LlamaIndex
What is LlamaIndex?
LlamaIndex is an open-source document AI platform for developers that turns messy files into structured data for agents. It combines Agentic OCR, Structured extraction, and layout-aware parsing with Build and deploy end-to-end document agents, and it integrates with Salesforce, GitHub, and Discord. Customers cited on the site include Jeppesen, NTT DATA, Experian, and Salesforce. Plans run Free, Starter Custom, Pro Custom, and Enterprise Custom.
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At a glance
- LlamaIndex is best for developers who need document pipelines that feed reliable AI agents.
- Free; Starter Custom; Pro Custom; Enterprise Custom
What does LlamaIndex do?
LlamaIndex handles document OCR and downstream AI workflows by turning messy files into structured data that agents can use. Its Parse, Extract, and Index flow covers layout-aware parsing, context-aware extraction, and retrieval-ready indexing, so teams can move from raw PDFs, scans, tables, charts, and handwriting to usable outputs without stitching together separate tools. The platform also supports workflows for building document agents around that pipeline. At scale, LlamaIndex says it has processed 1B+ documents, serves 300k+ LlamaParse users, and sees 25M+ package downloads a month. It supports 90+ formats and 100+ languages, with enterprise options for local cloud deployment, higher concurrency, and dedicated support. Customers cited on the site include Jeppesen, NTT DATA, Experian, and Salesforce, and the product is available with self-hosting.
Why use LlamaIndex?
- It combines parsing, extraction, and indexing in one document pipeline, reducing handoffs between separate tools.
- Layout-aware and multimodal processing helps preserve tables, charts, images, and spatial structure in complex files.
- Citations, confidence scores, and traceability make extracted data easier to audit before it reaches downstream systems.
- The platform is built for scale, with support for millions of pages and enterprise concurrency controls.
- Self-hosting and local cloud deployment give teams more control over where document data is processed.
Who is LlamaIndex for?
- Engineering teams that need to turn unstructured documents into agent-ready data.
- Operations teams that want to automate manual review across invoices, claims, and forms.
- Data and AI teams that need traceable extraction with confidence scores and citations.
- Enterprise developers that need scalable document processing with self-hosting options.
What are LlamaIndex's key features?
Agentic OCR
Extract text from scanned PDFs and images with OCR built for agents, handling ~1000 pages and 50+ unstructured file types for document workflows.
Structured extraction
Turn documents into schema-ready outputs with field-level confidence scores and citations, so teams can validate results instead of guessing.
Build and deploy end-to-end document agents
Create document agents that parse, extract, split, classify, and index files in one pipeline, reducing handoffs across separate tools.
Fully open-source
Run the stack with self-hosting and no cloud dependency, giving teams control over deployment, data handling, and internal customization.
Fast local processing
Process documents locally with no LLM tokens and no limits, which helps keep throughput high and avoids per-call model costs.
All major formats
Handle 90+ formats and 100+ languages, so one pipeline can cover mixed document sets without format-specific preprocessing.
Bounding box output
Return precise spatial output with bounding boxes and layout-aware parsing, which matters when buyers need traceable extraction from complex pages.
Integrations
Connect extracted document data to Salesforce, Github, and Discord, making it easier to move results into CRM, code, or team workflows.
What does LlamaIndex integrate with?
- Salesforce
- GitHub
- Discord
What are LlamaIndex's use cases?
Document agents for engineering teams
Engineering teams that need to turn unstructured documents into agent-ready data use LlamaIndex to build document workflows that parse, extract, and index files into downstream systems. They rely on Build and deploy end-to-end document agents and Structured extraction to turn PDFs, scans, and forms into usable outputs with less custom glue code.
Invoice review for operations
Operations teams that want to automate manual review across invoices, claims, and forms use LlamaIndex to route documents through Agentic OCR and Auto-Correction Loops. That helps them catch messy fields, reduce hand-checking, and move approved records into structured workflows faster.
Traceable extraction for AI teams
Data and AI teams that need traceable extraction with confidence scores and citations use LlamaIndex to validate outputs before they reach production. They combine Field-level confidence scores with Citations & traceability to audit extractions, compare schema versions, and trust what gets indexed.
Self-hosted processing for enterprises
Enterprise developers that need scalable document processing with self-hosting options use LlamaIndex to keep sensitive workloads under their own control. With Fully open-source and Fast local processing, they can process large document volumes without depending on a hosted black box.
How does LlamaIndex work?
- Connect your first document source and run Agentic OCR on PDFs, scans, or forms to turn raw files into machine-readable text and layout data.
- Choose Structured extraction or Parse to define the fields you need, then refine the schema as your documents vary across vendors and formats.
- Review Bounding box output, Field-level confidence scores, and Citations & traceability to verify each extracted value against the source page.
- Use Integrations to push clean records into Salesforce, Github, or Discord, or keep everything local with Fast local processing and Fully open-source deployment.
- Expand into Build and deploy end-to-end document agents, then monitor results with Test and evaluate as your pipeline handles more files over time.
How much does LlamaIndex cost?
Free
Free- Includes 10K credits
- 1 user
- Basic support
Starter
Custom- Includes 40K credits
- Pay-as-you-go up to 400K credits
- 5 users
- Basic support
Pro
Custom- Includes 400K credits
- Pay-as-you-go up to 4,000K credits
- 10 users
- Slack support
Enterprise
Custom- Volume discount on credits
- 5x higher rate limits
- Enterprise SSO
- SaaS or Hybrid cloud deployment
- Dedicated account manager
Frequently asked questions
What is LlamaIndex?
LlamaIndex is an open-source document AI platform for developers that turns messy files into structured data for agents. It combines Agentic OCR, Structured extraction, and layout-aware parsing with Build and deploy end-to-end document agents, and it integrates with Salesforce, GitHub, and Discord. Customers cited on the site include Jeppesen, NTT DATA, Experian, and Salesforce. Plans run Free, Starter Custom, Pro Custom, and Enterprise Custom.
How much does LlamaIndex cost? Is it free?
LlamaIndex has a free plan, with paid tiers including Starter at Custom, Pro at Custom, Enterprise at Custom.
What is LlamaIndex used for? Who is it for?
LlamaIndex is used for Agentic OCR, Structured extraction, and Build and deploy end-to-end document agents. It's built for Engineering teams that need to turn unstructured documents into agent-ready data, Operations teams that want to automate manual review across invoices, claims, and forms, and Data and AI teams that need traceable extraction with confidence scores and citations.
Does LlamaIndex have an API and what does it integrate with?
LlamaIndex doesn't publish a public API. It integrates with Salesforce, GitHub, Discord.
Editor's read
Check the credit ceilings before rollout: Free includes 10K credits, Starter 40K with pay-as-you-go up to 400K, and Pro 400K up to 4,000K. If your document volume is likely to exceed those bands, Enterprise is where higher rate limits and deployment options appear.
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