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AI Automation

Automated data extraction from invoices and documents

Context and approach

Traditional document readers break whenever a supplier changes the layout of an invoice or purchase order. Teams are then forced to type lines and totals by hand into accounting and management software.

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Documents in, decisions out

Varied documents go in, structured results come out, a person validatesThree documents slide into a box; a results table comes out; a checkpoint with a tick lights up between the two.
Invoices, contracts and forms read as they are and turned into clean fields.

When this helps

  • Your teams type invoices, purchase orders or contracts by hand.
  • Data entry errors surface late, when accounts are reconciled.
  • Your suppliers send documents in many different layouts.

When it does not. If you receive few documents, always in the same format, a simple import may be enough.

How we work

Sample

We start from your real documents to define the fields to extract and the checks to run.

Extraction

Each file is read, its totals and identifiers are checked, and doubtful cases are set aside.

Export

Verified data flows into your accounting or operations software.

What we deliver

Automated reading of invoices, purchase orders, contracts and tables
Conversion of raw document text into clean, structured records
Automatic checks on totals, dates and company identifiers
Direct export of verified records into your accounting or business software

Common questions

Does this work on scanned or photographed documents?

Yes, it handles tilted scans and lower-quality copies, and routes unclear files to a team member for review.

How does the extracted data reach our accounting software?

Verified records are exported automatically in the exact format expected by your accounting or operations tool.

Can our team review flagged documents before export?

Yes, a simple review screen lets your staff inspect flagged files and approve corrections in one click.

What happens with a document format it has never seen?

The system tries to read it and flags uncertain fields for approval. Corrections from your team are then used to adjust the checks.

Typical use cases

Let’s talk about your project

Tell us what you need in a few lines and we will reply directly.

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