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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
Android
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.

According to its site, it targets teams that need to turn documents into reliable production workflows, especially in enterprise settings. You can get started through its cloud product, LlamaParse, and it also presents itself as a framework for building custom agents and workflows around your data and business logic.

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 suggests it is useful for structured document pipelines and RAG-style applications. Pricing details beyond the free plan were not publicly visible on the page, though there is a free tier with credits and a contact-sales path.

A few details are still unclear from the crawled content, including the exact model providers supported, privacy controls, and whether the full platform is cloud-only or also self-hosted. The site does describe LlamaIndex as a “fully open agent framework,” which suggests open-source roots, but the commercial offering is cloud-hosted. If you need a simple consumer chatbot or a tool that works without developer setup, this is probably not the best fit.

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
Quick Facts
DeploymentCloud-hosted
AutonomySemi-autonomous
Model supportMulti-model
Open sourceYes
Team supportEnterprise
Pricing modelFreemium
Interfacegui, api

Agent Frameworks & Orchestration

Agent Development Kit (ADK) is a framework for developers building AI agents and multi-agent workflows. It supports Python, TypeScript, Go, and Java, and is designed to run across different models and deployment setups.

API
Integrations
Multi-Agent
+4

Semantic Kernel is Microsoft’s lightweight, open-source framework for adding AI models and agent workflows to C#, Python, and Java applications. It helps developers connect prompts, plugins, memory, and model calls into software that can take actions through existing APIs.

Open Source
iOS
API
+4