Document Processing

Extract structured records from invoices, contracts and forms, with a review threshold before anything is written.

Integrations

ERP
1C
Microsoft 365
Google Workspace
REST API

The task

Documents arrive as PDFs, scans and email attachments, and someone reads each one and types its contents into another system. It is high volume, low judgement, and exactly the transcription task where human error rates are highest.

What it works from

PDFs, scans and photographs of documents
Email attachments from a monitored mailbox
Your field definitions and validation rules
Reference data for matching — suppliers, contracts, accounts

The automated workflow

A document arrives and its type is classified.
Text is extracted, with OCR applied to scans and images.
Fields are extracted according to your definitions for that document type.
Values are validated — formats, arithmetic, dates, mandatory fields.
Entities are matched against reference data, and mismatches are flagged.
Confident, fully valid records are written to the target system.
Anything below threshold enters a review queue with the source page shown beside the extraction.

Where a human stays in control

A confidence threshold you set determines what is written automatically and what is reviewed.
Anything with a financial consequence above your limit is always reviewed, regardless of confidence.
Reviewers see the original document beside the extracted values, so checking is fast.
Every correction is recorded and used to improve extraction for that document type.

Integrations

ERP
Orders, inventory and finance records synchronised through a validated adapter rather than a nightly spreadsheet.
1C
Exchange with 1C configurations through supported interfaces, with reconciliation and a quarantine for bad records.
Microsoft 365
Identity, mail, calendars and document libraries, with permissions respected rather than bypassed.
Google Workspace
Sign-in, Drive, Sheets and Calendar as data sources and destinations for automated workflows.
REST API
Documented, versioned and authenticated endpoints — both consuming yours and exposing ours.

Expected effect

Described qualitatively. Actual impact depends on your volumes, data quality and process discipline.

Manual transcription drops to reviewing exceptions rather than typing every document.
Validation catches arithmetic and format errors that a tired reader would miss.
Processing continues at the same rate during volume peaks.
Every record carries a link back to the source document for audit.

Limits and what this does not do

Poor scans, handwriting and unusual layouts reduce accuracy, and no amount of tuning fully fixes a bad photograph.
A new document type needs configuration and a sample set before it works well.
It extracts and validates; it does not decide whether an invoice should be paid.
Legally significant documents should keep human sign-off regardless of measured accuracy.