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Receivables aging collection preparation

For Receivables collection analysts

Prepare customer, invoice, due date and aging balance from an ar aging with fields you can edit. Collection actions external.

25 free credits/month · No card needed

See the workflow and review checks

Inspect a document example.

Synthetic documents · Expected output
Standard documentPDF
receivables aging collection preparationFictional sample · For demonstration
report date
2026-09-30
customer name
Example Customer LLC - synthetic
customer reference
DEMO-CUSTOMER-0042
invoice rows
[ { "customer_name": "Example Customer LLC - synthetic", "invoice_reference": "DEMO-INVOICE-0042", "invoice_date": "2026-09-30", "due_date": "2026-11-30", "open_amount": 1250, "aging_bucket": "Current" } ]
stated open balance
1250
{
  "report_date": "2026-09-30",
  "customer_name": "Example Customer LLC - synthetic",
  "customer_reference": "DEMO-CUSTOMER-0042",
  "invoice_rows": [
    {
      "customer_name": "Example Customer LLC - synthetic",
      "invoice_reference": "DEMO-INVOICE-0042",
      "invoice_date": "2026-09-30",
      "due_date": "2026-11-30",
      "open_amount": 1250,
      "aging_bucket": "Current"
    }
  ],
  "stated_open_balance": 1250
}

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 ar aging arrives for receivables collection analysts. The next step needs customer, invoice, due date and aging balance, recorded under the correct document reference before the information enters your accounting review queue.

An aging report includes unapplied credits in a separate section. Keep their sign and reference rather than assigning them to the oldest invoice. 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

  • AR aging PDFs
  • Scanned or photographed ar aging pages

PDF, JPEG, PNG, TIFF, or WEBP. Send one file per extraction call; create separate schemas when the document types need different fields.

  1. Define the fields

    Open the starter schema. Edit field descriptions, mark the values your process requires, and save it in your account.

  2. Extract at intake

    Send the document and saved schema slug to POST /api/v1/extract, or collect the file through a branded upload site.

  3. Hand off reviewed data

    After checking report date, customer name, customer reference, your application maps the reviewed record into your accounting review queue. Keep the original document reference with the result. Collection actions 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 schema

Choose required fields for your process. The starter schema preserves any defined nested fields; refine line-item structures and test them on representative files.

FieldTypeWhat to capture
report_datedateReport date explicitly printed in this ar aging. Keep it distinct from other dates; leave it empty if no calendar date is stated.
customer_namestringCustomer name exactly as printed in this ar aging. Preserve identifiers and qualifiers; do not look up or infer missing information.
customer_referencestringCustomer reference exactly as printed in this ar aging. Preserve identifiers and qualifiers; do not look up or infer missing information.
invoice_rowsarrayEvery visible invoice rows row in this ar aging. Preserve separate rows, labels and qualifiers; do not merge entries or reconstruct missing ones.
stated_open_balancecurrencyStated open balance explicitly labeled in this ar aging. Preserve its sign and stated currency; do not calculate a missing amount.

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 contract

Run a synthetic response through a review gate

Checks for this process

  • An aging report includes unapplied credits in a separate section. Keep their sign and reference rather than assigning them to the oldest invoice.
  • Check report date against their own printed labels; leave an unstated date empty instead of deriving it.
  • Check stated open balance for signs, decimal placement and stated currency before any downstream calculation or posting.
  • Compare every invoice rows row with the source, including continuation pages, separate categories and repeated table headings.

Prove the fit on a representative batch.

Test ar aging examples from the layouts your team actually receives. Include the exception described here: An aging report includes unapplied credits in a separate section. Keep their sign and reference rather than assigning them to the oldest invoice. Compare the extracted report date, customer name, customer reference 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 ar aging 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 receivables collection analysts. Bring difficult ar aging samples and the review requirements your implementation must preserve.

Talk through document mix and volume

Start 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.

Free

$0/month

  • 25 credits/month
  • 2 schemas
  • 1 branded upload site
Test this workflow

Starter

$99/month

  • 500 credits/month
  • 10 schemas
  • 5 branded upload sites
Explore Starter

Growth

$499/month

  • 3,000 credits/month
  • 50 schemas
  • 25 branded upload sites
Explore Growth

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 receivables aging collection preparation

Which fields can I capture from an ar aging?

The starter schema contains report date, customer name, customer reference, invoice rows, stated open balance. 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 receivables aging collection preparation?

An aging report includes unapplied credits in a separate section. Keep their sign and reference rather than assigning them to the oldest invoice. 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 accounting review queue?

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. Collection actions 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.