Breadth
Handle more than clean PDFs
A useful document parsing API should keep working once the inputs include scans, photos, and mixed business documents.
Document parsing API
Document parsing API
A document parsing API that gives you something more useful than parsed text.
The phrase 'document parsing API' covers everything from clean-PDF parsing to business-ready extraction. LeapOCR is built for teams that need parsed documents to become readable markdown or structured workflow data, not just another intermediate artifact.
Why teams use this
Support PDFs, scans, images, invoices, forms, and mixed document inputs.
Return markdown or structured JSON depending on the next consumer.
Use one extraction layer across review, validation, and downstream writeback workflows.
Parsing request surface
Choose the output shape based on where the document is headed next.
Document parsing request
{ "url": "https://example.com/document.pdf", "file_name": "document.pdf", "format": "structured", "instructions": "Extract the fields needed by the downstream system."}
Why it works
What teams actually want from document parsing
The buying decision usually comes down to whether the parsed document is the destination or only the start of the workflow.
Output
Pick readable or structured output
Use markdown when the result needs to stay readable and structured JSON when another system needs named fields.
Workflow
Fit downstream systems cleanly
The result should reduce cleanup in the next system instead of creating another adaptation problem.
What you control
What 'document parsing' should mean in production
For production teams, parsing is valuable only if the output shape matches the real workflow.
documents
Input scope
PDFs, scans, forms, and images
The useful API does not stop at clean digital documents. It supports the document formats teams really receive.
markdown
Readable mode
Keep structure in a human-readable format
Markdown is useful for review, LLM context, and analysis workflows where the page still needs to read well.
json
System mode
Return a structured object for software systems
Use JSON when the document needs to become a trusted payload instead of only a readable artifact.
contracts
Downstream fit
Shape output for the next system
A schema or template keeps the result aligned with the system receiving the document next.
Examples
Two common document-parsing workflows
Most teams either need a readable parsed document or a structured object that can move through software cleanly.
Readable parsing
Use markdown when the document still needs to be read
Useful for review, QA, knowledge workflows, and operational handoff where a human-readable page still matters.
Markdown example
md
# Supplier declaration## Issuer- Harbor Components Ltd.## Declared values- Net weight: 640 kg
Structured parsing
Use JSON when the document feeds another system
Useful for product, finance, and logistics workflows where parsed content still has to become a reliable record.
JSON example
json
{ "issuer": "Harbor Components Ltd.", "net_weight_kg": 640.0, "document_type": "supplier_declaration"}
FAQ
Questions teams ask before wiring this up
Straight answers for teams evaluating how this workflow fits into production.
How is this different from the broader parsing page already on the site?
This page targets the exact-match commercial term 'document parsing API' directly and frames it around workflow-ready output instead of a broad capability overview.
Can a document parsing API still return markdown?
Yes. Markdown is useful when the parsed result needs to remain readable for people, review, or LLM workflows.
When should I use structured output instead?
Use structured output when the parsed document must feed another software system that expects named fields or a schema.
Ready to test
Test a document parsing API on the files your workflow actually receives
Use real PDFs and scans and check whether the output lands closer to the next system without another parsing layer.