# hugepdf.io FAQ

Q: What does hugepdf.io do?

A: hugepdf.io turns PDFs into structured data for agents. It treats every page as a first-class piece of data, runs multi-extraction plus vision, and submits each page for LLM processing against your prompt.

Q: Do you do RAG?

A: No. hugepdf.io does not treat a PDF as a blob to be vaguely searched. It processes PDFs page by page for high-fidelity downstream use.

Q: Why does hugepdf.io exist?

A: General-purpose agents and models are not built to process extremely large PDFs with page-by-page fidelity. hugepdf.io exists to turn huge PDFs into databases, manifests, captions, inventories, and other machine-usable outputs.

Q: What are good use cases?

A: Wholesaler price lists, printed product pages, catalogs, photo albums, scanned records, data extraction workflows, and any PDF-to-structured-data task where page-level fidelity matters.

Q: Why not just use Claude, Codex, or another general-purpose agent?

A: Try handing a general-purpose model a 150-page document or a 500MB PDF. It will not make meaningful, accurate, incremental progress across the whole file with the fidelity serious workflows need.

Q: What if I need reasoning over multiple pages, if you process pages in isolation?

A: hugepdf.io does not conflate extraction with interpretation. It produces high-fidelity per-page data ready for agentic consumption. Cross-page reasoning, synthesis, and decisions belong to your favorite agent.

Q: Is it only for huge PDFs?

A: As long as you have a PDF, we are happy to serve. We are here for data-driven workflows over huge PDFs. That said, you can absolutely run a 3-page or 5-page paper through us if you want a high-fidelity, cost-effective option.

Q: Why use hugepdf.io?

A: hugepdf.io uses multi-extraction plus vision for best-in-class text reconstruction and processing. Pricing is meant to be no-brainer, pay-as-you-go infrastructure: currently $0.03 per processed page.

Q: Do I need an account or API key?

A: No. No API key and no account are required. Payment on-chain is authentication and identity.

Q: How do I try it?

A: Use /quickstart for the first-job path. Agents should follow /llms.txt. Preview lets the agent inspect first-page extraction quality before paying for the full document.