Promissory note servicing setup
For Loan servicing onboarding specialists
Prepare principal, stated rate, maturity and payment terms from an executed note with fields you can edit. Servicing calculations external.
25 free credits/month · No card needed
See the workflow and review checksInspect a document example.
Synthetic documents · Expected output- borrower name
- Example Borrower - synthetic
- lender name
- Example Lender - synthetic
- note date
- 2026-09-30
- principal amount
- 1250
- stated rate
- 5.5
- maturity date
- 2026-11-30
- payment terms text
- Payment due 30 days after the invoice date, as stated in this synthetic source.
{
"borrower_name": "Example Borrower - synthetic",
"lender_name": "Example Lender - synthetic",
"note_date": "2026-09-30",
"principal_amount": 1250,
"stated_rate": 5.5,
"maturity_date": "2026-11-30",
"payment_terms_text": "Payment due 30 days after the invoice date, as stated in this synthetic source."
}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 executed note arrives for loan servicing onboarding specialists. The next step needs principal, stated rate, maturity and payment terms, recorded under the correct document reference before the information enters your loan intake worksheet.
A variable-rate note names an index and margin in a separate clause. Preserve the complete payment text rather than turning a stated rate into a forecast. 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
- Executed note PDFs
- Scanned or photographed executed note 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 borrower name, lender name, note date, your application maps the reviewed record into your loan intake worksheet. Keep the original document reference with the result. Servicing calculations 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 |
|---|---|---|
borrower_name | string | Borrower name exactly as printed in this executed note. Preserve identifiers and qualifiers; do not look up or infer missing information. |
lender_name | string | Lender name exactly as printed in this executed note. Preserve identifiers and qualifiers; do not look up or infer missing information. |
note_date | date | Note date explicitly printed in this executed note. Keep it distinct from other dates; leave it empty if no calendar date is stated. |
principal_amount | currency | Principal amount explicitly labeled in this executed note. Preserve its sign and stated currency; do not calculate a missing amount. |
stated_rate | number | Rate printed in the source. Preserve its stated unit or rate basis separately. |
maturity_date | date | Maturity date explicitly printed in this executed note. Keep it distinct from other dates; leave it empty if no calendar date is stated. |
payment_terms_text | string | Payment terms text exactly as printed in this executed note. 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 variable-rate note names an index and margin in a separate clause. Preserve the complete payment text rather than turning a stated rate into a forecast.
- Check note date, maturity date against their own printed labels; leave an unstated date empty instead of deriving it.
- Check principal amount for signs, decimal placement and stated currency before any downstream calculation or posting.
Prove the fit on a representative batch.
Test executed note examples from the layouts your team actually receives. Include the exception described here: A variable-rate note names an index and margin in a separate clause. Preserve the complete payment text rather than turning a stated rate into a forecast. Compare the extracted borrower name, lender name, note date 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 executed note 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 loan servicing onboarding specialists. Bring difficult executed note 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 promissory note servicing setup
Which fields can I capture from an executed note?
The starter schema contains borrower name, lender name, note date, principal amount, stated rate, maturity date, payment terms text. 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 promissory note servicing setup?
A variable-rate note names an index and margin in a separate clause. Preserve the complete payment text rather than turning a stated rate into a forecast. 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. Servicing calculations 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.