Data

Document & Data Automation

Documents arrive, data comes out structured—with review where accuracy matters.

Discuss your business problem
The problem

Invoices, forms, orders and contracts arrive as PDFs, scans and photographs. Someone reads each one and types the contents into another system, every day.

What gets built
  • Extraction from PDFs, scans and images into structured records
  • Validation rules that catch inconsistencies before they enter your systems
  • Human review queues for low-confidence or high-value items
  • Direct delivery into your accounting, ERP or database
What changes

Manual data entry largely removed, with fewer transcription errors and a clear audit trail.

When this is not the right fit

If volume is genuinely low—a handful of documents a week—the setup will cost more than the time it saves. Volume is the deciding factor.

How it works

1. Sample document review

Real invoices, forms and contracts are collected, and the fields to extract—amount, date, party names and so on—are defined.

2. Building the extraction model

Extraction logic matching the document type is built and tested across varying formats and quality levels.

3. Validation rules

Rules are added to catch inconsistencies, such as totals that do not add up.

4. Delivery and human review

High-confidence results go straight into your systems; low-confidence cases go to a review queue.

Use cases

Invoice processing

Supplier invoices are read automatically and delivered into accounting software as structured records.

Contract data extraction

Party names, dates and key terms are pulled automatically from contract text into a spreadsheet.

Order form processing

Paper or PDF order forms enter your warehouse or CRM system directly as structured data.

Document and ID verification

Uploaded documents are checked automatically for required fields, with missing ones flagged.

Frequently asked questions

Does it work with handwritten documents?

Depending on quality, yes—though accuracy is typically lower than with printed documents. Testing on a sample is recommended first.

How risky is incorrectly extracted data?

Validation rules catch inconsistencies, and low-confidence cases go to human review automatically—bad data does not silently enter your systems.

What volume makes this worthwhile?

Generally, tens of documents a week or more shows a clear return. At lower volumes, manual work can be cheaper, as noted in the "not for" section.

Does it integrate with our accounting or ERP system?

In most cases yes, provided a suitable integration point exists. This is checked during discovery.

Have a process that could work better?

Describe it in a few sentences. You will get an honest view of whether it is worth automating—before any proposal.

Discuss your business problem