LlamaParse is great inside LlamaIndex. If you want clean extraction from a standalone API, with a correctness check for financial docs, start here.
LlamaParse turns complex layouts, tables and figures into clean Markdown for LLM pipelines, and plugs straight into LlamaIndex. If you're building on that stack, it's the native choice.
pdftojson gives you the same clean Markdown (plus JSON, CSV, XML and text) from a plain HTTP API with no framework attached, and adds reconciliation for the financial documents where a wrong number is expensive.
LlamaParse is good at turning complex layouts, tables and figures into clean Markdown for LLM pipelines.
If you're already building on LlamaIndex, it drops straight in with no extra glue.
| pdftojson | LlamaParse | |
|---|---|---|
| Output for RAG | Markdown (plus JSON, CSV, XML, Text) | Markdown for LLMs |
| Ecosystem | Standalone HTTP API | Native to LlamaIndex |
| Free in-browser tool | Yes | No |
| Bank-statement reconciliation | Yes | No |
| Best for | Standalone extraction with verification | RAG inside LlamaIndex |
| Pricing | Flat $29/mo | Usage-based (pages / credits) |
If your whole pipeline lives in LlamaIndex, LlamaParse is the path of least resistance. pdftojson is the better fit when you want extraction as a plain API call you can use from any stack, or when the document is financial and you need the numbers checked.
The bank-statement endpoint reconciles its own output against the opening and closing balances, so you catch a dropped or misread row before it reaches your data.
Yes. It returns Markdown that keeps headings and structure, which is what makes chunking for RAG cleaner than raw text.
No. It's a plain HTTP API you can call from any language or framework, with a free in-browser tool for one-off files.
When you're already building on LlamaIndex and want the native integration. pdftojson is framework-agnostic and adds a correctness check for financial documents.
A flat $29/mo Developer plan with a free tier, billed per page processed.