Extracting data

How the infer → correct → remember loop works

What is extracting data?

Definition: Data extraction in Dynamite Docs is an automated three-phase loop—infer, correct, and remember—that turns unstructured business paperwork into verified tabular records.

Extraction works in three steps: infer (the AI reads the document and infers which columns matter), correct (you review and edit anything wrong in Data Studio), and remember (every correction becomes a reusable pattern).

Select one or more files and press Ctrl+Enter, or use the Extract button. Results appear as an editable table. For whole batches, select files and use Add to job to build a named Extraction job (Hobby and above), then press Run job. Hobby permits 25 files per job, 10 active jobs, and unlimited runs. Each document is extracted on its own into a View Extractions folder named after the job.

Each page successfully processed with a hosted model costs 1 page-equivalent (PE). Failed extractions cost 0 PE.

BYOK is available on every plan. BYOK on Free and Hobby uses the monthly PE allowance; BYOK on Pro and Ultra is unlimited. A run counts as BYOK only when it uses your own provider API key.

Each plan caps hosted pages per document. BYOK has no per-document tier cap, though Free and Hobby BYOK still uses monthly PE and provider and file-size limits still apply.

Key fact: Each successfully processed hosted page consumes 1 page-equivalent (PE) while failed jobs cost 0 PE, with corrections automatically saved to improve future batches.

How does automated schema inference extract line items without templates?

Extraction works in three steps: infer (the AI reads the document and infers which columns matter), correct (you review and edit anything wrong in Data Studio), and remember (every correction becomes a reusable pattern).

Related workflows and guides

Open the document extraction app, browse document input and export integrations, or compare PE, storage, and API limits.

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