LlamaParse
Verified Document Processing Est. 2022

LlamaParse

Industry-leading agentic document processing for complex documents.

0.00 (0)
US Global

LlamaIndex SDK Monthly Downloads

25M+

Total Funding

$27.5M

Free Tier

1k pages/day

About LlamaParse

LlamaParse provides a sophisticated, API-driven solution for parsing and extracting structured information from complex documents. It is specifically engineered to handle challenging layouts, embedded tables, and charts within PDFs, which traditional OCR methods often fail to interpret correctly. The service is a core component of the LlamaIndex ecosystem, designed to feed clean, structured data into Retrieval-Augmented Generation (RAG) pipelines. Developers can access LlamaParse via a REST API or dedicated Python and TypeScript SDKs, which handle asynchronous job polling. It operates on a credit-based system, offering a free tier for initial use and pay-as-you-go plans for scalable production workloads.

Pricing Model

Credit System

The platform operates on a credit-based system where actions like parsing or extraction consume credits.

Free Plan

Includes a generous free tier for developers, allowing up to 1,000 pages per day.

Pay-As-You-Go

Paid plans start with a Starter tier, allowing users to purchase credits for higher volume usage.

Cost Per Page

The number of credits per page varies based on the parsing mode and model used.

API & Developer Experience

Api Type

Asynchronous REST API. You submit a job and then poll for the result.

Sdks

Official SDKs for Python and TypeScript are available to simplify integration and handle job polling.

Authentication

Uses a LlamaCloud API key passed in the environment variables or client configuration.

Core Functionality

Provides agentic OCR, structured data extraction, classification, and indexing.

Tags

API Enterprise
Visit Website
Founded 2022
Founder(s) Jerry Liu, Simon Suo
Country US
Coverage Global
Access Type Self-serve
Pricing Model Freemium
Pricing Visibility Public
Auth Method API Key
Sandbox Available
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