Leave request record preparation
For People operations leave intake teams
Prepare employee, dates, leave category and stated support from a leave form with fields you can edit. Entitlement decision external.
25 free credits/month · No card needed
See the workflow and review checksInspect a document example.
Synthetic documents · Expected output- employee name
- Example Employee - synthetic
- request date
- 2026-09-30
- leave type
- Example leave type - synthetic
- requested start date
- 2026-09-01
- requested end date
- 2026-09-30
- requested hours
- 8
- support reference
- DEMO-SUPPORT-0042
{
"employee_name": "Example Employee - synthetic",
"request_date": "2026-09-30",
"leave_type": "Example leave type - synthetic",
"requested_start_date": "2026-09-01",
"requested_end_date": "2026-09-30",
"requested_hours": 8,
"support_reference": "DEMO-SUPPORT-0042"
}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 leave form arrives for people operations leave intake teams. The next step needs employee, dates, leave category and stated support, recorded under the correct document reference before the information enters your people operations review register.
A leave request describes partial days rather than full days. Preserve hours and dates; entitlement and approval remain with the employer. 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
- Leave form PDFs
- Scanned or photographed leave form 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 employee name, request date, leave type, your application maps the reviewed record into your people operations review register. Keep the original document reference with the result. Entitlement decision 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 |
|---|---|---|
employee_name | string | Employee name exactly as printed in this leave form. Preserve identifiers and qualifiers; do not look up or infer missing information. |
request_date | date | Request date explicitly printed in this leave form. Keep it distinct from other dates; leave it empty if no calendar date is stated. |
leave_type | string | Leave type exactly as printed in this leave form. Preserve identifiers and qualifiers; do not look up or infer missing information. |
requested_start_date | date | Requested start date explicitly printed in this leave form. Keep it distinct from other dates; leave it empty if no calendar date is stated. |
requested_end_date | date | Requested end date explicitly printed in this leave form. Keep it distinct from other dates; leave it empty if no calendar date is stated. |
requested_hours | number | Requested hours as reported in this leave form. Preserve the labeled measure and its unit; do not estimate it. |
support_reference | string | Support reference exactly as printed in this leave form. Preserve identifiers and qualifiers; do not look up or infer missing information. |
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 leave request describes partial days rather than full days. Preserve hours and dates; entitlement and approval remain with the employer.
- Check request date, requested start date, requested end date against their own printed labels; leave an unstated date empty instead of deriving it.
- Resolve missing employee name, request date, leave type against the source before using the record.
Prove the fit on a representative batch.
Test leave form examples from the layouts your team actually receives. Include the exception described here: A leave request describes partial days rather than full days. Preserve hours and dates; entitlement and approval remain with the employer. Compare the extracted employee name, request date, leave type 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 leave form 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 people operations leave intake teams. Bring difficult leave form 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 leave request record preparation
Which fields can I capture from a leave form?
The starter schema contains employee name, request date, leave type, requested start date, requested end date, requested hours, support reference. 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 leave request record preparation?
A leave request describes partial days rather than full days. Preserve hours and dates; entitlement and approval remain with the employer. 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 people operations review 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. Entitlement decision 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.