Equipment collateral schedule capture
For Equipment finance intake teams
Prepare serial identifier, description, owner and stated value from an equipment schedule with fields you can edit. No valuation.
25 free credits/month · No card needed
See the workflow and review checksInspect a document example.
Synthetic documents · Expected output- business name
- Example Harbor Services LLC - synthetic
- schedule date
- 2026-09-30
- equipment rows
- [ { "serial_number": "DEMO-SERIAL-0042", "description": "Example document line - original synthetic data", "stated_value": 1250, "location_text": "Location text explicitly printed in the original synthetic source for reviewer context.", "ownership_note": "Jointly held as stated; reviewer checks ownership share." } ]
- stated total value
- 1250
- valuation basis
- Value stated by the applicant; no independent valuation.
{
"business_name": "Example Harbor Services LLC - synthetic",
"schedule_date": "2026-09-30",
"equipment_rows": [
{
"serial_number": "DEMO-SERIAL-0042",
"description": "Example document line - original synthetic data",
"stated_value": 1250,
"location_text": "Location text explicitly printed in the original synthetic source for reviewer context.",
"ownership_note": "Jointly held as stated; reviewer checks ownership share."
}
],
"stated_total_value": 1250,
"valuation_basis": "Value stated by the applicant; no independent valuation."
}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
An equipment schedule arrives for equipment finance intake teams. The next step needs serial identifier, description, owner and stated value, recorded under the correct document reference before the information enters your loan intake worksheet.
An equipment list has two similar machines with different serial numbers. Preserve each row and its stated value instead of merging the assets. 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
- Equipment schedule PDFs
- Scanned or photographed equipment schedule 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 business name, schedule date, equipment rows, your application maps the reviewed record into your loan intake worksheet. Keep the original document reference with the result. No valuation. 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 |
|---|---|---|
business_name | string | Business name exactly as printed in this equipment schedule. Preserve identifiers and qualifiers; do not look up or infer missing information. |
schedule_date | date | Schedule date explicitly printed in this equipment schedule. Keep it distinct from other dates; leave it empty if no calendar date is stated. |
equipment_rows | array | Every visible equipment rows row in this equipment schedule. Preserve separate rows, labels and qualifiers; do not merge entries or reconstruct missing ones. |
stated_total_value | currency | Stated total value explicitly labeled in this equipment schedule. Preserve its sign and stated currency; do not calculate a missing amount. |
valuation_basis | string | Valuation basis exactly as printed in this equipment schedule. 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
- An equipment list has two similar machines with different serial numbers. Preserve each row and its stated value instead of merging the assets.
- Check schedule date against their own printed labels; leave an unstated date empty instead of deriving it.
- Check stated total value for signs, decimal placement and stated currency before any downstream calculation or posting.
- Compare every equipment rows row with the source, including continuation pages, separate categories and repeated table headings.
Prove the fit on a representative batch.
Test equipment schedule examples from the layouts your team actually receives. Include the exception described here: An equipment list has two similar machines with different serial numbers. Preserve each row and its stated value instead of merging the assets. Compare the extracted business name, schedule date, equipment rows 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 equipment schedule 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 equipment finance intake teams. Bring difficult equipment schedule 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 equipment collateral schedule capture
Which fields can I capture from an equipment schedule?
The starter schema contains business name, schedule date, equipment rows, stated total value, valuation basis. 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 equipment collateral schedule capture?
An equipment list has two similar machines with different serial numbers. Preserve each row and its stated value instead of merging the assets. 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 loan intake worksheet?
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. No valuation.
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.