to prototype and build without upfront costs.
Highly modular and framework-agnostic: LlamaIndex Core is open source and integrates with any LLM, vector store, or cloud infrastructure, giving teams full control over their AI stack.
Production-proven at enterprise scale: With 300k+ users and 25M+ monthly downloads, the platform has a large community, extensive documentation, and a track record in mission-critical deployments.

Cons

Steeper learning curve for advanced workflows: While the low-code builder lowers the barrier, complex multi-agent orchestration still requires solid Python and AI development knowledge.
Credit consumption can escalate at scale: Heavy document processing workloads can quickly exhaust the free tier, and enterprise pricing may be significant for high-volume use cases.
Ecosystem primarily Python-centric: LlamaIndex's core framework is Python-first, which may limit accessibility for teams working in other languages or non-engineering environments.

Frequently Asked Questions

LlamaIndex is used to build AI-powered document agents that can parse, extract, index, and reason over complex documents. It's commonly used for financial due diligence, invoice processing, technical document search, and enterprise customer support automation.

LlamaParse is LlamaIndex's flagship document parsing product. It uses agentic OCR to accurately extract content from 90+ file types including PDFs, spreadsheets, images, and more — supporting complex layouts, embedded images, multi-page tables, and handwritten notes.

Yes, LlamaIndex offers a free plan with 10,000 credits per month (approximately 1,000 pages of document processing). Paid plans are available for higher volume and enterprise needs. The core framework (LlamaIndex Core) is also open source.

While both are AI agent frameworks, LlamaIndex specializes in document intelligence — offering best-in-class OCR, parsing, and retrieval pipelines optimized for structured and unstructured documents. LangChain is more general-purpose. LlamaIndex also offers a managed cloud platform (LlamaParse) alongside its open-source framework.

LlamaIndex is used across finance (investment analysis, due diligence), insurance (claims and underwriting automation), healthcare and pharma (clinical research), manufacturing (technical documentation), and more. Its agents are designed to adapt to dozens of industry-specific domains.