Free Guide for Lenders, HR Teams & Property Managers
A practical guide to automating pay stub data extraction for income verification.
How lenders, HR teams, and property managers verifying income replace manual pay stub data entry with an upload-review-export workflow.
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Income verification means reviewing pay stubs from ADP, Gusto, Paychex, and dozens of other formats.
Manually pulling gross pay, YTD totals, and deductions off each stub is slow, repetitive work.
Applicants submit phone photos of pay stubs, and the image quality is often rough.
Your team spends hours on data entry that adds zero judgment to the actual decision.
Errors in manually keyed pay stub data create liability and compliance risk.
Four steps, from document to structured data:
PDF, scan, or photo from any payroll provider — no format restrictions for applicants.
Employee and employer names, pay period, gross pay, net pay, itemized deductions, and YTD totals as structured fields.
Each field carries a confidence score, so low-quality photos get flagged for a human look instead of silently guessed.
Export JSON/CSV/Excel or use the API to push verified income data into your origination, HR, or property-management system.
Combine automation with explicit review and source-document checks. Test representative inputs, use confidence signals, and define quality checks before you automate higher-volume work.
Convert supported pay stubs into consistently named data for review and export.
Route uncertain fields to a person instead of treating every extracted value as equally reliable.
Evaluate the workflow with your own layouts and image-quality range before scaling.
Move from manual uploads to an integrated workflow after review rules are established.
Verify sensitive tax, legal, medical, and financial fields before downstream use.
Every extraction returns these fields as structured data with per-field confidence scores:
Pay stub data exports as CSV/Excel for underwriting files or flows via the REST API into loan-origination, applicant-screening, and HR systems. Batch upload processes applicant pipelines in one pass.
The Tax Preparer’s AI Automation Playbook
A free PDF playbook covering AI extraction workflows, quality control, batch processing, and API integration for tax-document operations.
9 practical chapters covering evaluation, review, integration, and operations.
Identify where pay stub data enters, who reviews it, and where the approved result goes.
Build a test set covering common layouts, scans, photos, and known edge cases.
Upload a supported file and inspect the returned fields, structure, and confidence signals.
Set thresholds and source-document checks for fields that matter to the decision or filing.
Map reviewed JSON, CSV, or Excel fields to the destination system.
Introduce higher-volume processing only after the single-file workflow is reliable for your inputs.
Use authentication, retries, validation, and exception handling in an integrated workflow.
Confirm access, retention, deletion, and audit requirements for the data you process.
Track review outcomes, add edge cases to the test set, and revisit thresholds as layouts change.
Intake forms, processing checklists, and quality-control templates.
A consistent checklist for comparing document-parsing tools and workflow fit.
Authentication, structured output, validation, and error-handling patterns.
Employee & employer name; Pay period dates; Gross pay; Net pay; Federal & state tax withheld; FICA (Social Security & Medicare); YTD totals. Each field comes back with a confidence score, and results export to JSON, CSV, or Excel.
No. The core workflow is upload, review, and export, all in the browser. Developers can additionally use the REST API and batch upload, but nothing requires code.
PDF (including scanned), PNG, JPG, and WEBP. Native PDFs, scans, and phone photos all work, with confidence scores flagging anything hard to read.
Your first 3 documents are free with no credit card. Paid plans start at $9/month, and every plan includes API access and all export formats.
No. It focuses on document intake, representative testing, confidence-based review, structured exports, API integration, and exception handling.
The early chapters use the browser-based workflow. The API section is optional and intended for teams that want a programmatic integration.
The core workflow is tool-agnostic and emphasizes evaluation criteria you can apply to document-extraction products, including this one.
Check this page for the current version as the product and recommended review practices evolve.