Parse PDFs, scans, images, and Office files into spatial JSON or Markdown with coordinates, confidence, and page context. Extract structured data for agents, RAG, search, automation, and human review.
Trusted by enterprises, governments, and AI-native teams building document workflows at scale.
Capabilities
Detect every document element
Identify tables, forms, formulas, images, charts, handwriting, key-value regions, headings, lists, and reading order across complex files.
Preserve page context
Keep elements connected to page position, confidence, and reading order so teams can validate, highlight, and use results downstream.
Choose speed, cost, or depth
Select the processing mode that fits the document — from low-cost Markdown to AI-augmented parsing for complex visual layouts.
Handle real-world files
Process PDFs, images, Office files, scans, and multilingual documents through one API.
Map data to your schema
Define a JSON Schema for the fields you need, or scaffold one from example documents using the schema generator in Studio. Every extracted value comes back with bounding boxes, match labels, and confidence scores.
Extract complex tables
Extract tables, forms, images, and handwriting with rows, columns, spans, captions, and footnotes preserved.
Trace every value
Keep values connected to page position, confidence scores, reading order, and source evidence for review.
Send downstream
Return output ready to map into databases, ERPs, CRMs, review queues, and document workflows.
Spatial JSON for structured operations
Use spatial JSON for layout-aware elements, tables, key-value regions, coordinates, confidence scores, and page context.
Markdown for AI and search
Use Markdown for fast, cost-efficient content for RAG, search indexing, knowledge bases, and content migration.
Predictable output for the next step
Return results in predictable formats so downstream systems can validate, route, review, automate, or feed AI and search workflows.
Validate before automating
Use confidence scores, coordinates, and word-level details to review the output before sending it downstream.
Route exceptions
Move clean results forward and hold low-confidence, incomplete, or mismatched files for review.
Reconcile and map
Compare extracted values against business rules, records, or downstream systems before posting.
Support review and recovery
Keep results tied to the source so teams can trace, fix, and recover issues.
Automate downstream workflows
Send typed JSON to business systems and review queues. Or, send Markdown to AI, search, knowledge bases, and content pipelines.
Detect every document element
Identify tables, forms, formulas, images, charts, handwriting, key-value regions, headings, lists, and reading order across complex files.
Preserve page context
Keep elements connected to page position, confidence, and reading order so teams can validate, highlight, and use results downstream.
Choose speed, cost, or depth
Select the processing mode that fits the document — from low-cost Markdown to AI-augmented parsing for complex visual layouts.
Handle real-world files
Process PDFs, images, Office files, scans, and multilingual documents through one API.
Map data to your schema
Define a JSON Schema for the fields you need, or scaffold one from example documents using the schema generator in Studio. Every extracted value comes back with bounding boxes, match labels, and confidence scores.
Extract complex tables
Extract tables, forms, images, and handwriting with rows, columns, spans, captions, and footnotes preserved.
Trace every value
Keep values connected to page position, confidence scores, reading order, and source evidence for review.
Send downstream
Return output ready to map into databases, ERPs, CRMs, review queues, and document workflows.
Spatial JSON for structured operations
Use spatial JSON for layout-aware elements, tables, key-value regions, coordinates, confidence scores, and page context.
Markdown for AI and search
Use Markdown for fast, cost-efficient content for RAG, search indexing, knowledge bases, and content migration.
Predictable output for the next step
Return results in predictable formats so downstream systems can validate, route, review, automate, or feed AI and search workflows.
Validate before automating
Use confidence scores, coordinates, and word-level details to review the output before sending it downstream.
Route exceptions
Move clean results forward and hold low-confidence, incomplete, or mismatched files for review.
Reconcile and map
Compare extracted values against business rules, records, or downstream systems before posting.
Support review and recovery
Keep results tied to the source so teams can trace, fix, and recover issues.
Automate downstream workflows
Send typed JSON to business systems and review queues. Or, send Markdown to AI, search, knowledge bases, and content pipelines.
Turn complex files into document structure
Detect every document element
Identify tables, forms, formulas, images, charts, handwriting, key-value regions, headings, lists, and reading order across complex files.
Preserve page context
Keep elements connected to page position, confidence, and reading order so teams can validate, highlight, and use results downstream.
Choose speed, cost, or depth
Select the processing mode that fits the document — from low-cost Markdown to AI-augmented parsing for complex visual layouts.
Handle real-world files
Process PDFs, images, Office files, scans, and multilingual documents through one API.
Extract data for systems, agents, and review
Map data to your schema
Define a JSON Schema for the fields you need, or scaffold one from example documents using the schema generator in Studio. Every extracted value comes back with bounding boxes, match labels, and confidence scores.
Extract complex tables
Extract tables, forms, images, and handwriting with rows, columns, spans, captions, and footnotes preserved.
Trace every value
Keep values connected to page position, confidence scores, reading order, and source evidence for review.
Send downstream
Return output ready to map into databases, ERPs, CRMs, review queues, and document workflows.
Return predictable output your systems can use
Spatial JSON for structured operations
Use spatial JSON for layout-aware elements, tables, key-value regions, coordinates, confidence scores, and page context.
Markdown for AI and search
Use Markdown for fast, cost-efficient content for RAG, search indexing, knowledge bases, and content migration.
Predictable output for the next step
Return results in predictable formats so downstream systems can validate, route, review, automate, or feed AI and search workflows.
Build governed document workflows, from extraction to downstream use
Validate before automating
Use confidence scores, coordinates, and word-level details to review the output before sending it downstream.
Route exceptions
Move clean results forward and hold low-confidence, incomplete, or mismatched files for review.
Reconcile and map
Compare extracted values against business rules, records, or downstream systems before posting.
Support review and recovery
Keep results tied to the source so teams can trace, fix, and recover issues.
Automate downstream workflows
Send typed JSON to business systems and review queues. Or, send Markdown to AI, search, knowledge bases, and content pipelines.
Try it live
Switch processing modes and inspect live output from a sample invoice as rendered Markdown, raw Markdown, or spatial JSON.
Processing modes
Choose speed, cost, or depth per workflow. Set mode per request.
Text
AvailableLow-cost Markdown for born-digital PDFs and Office files
Structure
AvailableSpatial JSON with OCR, tables, key-value regions, bounds, confidence, and page context
Agentic
AvailableAgent-guided extraction for documents that need deeper reasoning, review, and recovery
INDUSTRIES AND DOCUMENTS
Structured output for high-stakes teams.
Output formats
Elements, bounds, confidence, metadata, and usage. Chooseoutput: "json" or Markdown per request.
Spatial JSON
For extraction · validation · review
{ "status": "processed", "usage": { "pages": 4, "credits": 6 }, "pages": [ { "index": 0, "elements": [ { "type": "key_value_pair", "label": "Invoice number", "value": "INV-20241108", "confidence": 0.98, "page": 1, "bounds": [82, 128, 284, 152] }, { "type": "table", "rows": 3, "columns": 4, "confidence": 0.96, "bounds": [70, 320, 516, 482] } ] } ]}Markdown
For RAG · search · knowledge bases
# Invoice INV-20241108
**From** Acme Studios LLC**Issued** Nov 8, 2024
## Line items
| Item | Qty | Total || --- | ---: | ---: || Visual identity | 1 | $8,500 || Brand guidelines | 1 | $2,200 |
**Total · $13,500.00**Built for production
Handle messy real-world files
Process PDFs, photos, scans, Office files, and archives without building a separate parser for each format.
Return source-grounded outputs
Return coordinates, confidence, page context, and review paths so AI outputs stay tied to source evidence.
Flag uncertainty before automation
Use confidence scores and page context to catch extraction issues before agents or automations rely on them.
Choose speed, cost, or depth
Pick the cheapest mode that meets your accuracy bar. Then increase depth only when documents require it.
Prepare schema-ready data
Use /extract to pull specific fields from any document — each value is returned with bounding boxes and match labels so you can validate, route to human review, or send directly downstream.
Connect the full workflow
Parse first. Then convert, redact, generate, sign, view, edit, or approve across Nutrient DWS and SDKs.
SOC 2 Type 2 audited
Audited annually. Reports available under NDA.
Regional processing options
Choose supported processing regions for enterprise deployments.
Trust and compliance
Secure document handling
Files are discarded once their data is extracted.
HTTPS/TLS encryption
API communication is encrypted by default, and unencrypted requests are rejected.
Data Extraction API processes PDFs, images, Word, Excel, PowerPoint, and other common document formats. Upload files directly, send raw binary content, or point the API at a hosted document URL. It handles scanned PDFs, fillable forms, and mixed digital/image-based documents without requiring a separate OCR pipeline.
Yes. The /extract API maps a document to your JSON Schema and returns the requested fields with per-field citations back to the source — so every value traces back to an exact location in the original document. It works with PDFs, scans, images, and Office files.
A general LLM can reason over document text, but it doesn’t give you a document processing layer by itself. Data Extraction API returns layout-grounded elements with reading order, coordinates, confidence scores, and page references, so teams can validate, route, highlight, and automate with traceability.
Spatial JSON and Markdown are separate output formats on the same API. Choose spatial JSON when your workflow needs structured elements with layout context, or Markdown when you need clean structured content for RAG, search, or document Q&A. Send two requests if your pipeline needs both.
Every extracted element comes back with confidence scores, page references, coordinates, and word-level details, so you can compare outputs across sample documents, flag low-confidence fields for human review, highlight results on the original document, and route exceptions to a review queue. Because results stay connected to the source document, teams can trace outputs back to the original page and correct downstream records when needed.
Yes. Use Data Extraction API as the parsing layer. Then connect the output to AI Document Processing for templates and validation; DWS Processor for conversion, redaction, generation, and signing; and Nutrient SDKs when humans need to review, edit, annotate, or approve documents in your application.
Yes. The API is backed by Nutrient’s broader security practices, including SOC 2 Type 2-audited infrastructure and TLS-encrypted transport — built for use in business-critical and regulated workflows.
New accounts get 5,000 free Data Extraction API credits per month with no credit card required. Beyond the free tier, you control cost by choosing the processing mode that fits each workflow: text for low-cost Markdown extraction, structure for spatial JSON, understand for AI-augmented parsing, and agentic for advanced extraction workflows.
Use the schema generator in Studio — upload up to five example documents and describe the document type, and it generates a JSON Schema you can use directly with /extract. You can also write the schema manually. Refer to the documentation for supported field types, constraints, and size limits.
Understand mode uses an AI-augmented extraction pipeline for complex documents that need richer layout understanding, OCR correction, handwriting support, formulas, and structure-aware output.
A data extraction API is a service that parses documents — PDFs, scans, images, and Office files — and returns structured, usable data rather than just readable text. Instead of manually pulling values from documents or building custom parsers for each file format, you send a document to the API and get back structured output: spatial JSON with element types, coordinates, confidence scores, and page context, or Markdown for AI and search workflows. Nutrient Data Extraction API handles this across four processing modes — text, structure, understand, and agentic — so teams can choose speed, cost, or depth per workflow.
OCR makes scanned or image-based documents machine-readable by identifying text on a page. A data extraction API goes further: It identifies which values matter, where they sit in the document, how they relate to each other, and how to structure them for downstream use. OCR gives you a wall of text. A data extraction API gives you typed fields with coordinates, confidence scores, page references, and reading order — output that a system can validate, route, and act on without additional processing.
Most document formats used in business and regulated workflows are supported, including PDFs (digital, scanned, and image-based), images, and Office files such as Word, Excel, and PowerPoint. Within those formats, the API handles forms, tables, key-value regions, handwriting, revision histories, stamps, and mixed layouts. Different document types — invoices, contracts, RFIs, submittals, medical records, permits — carry different data in different formats, so extraction workflows often define document-specific schemas rather than applying a single generic approach.
Developer resources
5,000 free Data Extraction API credits per month — no credit card required. Parse PDFs, images, scans, and Office files into spatial JSON or Markdown for AI workflows, automation, and human review.