Most enterprise data still sits inside PDFs, scans, and slide decks. Large language models and agents cannot use that data until it becomes structured JSON. Open-source document extraction has become the standard way to do that conversion on your own hardware.
Two different problems hide under the phrase ‘PDF to JSON.’ The first is schema-driven extraction: you define fields, and a model fills them with values. The second is document parsing: a model reconstructs the page into structured JSON or Markdown. Most teams need one, sometimes both. Choosing the wrong category costs real time.
Open weights matter here for cost and privacy. Proprietary APIs can cost thousands of dollars per million pages, and they require sending documents off-premise. Local models remove both constraints. Below are the models and toolkits worth evaluating, grouped by what they actually do.
Two categories, one phrase
Schema-driven extraction takes a document and a JSON schema, then returns values for your fields. Use it for invoices, forms, contracts, and receipts, where you know the fields in advance.
