LlamaIndex
LlamaIndex is the leading document agent and OCR platform
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What is LlamaIndex?
LlamaIndex is the developer-trusted framework for building context-aware AI agents over your data. It is an open-source data framework that enables developers to go from concept to production AI application in just a few lines of code using flexible Python and TypeScript SDKs. The framework provides essential abstractions to ingest, structure, and access private or domain-specific data to inject safely and reliably into LLMs for more accurate text generation through Retrieval-Augmented Generation (RAG) systems.
The platform centers on LlamaParse, an enterprise platform for turning documents into production AI pipelines with agentic OCR capabilities. It offers six composable products: Parse (agentic OCR for 130+ formats), Extract (structured JSON data extraction with custom schemas), Classify (document routing with natural-language rules), Split (segmenting concatenated documents), Sheets (spreadsheet data extraction to Parquet), and Index (hosted vector search for RAG). The framework includes core building blocks like memory, state management, human-in-the-loop, and reflection, with day-zero integrations for the latest LLMs and tools.
LlamaIndex is designed for developers and enterprises building AI agents, particularly those working with document-heavy workflows. Common use cases include conversational chatbots, customer support systems, internal knowledge bases, and automating document-heavy processes. The framework serves teams going from prototype to production, with over 25M+ monthly package downloads, 1.5k+ contributors, and 20k+ community members. It's trusted by enterprise teams including Salesforce Agentforce for building production-ready RAG applications with state-of-the-art document parsing.
The framework supports vibe coding with natural language to prototypes in seconds, leveraging an llm.txt file for AI coding assistants. It provides extensible building blocks that can be customized to match workflows, with fully-featured SDKs that integrate into existing development stacks. The platform includes tracing and debugging capabilities, workflow support, and structured data extraction features for building sophisticated AI applications.
LlamaIndex pricing
Pricing model: Freemium
LlamaIndex operates on a credit-based system where 1,000 credits = $1.25. The Free plan includes 10K credits monthly (~1000 pages), 1 user, 1 project, 5 concurrent parse jobs, 5 indexes, 50 files per index, and community support. The Starter plan includes 40K credits, pay-as-you-go up to $500/mo, 5-10 users, 1 project, 5 concurrent jobs, 50 indexes, 500 files per index, 50 external data sources, and basic email support. The Pro plan includes 400K credits, pay-as-you-go up to $5,000/mo, 10 users, 5 projects, 20 concurrent jobs, 100 indexes, 2,000 files per index, 100 external data sources, Slack priority support, SOC2/HIPAA/GDPR compliance, and SSO/MFA. Enterprise offers custom credits with volume discounts, 5x higher rate limits, 100 concurrent jobs, Enterprise SSO, SaaS or Hybrid cloud deployment, VPC option, custom BAAs, and dedicated account manager with priority Slack Connect support. The free parse tiers include Fast (1 credit/page), Cost Effective (3 credits/page), Agentic (10 credits/page), and Agentic Plus (45 credits/page). Startups can apply for a program offering free credits and dedicated support.
LlamaIndex pros
- Fully open source with no restrictions on production or commercial use
- Flexible Python and TypeScript SDKs for any development stack
- Day-zero integrations with latest LLMs and tools
- 25M+ monthly package downloads proving reliability
- 1.5k+ contributors and 20k+ community members for support
- Six composable products in one platform with single API key
- Agentic OCR supporting 130+ document formats including PDF, Office, images
- Advanced table and chart extraction with layout detection
- Structured JSON output with custom schema support
- 80+ languages supported for global applications
- Auto Mode smart tier routing saves up to 80% on costs
- 10K free credits monthly (~1000 pages) for new users
- SOC 2 Type II, GDPR, and HIPAA compliance for enterprise
- VPC deployment option ensuring data never leaves your tenant
- Starter templates like SEC Insights and Invoice Matching
LlamaIndex cons
- LlamaParse commercial platform is not open source
- Credit-based pricing can become expensive at scale
- 1,000 credits cost $1.25 which adds up quickly
- Free tier limited to 1 user and 1 project only
- Basic parsing still requires API key and internet connection
- Complex documents require higher-cost Agentic Plus tier
- Concurrent parse jobs limited to 5 on free/starter plans
- On-premises deployment only available for Enterprise plan
- Learning curve for understanding all six composable products
- Caching retained only 48 hours unless turned off manually
Frequently asked questions about LlamaIndex
Is LlamaIndex open source?
Yes, LlamaIndex is fully open source, granting developers full control over how they build applications without any restrictions on leveraging your app in production or for commercial use. Our open source projects provide AI builders with foundational building blocks for creating AI apps, including both low-level and high-level abstractions deployable in just a few lines of code.
Is LlamaParse open source?
LlamaParse is our commercial platform designed to automate document workflows including agentic document parsing, extraction and indexing. It provides a generous provision of 10k free credits a month to all new users, but is not open source. Our open source projects LlamaIndex and Workflows provide the foundational building blocks while LlamaParse is the enterprise platform for document processing.
What are common ways to use LlamaIndex?
Common use cases include conversational chat, customer support, internal knowledge bases, automating document-heavy processes, and more. The framework is particularly valuable for building context-aware AI agents, RAG systems, document agents powered by agentic OCR, and multi-step AI workflows that can reason, understand, and act on document data.
How many credits does it cost to parse or extract one page?
It depends on the modes or options selected. Basic Parsing costs as low as 1 credit per page. Layout-aware agentic parsing with LLMs or VLMs costs higher for greater accuracy. The tiers are: Fast (1 credit/page) for simple text-heavy documents, Cost Effective (3 credits/page) for balanced performance, Agentic (10 credits/page) for complex layouts and multimodal content, and Agentic Plus (45 credits/page) for maximum accuracy on mission-critical documents.
Does LlamaParse deploy on premises?
LlamaParse SaaS is hosted on a secure cloud tenant with data encrypted in transit and at rest. Cached data is retained only for 48 hours before permanent deletion. For enterprises, we offer deployment in private VPCs across all cloud providers ensuring data never leaves your tenant. LlamaParse is available on both AWS and Microsoft Azure marketplaces.
What compliance certifications does LlamaParse have?
LlamaParse is certified for SOC 2 Type II, GDPR, and HIPAA compliance. These certifications ensure enterprise-grade security and data protection for organizations with strict compliance requirements. For more details, you can visit their Trust Center.
How does LlamaIndex work with LlamaParse?
LlamaParse allows builders to turn unstructured data sources like PDFs and PPTs into AI-ready markdown, JSON, and other formats. Workflows then enables builders to use that data to build multi-step AI agents that can reason, understand, and act. Parse provides the document parsing foundation while LlamaIndex provides the core building blocks for agents like state and memory.
How is LlamaIndex different from Workflows?
LlamaIndex provides developers with the core building blocks for building agents like state, memory, and more. Workflows allows developers to build highly controlled multi-step workflows that can even combine multiple agents. LlamaIndex focuses on the foundational abstractions while Workflows focuses on orchestrating complex multi-step agent processes.
What file formats does LlamaParse support?
LlamaParse supports 130+ formats including PDF, Office documents (DOCX, DOC, PPTX, PPT), spreadsheets (XLSX, CSV), images (PNG, JPG), and more. Output formats include Markdown, Plain Text, JSON (per-page), XLSX, HTML Tables, and Annotated PDF. The platform handles complex layouts, tables, charts, handwriting, checkboxes, and embedded visuals.
Are there programs for startups?
Yes, startups can apply to the startup program for free credits, dedicated support, community spotlights, and more. The program is designed to help early-stage companies build with LlamaIndex without worrying about costs in the early stages. Startups receive the same enterprise-grade capabilities with additional support resources.