What is LlamaIndex used for?

LlamaIndex is a document processing platform that converts PDFs, scans, and Office files to markdown or JSON, and extracts structured data. It is a good fit for parse a financial report and extract every table, extract data from financial reports with citations, and process all PDFs in a folder asynchronously.

Is LlamaIndex open source?

Yes. LlamaIndex is open source under the MIT licence. Its source code is on GitHub at run-llama/llama_index and is written mainly in Python.

Yes. LlamaIndex is open source, so the software itself is free to use. A managed cloud version is also available.

Can I self-host LlamaIndex?

Yes. LlamaIndex can be self-hosted on your own server or infrastructure.

What is LlamaIndex an alternative to?

LlamaIndex is an open-source alternative to Vellum, Unstructured, Vectara and Cohere. Other open-source alternatives to Vellum include RAGFlow and Kubeflow.

Is LlamaIndex actively maintained?

Yes. The most recent commit to LlamaIndex was on 12 October 2026, and the latest release is v0.14.25, published on 21 September 2026. The project has 52k stars on GitHub.

LlamaIndex: open-source alternative to Vellum, Unstructured

About LlamaIndex

LlamaParse is a document processing platform from LlamaIndex. It provides APIs to parse PDFs, scans, and Office files into markdown or JSON, and to extract structured data in a user-defined schema. The platform also includes features for classifying, segmenting, and indexing documents.

It offers SDKs for Python, TypeScript, Go, and Java, and can be accessed via a single API key. The platform includes a web UI for extraction and supports batch processing, polling, and latency management for production use.

Key features

Parse converts PDFs, scans, and Office files to markdown or JSON
Extract returns JSON in a user-defined schema
Classify, Split, and Index cover sorting, segmenting, and retrieval
SDKs for Python, TypeScript, Go, and Java
Web UI for extraction
Supports batch processing, polling, and latency management

Good fit for

Parse a financial report and extract every table
Extract data from financial reports with citations
Process all PDFs in a folder asynchronously

Built with: Python tools
Tags: document processing; pdf parsing; extraction; ai; llamaindex; sdk

LlamaIndex: questions and answers

What is LlamaIndex used for?: LlamaIndex is a document processing platform that converts PDFs, scans, and Office files to markdown or JSON, and extracts structured data. It is a good fit for parse a financial report and extract every table, extract data from financial reports with citations, and process all PDFs in a folder asynchronously.
Is LlamaIndex open source?: Yes. LlamaIndex is open source under the MIT licence. Its source code is on GitHub at run-llama/llama_index and is written mainly in Python.
Is LlamaIndex free?: Yes. LlamaIndex is open source, so the software itself is free to use. A managed cloud version is also available.
Can I self-host LlamaIndex?: Yes. LlamaIndex can be self-hosted on your own server or infrastructure.
What is LlamaIndex an alternative to?: LlamaIndex is an open-source alternative to Vellum, Unstructured, Vectara and Cohere. Other open-source alternatives to Vellum include RAGFlow and Kubeflow.
Is LlamaIndex actively maintained?: Yes. The most recent commit to LlamaIndex was on 12 October 2026, and the latest release is v0.14.25, published on 21 September 2026. The project has 52k stars on GitHub.