The short answer
Document automation turns paper forms, scans and PDFs into structured records your systems can use. The steps are always the same: inventory, redesign what you control, capture the rest cleanly, extract, validate with rules and people, load into the right system, and keep originals as long as required. The biggest win is usually not clever extraction: it is replacing your own paper form with a digital one.
Step 1: take inventory
List every recurring document someone re-types: sender, monthly volume, layouts, key fields, destination, personal information (worksheet at the end). You will find two groups:
Documents you control
Intake forms, expense claims, timesheets, inspection checklists, applications.
Documents you do not control
Supplier invoices, packing slips, bank letters, government forms, customer purchase orders.
Step 2: redesign what you control
A web or mobile form with required fields, drop-downs and validation produces structured data with no extraction, and removes handwriting, the biggest cause of extraction errors.
Ask only what you need
Also supports the data minimization principles in many state privacy laws.
The right languages
Offer the languages your audience needs, where practical.
Accessible from the start
So everyone can complete the form.
Straight into systems
Into your ERP, CRM or case system, not an inbox.
Step 3: capture the rest cleanly
Capture quality decides extraction quality: consistent scan resolution, straight pages, one document per file, and email attachments routed to a dedicated mailbox, not personal inboxes.
Step 4: extract the fields
Modern services go well beyond plain OCR. Azure Document Intelligence is machine-learning OCR and document processing, with prebuilt invoice and receipt models and custom models (Microsoft Learn); Amazon Textract extracts text, forms and tables, with invoice and receipt operations (AWS).
Check the fine print: Amazon's identity-document operation is described for documents issued by the U.S. government, so confirm it covers the ID types you handle. Always test on your own real documents, including messy ones.
Step 5: validate with rules and people
Extraction produces suggestions, not facts.
Rules
Totals add up, dates are sensible, sender exists, no duplicates, tax makes sense for the state.
Confidence thresholds
Low-confidence fields go to a person.
A review queue
One screen with the image beside the extracted fields, for quick correction.
Feedback
Tracked corrections show which layouts or senders cause trouble.
A hypothetical example: field inspection forms
A property maintenance firm receives handwritten inspection sheets from technicians.
- Before: an office administrator re-types each sheet into the job system at the end of the week.
- Redesign: technicians complete a tablet form with required fields and photo upload; the job updates immediately.
- Remaining paper: subcontractors still send scanned sheets. These go through extraction, and any field below the confidence threshold lands in the administrator's review queue.
The firm would measure fewer sheets typed by hand and faster job close-out. No figures are assumed; they depend on volumes and how quickly subcontractors adopt the new process.
Step 6: load into your systems
Use scheduled imports (ERPNext's data import tool inserts or updates records from CSV or Excel) or API integrations that create records once a document is approved. Link each record to its original image so anyone can check the source.
Rather talk it through? If your team spends hours re-typing forms and PDFs, we can help you decide what to redesign, what to extract and how to connect it to your systems. Talk to a Promatics specialist
Step 7: keep records properly
Automation does not change record-keeping obligations. The IRS says how long to keep business records depends on the transaction and your tax situation: often about three years from filing, longer in some cases, with a separate minimum for employment tax records (IRS). Read its requirements for electronic and imaged records before you shred originals. State tax rules, payroll and employment laws, HIPAA for health records, or contract and industry requirements may set other periods; confirm current rules with your accountant. General information, not legal or tax advice.
What usually goes wrong
| Mistake | Consequence |
|---|---|
| Automating a bad form | It should have been redesigned |
| Testing on clean samples | Live documents are crumpled, handwritten, multi-page |
| No exception path | Low-confidence documents block the process or pass unchecked |
| Destroying paper too early | Images may not meet record-keeping requirements |
| Scattered personal information | Mailboxes, drives and extraction services with no retention rule |
When to bring in help
Redesigning one form in a tool you own, or trying built-in extraction on small volumes with every result checked, is often DIY. A professional pays off when documents feed financial or regulated records, come in many layouts, hold sensitive personal information or must reach your ERP or case system.
Our AI solutions and intelligent automation service designs capture, extraction and review, connected through workflow automation. For supplier invoices, see OCR invoice automation in your ERP.
Document inventory worksheet
| Document | Sender | Monthly volume | Layouts | Key fields | Destination system | Personal info? | Redesign or extract? |
|---|---|---|---|---|---|---|---|
- Every document you control has been considered for redesign.
- Extraction was tested on real, messy samples.
- Validation rules and confidence thresholds are written down.
- A review queue and an owner exist.
- Retention periods are confirmed before any originals are destroyed.
Sources and further reading
Product capabilities and guidance change. These are the primary sources this article relies on, checked on the review date above.
- What is Azure Document Intelligence in Foundry Tools?, Microsoft Learn
- What is Amazon Textract?, Amazon Web Services
- Internal Revenue Service, U.S. Internal Revenue Service
- Data Import, ERPNext documentation (Frappe)
This article is general information, not legal, accounting or security advice for your specific situation. Examples are hypothetical unless stated otherwise.