Give acquisitions analysts a usable rent roll when the deal arrives
For Acquisitions analysts and real estate diligence teams
Extract a seller-supplied PDF rent roll into a consistent set of unit rows. Retain the report date and original rent labels so analysts can prepare their diligence workbook without silently treating a snapshot as verified property performance.
25 free credits/month · No card needed
See the workflow and review checks{
"property_name": "Example Courtyard Apartments",
"report_date": "2026-08-31",
"report_currency": "USD",
"unit_rows": [
{
"unit": "A101",
"occupancy_label": "Occupied",
"lease_end_date": "2027-06-30",
"monthly_lease_rent": 1800,
"monthly_market_rent": 1850
},
{
"unit": "A102",
"occupancy_label": "Vacant",
"monthly_lease_rent": 0,
"monthly_market_rent": 1900
}
],
"reported_unit_count": 2,
"reported_monthly_rent_total": 1800,
"report_notes": "Monthly lease rent total excludes vacant units."
}Synthetic data, not a live extraction. Real responses also include confidence, validation, and result status.
When this work lands on your desk
A broker sends a property package, and the acquisitions team needs a first-pass unit schedule before its internal diligence meeting.
Rent rolls vary by property system and report settings. Market rent, lease rent, concessions, and balances may appear in neighboring columns. Vacant units can lack tenant names, and summary rows can resemble units. Manual copying invites errors before the analyst even begins evaluating the property.
Start with the documents you already collect
- PDF rent roll exports
- Scanned unit schedules
- PDF occupancy reports with stated rent columns
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 analyst reviews the extracted unit schedule, maps it into the diligence workbook, and reconciles it with leases, financial statements, and later reports. Occupancy verification, revenue assumptions, and investment decisions remain with the acquisition team.
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 |
|---|---|---|
property_name | string | Property name shown on the report. |
report_date | date | As-of date of the supplied snapshot. |
report_currency | string | Currency stated on the report; ambiguous symbols need review. |
unit_rows | array | Unit, occupancy label, lease dates, and separately named printed rent columns. |
reported_unit_count | number | Printed summary count when present; not a reconstructed total. |
reported_monthly_rent_total | currency | A specifically labeled printed total, preserving its definition. |
report_notes | string | Visible exclusions or notes that qualify the report. |
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
- Exclude subtotals and property headings from unit rows.
- Keep market rent, lease rent, collections, and balances in distinct fields.
- Review vacant units and missing dates without inventing a tenant or lease term.
Prove the fit on a representative batch.
Use PDF reports from several property systems, including one with vacant units and a continued table. Check unit-row completeness and column assignments against the source before using the output in a diligence model.
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
A paid tier supports more incoming deals and schemas for lease abstracts or property financial statements. Separate branded sites can collect document packages for distinct acquisition pipelines, with your own association logic downstream.
For a tailored implementation
Discuss custom volume or long rent rolls when larger portfolios exceed the supported self-serve document 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 rent roll acquisition intake
Can I upload an Excel rent roll to this endpoint?
This workflow uses supported PDFs and images. Use a readable PDF export for document extraction; native spreadsheet ingestion is not represented by this example.
Does it verify occupancy or rental income?
No. The output reflects the supplied report. Your diligence process must establish occupancy, collections, lease terms, and the reliability of seller-provided figures.
Can it compare successive monthly rent rolls?
Extract each report with its date and stable unit references. Your application performs the association and period-to-period comparisons after review.
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.