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LlamaIndex

Document OCR and workflows for building AI agents

LlamaIndex helps developers build document agents that parse, extract, and reason over complex files. It combines agentic OCR with a low-code workflow builder for document-heavy automation.

Open Source
Vision
File Access
B2B
For Developers
RAG
For Teams
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About

What It Is

LlamaIndex is a developer-focused platform for building document-centric AI agents and workflows. It sits in the agent frameworks and document automation space, with a strong emphasis on OCR, parsing, retrieval, and structured extraction from PDFs, spreadsheets, images, and other unstructured files.

What to Know

The product appears strongest when your workflow depends on document understanding rather than general-purpose chat. It advertises layout-aware parsing, schema-based extraction, citations, confidence scores, and a low-code workflow builder, which...

Key Features
Agentic OCR for layout-aware document parsing
Supports 90+ unstructured file types
Schema-based structured extraction
Page citations and confidence scores for extracted outputs
Chunking and embedding pipeline for retrieval
Use Cases
Automating intake and extraction from invoices, forms, and reports
Building enterprise document Q&A and knowledge bases
Creating agent workflows that read documents and apply business rules
Agenticness: Guided Assistant

Executes tasks you assign, one step at a time, within narrow domains.

High evidence
Last evaluated: Mar 28, 2026

Dimension Breakdown

Action Capability
Autonomy
Adaptation
State & Memory
Safety

Categories

Pricing
  • Free: 10,000 free credits per month, roughly 1,000 pages, plus agentic OCR, structured extraction, and end-to-end document agent building
  • Paid: Additional pricing not publicly available on the page
  • Enterprise: Contact sales
Details
AddedJanuary 16, 2026
RefreshedMarch 28, 2026
Agenticness
Quick Facts
DeploymentCloud-hosted
AutonomySemi-autonomous
Model supportMulti-model
Open sourceYes
Team supportEnterprise
Pricing modelFreemium
Interfacegui, api

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Documentation for the Xet content-addressed storage protocol and its reference implementations. It is aimed at developers building clients or tools that upload and download data from Hugging Face Hub using Xet.

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Chrome Extension
Code Execution
File Access
+5
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