Stop on uncertainty
The agent must not guess missing values. Low-confidence or conflicting data should be reviewed.
Automation example
AI data extraction from PDF and scans
Convert PDFs and scanned documents into structured, validated data that can be used by ERP, accounting, CRM or another workflow.
In short
Convert PDFs and scanned documents into structured, validated data that can be used by ERP, accounting, CRM or another workflow.
From trigger to result
A controlled workflow
Identify document typeChecked step in the process
Run OCR when neededChecked step in the process
Extract configured fields and tablesChecked step in the process
Check formats, totals and referencesChecked step in the process
Flag low-confidence valuesChecked step in the process
Send approved data to the target systemChecked step in the process
Systems and data
PDF, scans, OCR, document storage, ERP, CRM and databases
We confirm the exact interfaces and permissions before implementation.
Human control
Keep evidence
Source documents, validation results and important actions should remain traceable.
Measure the result
Compare human time, errors, rework and exception rate before and after the pilot.
FAQ
Sometimes, but the safe level of autonomy depends on data quality, business rules and the impact of a wrong action.
The standard design is to stop, explain what is missing and route the case to a person instead of guessing.
Next step
Show us one repetitive process.
We will review how it works today, which systems are involved and what can realistically be automated.