Court filing docket record capture
For Legal docket document coordinators
Prepare case, court, filing label and stated date from a filed document with fields you can edit. Docket verification external.
25 free credits/month · No card needed
See the workflow and review checksInspect a document example.
Synthetic documents · Expected output- case reference
- DEMO-CASE-0042
- court name
- Example Court - synthetic
- filing label
- Example filing label - synthetic
- filing date
- 2026-09-30
- party names text
- Party names text explicitly printed in the original synthetic source for reviewer context.
- document reference
- DEMO-DOCUMENT-0042
- stated hearing date
- 2026-09-30
{
"case_reference": "DEMO-CASE-0042",
"court_name": "Example Court - synthetic",
"filing_label": "Example filing label - synthetic",
"filing_date": "2026-09-30",
"party_names_text": "Party names text explicitly printed in the original synthetic source for reviewer context.",
"document_reference": "DEMO-DOCUMENT-0042",
"stated_hearing_date": "2026-09-30"
}A complete synthetic document with the visible values shown below. Real responses also include model-reported confidence, validation and result status. Test your own file with this schema.
When this work lands on your desk
A filed document arrives for legal docket document coordinators. The next step needs case, court, filing label and stated date, recorded under the correct document reference before the information enters your contract document register.
A filing lists a service date and a separate hearing date. Keep the labels and do not treat the file as a verified docket update. This schema keeps the source labels and values explicit so the reviewer can resolve the issue before downstream use.
Start with the documents you already collect
- Filed document PDFs
- Scanned or photographed filed document pages
PDF, JPEG, PNG, TIFF, or WEBP. Send one file per extraction call; create separate schemas when the document types need different fields.
Define the fields
Open the starter schema. Edit field descriptions, mark the values your process requires, and save it in your account.
Extract at intake
Send the document and saved schema slug to
POST /api/v1/extract, or collect the file through a branded upload site.Hand off reviewed data
After checking case reference, court name, filing label, your application maps the reviewed record into your contract document register. Keep the original document reference with the result. Docket verification external. Dokyumi processes one file with a saved schema; your application owns record matching, business rules and updates to other systems.
A schema shaped around the next step.
Start with these fields, then adjust them to match your documents and destination system. The example above shows the data object you are asking Dokyumi to extract.
Download editable starter schemaChoose required fields for your process. The starter schema preserves any defined nested fields; refine line-item structures and test them on representative files.
| Field | Type | What to capture |
|---|---|---|
case_reference | string | Case reference exactly as printed in this filed document. Preserve identifiers and qualifiers; do not look up or infer missing information. |
court_name | string | Court name exactly as printed in this filed document. Preserve identifiers and qualifiers; do not look up or infer missing information. |
filing_label | string | Filing label exactly as printed in this filed document. Preserve identifiers and qualifiers; do not look up or infer missing information. |
filing_date | date | Filing date explicitly printed in this filed document. Keep it distinct from other dates; leave it empty if no calendar date is stated. |
party_names_text | string | Party names text exactly as printed in this filed document. Preserve identifiers and qualifiers; do not look up or infer missing information. |
document_reference | string | Document reference exactly as printed in this filed document. Preserve identifiers and qualifiers; do not look up or infer missing information. |
stated_hearing_date | date | Stated hearing date explicitly printed in this filed document. Keep it distinct from other dates; leave it empty if no calendar date is stated. |
Give exceptions a clear path to review.
Dokyumi returns a model-reported confidence map, validation details, and a completed or review status for produced results. Check required fields and your business rules before passing data onward.
A completed extraction describes the extraction result. Your application and reviewers own matching, approvals, routing, and updates to other systems.
Read the response contractChecks for this process
- A filing lists a service date and a separate hearing date. Keep the labels and do not treat the file as a verified docket update.
- Check filing date, stated hearing date against their own printed labels; leave an unstated date empty instead of deriving it.
- Resolve missing case reference, court name, filing label against the source before using the record.
Prove the fit on a representative batch.
Test filed document examples from the layouts your team actually receives. Include the exception described here: A filing lists a service date and a separate hearing date. Keep the labels and do not treat the file as a verified docket update. Compare the extracted case reference, court name, filing label and any line rows with a reviewer's checked reference before enabling downstream actions.
Compare extracted values with a reviewer’s reference set. Record corrections, unresolved fields, review time, and credits used before connecting downstream actions.
The free plan’s credit limits apply. Assisted pilots are scoped with Dokyumi before work begins.
Expand when the next process is ready
Add recurring extraction capacity when filed document intake becomes routine. Reuse this field contract for layouts that express the same information; create a separate schema when the next document has different fields or review requirements.
For a tailored implementation
Discuss document volume, page lengths and schema setup for legal docket document coordinators. Bring difficult filed document samples and the review requirements your implementation must preserve.
Talk through document mix and volumeStart small. Add capacity as intake grows.
All self-service plans include the REST API, upload-site webhooks, custom confidence thresholds, and schema inference. Choose by volume, schema count, and upload sites.
Each document uses one credit per 5 pages, rounded up. An 8-page file uses 2 credits. Self-service files can be up to 50 pages; larger files, custom-built schemas, and additional volume are quoted through Enterprise. Full pricing details
Questions about court filing docket record capture
Which fields can I capture from a filed document?
The starter schema contains case reference, court name, filing label, filing date, party names text, document reference, stated hearing date. Edit those definitions and choose your required fields before saving. Array fields include defined sub-fields so row values have a validation structure.
What needs review in court filing docket record capture?
A filing lists a service date and a separate hearing date. Keep the labels and do not treat the file as a verified docket update. Check the original source alongside model-reported confidence and validation output; completion status describes the extraction result, not the business decision.
How does this data reach your contract document register?
Save the schema, then send one supported PDF or image to POST /api/v1/extract with its slug. The response contains the data, model-reported confidence, validation and result status. Your application maps reviewed values to the destination; upload-site submissions can use a configured webhook. Docket verification external.
How do I test this workflow on my own documents?
Start free with 25 credits per month, 2 schemas, and 1 branded upload site. The starter schema opens in the schema builder after sign-up. Edit the fields, save it, and upload a representative file through your account or the extraction API. Account documents are stored according to Dokyumi’s privacy policy; contact hello@dokyumi.com for deletion requests and retention requirements.