Help tax intake teams prepare a usable file before preparer review
For Tax practice intake managers and preparer support teams
Capture the tax year, payer or employer details, and selected form boxes in a consistent intake record. Start with one form type, then expand the schemas your practice needs while keeping document completeness and preparation decisions with your staff.
25 free credits/month · No card needed
See the workflow and review checks{
"form_type": "W-2",
"tax_year": "2025",
"employer_name": "Example Payroll Company",
"employee_name": "Example Taxpayer",
"wages_box1": 62500,
"federal_withholding_box2": 7400,
"state_rows": [
{
"state": "CA",
"state_wages": 62500,
"state_withholding": 2600
}
]
}Synthetic data, not a live extraction. Real responses also include confidence, validation, and result status.
When this work lands on your desk
A client begins uploading tax documents and the intake team needs to organize the current-year forms before assigning the file to a preparer.
Client uploads can include duplicate copies, prior-year forms, corrected documents, and different members of the 1099 family. An intake record needs the form type and year alongside amounts; a generic amount field can erase the meaning of a numbered box before the preparer sees it.
Start with the documents you already collect
- W-2 PDFs and supported images
- 1099 variants using a schema for each relevant form
- Prior-year return PDFs using a separate intake schema
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
Your intake staff associates each reviewed extraction with the client, identifies duplicate or corrected forms, and tracks missing documents. A customer-built mapping can prepare records for tax software; the preparer owns calculations and filing.
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 schemaStarter fields are optional until you choose which are required. Nested line items need a defined structure if you want validation of their individual values.
| Field | Type | What to capture |
|---|---|---|
form_type | string | This example requests W-2; use another schema for different box definitions. |
tax_year | string | Year on the form, separate from the upload date. |
employer_name | string | Employer as printed on the W-2. |
employee_name | string | Employee name for staff-owned client association. |
wages_box1 | currency | Box 1 wages, tips, and other compensation. |
federal_withholding_box2 | currency | Box 2 federal income tax withheld. |
state_rows | array | State labels, wages, and withholding from the relevant state boxes. |
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
- Confirm tax year and form type before comparing any numbered box amounts.
- Check duplicate copies and corrected documents in the client’s full file.
- Review masked identifiers, multi-state rows, and cropped form edges without inferring missing values.
Prove the fit on a representative batch.
Evaluate a representative W-2 set with different layouts, a multi-state form, and a scan. Measure box-level corrections and intake preparation time before adding separate schemas for the 1099 variants your practice receives.
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
Seasonal volume supports more credits, while additional schemas cover distinct tax forms. Branded upload sites can serve practice locations or intake groups, and your own integration can route reviewed data to the next preparation step.
For a tailored implementation
Discuss custom seasonal volume, long client documents, or a larger portal rollout when the validated intake process exceeds self-serve scope.
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 tax season client intake
Can one schema cover every tax document?
Different forms assign different meanings to their boxes. Start with form-specific schemas and select the appropriate one for each file; this example does not promise automatic packet classification.
Does this calculate or file the client’s tax return?
No. Dokyumi extracts document fields. Your preparer and tax software handle calculations, eligibility decisions, completeness review, and filing.
Can I leave Social Security numbers out of the output?
Yes, omit fields you do not need from the schema. The full uploaded source and OCR data may still be processed or stored; review the security and privacy pages when setting your intake policy.
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.