Layout-aware document parsing
Handles structural elements such as headers, footers, nested or split sections, tables, and complex spatial layouts so the resulting data retains document context.
LlamaParse is an AI document parsing platform that converts complex PDFs, office files, spreadsheets, images, and other documents into structured, AI-ready data. It is designed for developers and enterprise teams building retrieval, extraction, and document automation workflows.
LlamaParse is an AI document parsing platform that converts unstructured files into data for AI applications and automated workflows. It is built to handle complex PDFs, office documents, spreadsheets, images, and scanned files rather than only plain text.
The parser recognizes document structure such as tables, charts, handwriting, checkboxes, images, headers, footers, and split sections. It can produce Markdown, plain text, per-page JSON, XLSX, HTML tables, annotated PDFs, and structured JSON for custom schemas. Parsing modes allow teams to choose a balance between processing cost and accuracy.
LlamaParse is aimed at developers and enterprise teams building retrieval-augmented generation, extraction, indexing, and document-agent workflows. It is available as a hosted SaaS service, with private VPC deployment options listed for enterprise use.
Handles structural elements such as headers, footers, nested or split sections, tables, and complex spatial layouts so the resulting data retains document context.
Processes more than text, including charts, images, handwriting, and checkboxes, for documents where visual information contributes to meaning.
Provides different parsing modes for adjusting the trade-off between processing cost and accuracy. The pricing information also lists Auto Mode for smart tier routing per page on applicable plans.
Exports parsed content as Markdown, plain text, per-page JSON, XLSX, HTML tables, or annotated PDFs; structured JSON output can be generated for custom schemas.
The product site states support for more than 90 document formats and over 100 languages, covering PDFs, office files, spreadsheets, images, and other document types.
Enterprise offerings include private VPC deployment, higher concurrency and rate limits, and SaaS or hybrid-cloud deployment options.
Parse invoices into structured records containing line items, taxes, totals, vendor information, and payment details, then use the results in validation or approval workflows.
Convert complex business documents into cleaner AI-ready content for retrieval-augmented generation, indexing, and agents that need to work across tables, images, and hierarchical layouts.
Process technical documentation and scientific papers while preserving tables, figures, sections, and other layout context needed for search or downstream analysis.
Turn insurance claims and healthcare forms into machine-readable data, including information captured in scanned or visually complex documents.
Process multi-page scanned PDFs and other image-heavy files as part of enterprise ingestion pipelines that need to handle high document volumes.
No. LlamaParse is a commercial document parsing platform. LlamaIndex and Workflows are separate open-source projects from the same organization.
The listed outputs include Markdown, plain text, per-page JSON, XLSX, HTML tables, and annotated PDFs. The pricing information also lists structured JSON output for custom schemas.
LlamaIndex uses a credit-based model in which parsing, indexing, and extraction actions consume credits. The site lists a free plan, paid plans, pay-as-you-go options, and custom enterprise pricing; the exact credit cost depends on the selected parsing mode and options.
The SaaS product runs in a hosted cloud tenant. Enterprise customers can use private VPC deployment options, and the site also lists SaaS or hybrid-cloud deployment for enterprise plans.
The product site describes support for more than 90 formats and over 100 languages, including PDFs, office documents, spreadsheets, images, technical documents, invoices, claims, healthcare forms, and multi-page scanned PDFs.
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