Case numbers, parties, recording information, legal descriptions, dates, and fees remain scattered across filed documents until someone extracts them. Nutrient Data Extraction API turns court filings, deeds, and clerk records into structured data — with confidence scores and source context so staff can review uncertain values, not every field.
Trusted by enterprises, governments, and teams building document workflows at scale
USE CASES
Extract case numbers, filing types, parties, attorneys, judges, and hearing dates from civil, criminal, and administrative filings.
Structure instrument types, recording numbers, grantor and grantee details, parcel identifiers, and legal descriptions from deeds and recorded instruments.
Extract document type, applicant, fees, reference numbers, submission dates, and status information from clerk-issued records.
Turn document content into structured metadata for search, classification, retrieval, and records management systems.
Export typed JSON that maps to the fields case management, recording, or enterprise content platforms expect.
GOVERNED EXTRACTION
LLMs can interpret a court filing — but public record workflows need deterministic, traceable output grounded in the source document, not generated answers that vary between runs.
Typed output remains tied to the source document — not generated text that changes from one run to the next.
Flag uncertain values before they move downstream into case management or recording systems.
Every extracted value is anchored to its source location for traceability and staff review.
Tables, key-value regions, and reading order preserved — not flattened into unstructured text.
Support validation steps before structured data enters the official record or downstream system.
Source context and page detail support traceable, reviewable government document workflows.
WHAT YOU CAN EXTRACT
Case numbers, court, jurisdiction, filing type, filing date, and hearing dates from civil, criminal, and administrative filings.
Plaintiff, defendant, attorney, agency, and contact details from court filings and administrative records.
Instrument type, recording number, recording date, and book-and-page references from deeds and recorded instruments.
Parcel number, property address, legal description, grantor, and grantee from land and recording records.
Consideration amounts, filing fees, and other financial values from court filings and recorded instruments.
Stamps, handwritten annotations, notary information, and signature presence from older or scanned records.
HOW IT WORKS
Parse
Turn court filings, deeds, and scanned public records into document structure.
Extract
Identify case details, parties, recording information, legal descriptions, and document metadata.
Map
Define the fields the workflow needs using the schema generator in Studio, or write a JSON Schema directly. Get back structured, validated output.
Structure
Return typed JSON for records systems and validation, or Markdown for search and AI workflows.
Process
Send structured data into court management, recording, records management, or public access systems.
OUTPUT FORMATS
Confidence scores, coordinates, and page context included.
Choose output: "json" or Markdown per request.
Spatial JSON
For extraction · validation · review
{ "type": "keyValueRegion", "id": "kv_c1d2e3", "bounds": { "x": 82, "y": 128, "width": 340, "height": 96 }, "confidence": 0.98, "page": { "pageIndex": 0, "pageNumber": 1 }, "pairs": [ { "key": { "entityType": "QUESTION", "value": "Case number", "bounds": { "x": 82, "y": 128, "width": 100, "height": 24 }, "confidence": 0.99 }, "value": { "entityType": "ANSWER", "value": "2024-CV-008841", "bounds": { "x": 190, "y": 128, "width": 150, "height": 24 }, "confidence": 0.99 }, "relationshipConfidence": 0.97 }, { "key": { "entityType": "QUESTION", "value": "Filing type", "bounds": { "x": 82, "y": 164, "width": 100, "height": 24 }, "confidence": 0.98 }, "value": { "entityType": "ANSWER", "value": "Civil Complaint", "bounds": { "x": 190, "y": 164, "width": 130, "height": 24 }, "confidence": 0.98 }, "relationshipConfidence": 0.96 }, { "key": { "entityType": "QUESTION", "value": "Filing date", "bounds": { "x": 82, "y": 200, "width": 100, "height": 24 }, "confidence": 0.99 }, "value": { "entityType": "ANSWER", "value": "2024-03-15", "bounds": { "x": 190, "y": 200, "width": 100, "height": 24 }, "confidence": 0.99 }, "relationshipConfidence": 0.97 } ]}Markdown
For RAG · search · knowledge bases
# Court Filing — Civil Complaint
**Case number** 2024-CV-008841**Court** Superior Court, Los Angeles County**Filing date** March 15, 2024
## Parties
| Role | Name || --- | --- || Plaintiff | Riverside Capital LLC || Defendant | Oakwood Properties Inc |
**Judge** Hon. Patricia Vega**Filing type** Civil ComplaintRegional processing options
Choose supported processing regions for government and enterprise deployments.
SOC 2 Type 2 audited
Audited annually. Reports available under NDA for enterprise customers.
Trust and compliance
TLS encryption by default
All API communication is encrypted. Unencrypted requests are rejected.
Yes. For handwritten fields, stamps, and mixed-format documents, the API applies intelligent character recognition to capture what standard OCR misses. Every extracted value includes a confidence score so uncertain fields can be flagged for staff review before moving downstream.
Data Extraction API processes PDFs; images (including scans and photos); and Word, Excel, and PowerPoint files. It handles scanned court documents, image-based filings, and mixed digital/image records without requiring a separate OCR pipeline.
Nutrient Data Extraction API is an extraction layer, not a court management, recording, or records management platform. It turns document content into structured data so that data can be reviewed, validated, and routed into the systems organizations and software providers already use.
Every extracted element includes confidence scores, page references, and coordinates so teams can flag low-confidence fields for review, trace values back to the source document, and validate results before they enter case management, recording, or public access systems.
Use the schema generator in Studio — upload example filings, deeds, or clerk documents and describe the document type. It generates a JSON Schema for the /extract endpoint. Fields like case number, parties, recording information, and legal descriptions can also be defined manually. Refer to the documentation for supported field types and limits.
Use agentic mode for degraded scans, older handwritten filings, and documents with complex visual layouts where understand mode produces insufficient results. Agentic mode adds a vision language model (VLM) on top of the understand pipeline for complex visual content. It costs 18 credits per page.