Many companies are still trying to figure out how to speed up invoice processing and reduce the number of manual checks. A big difference is made in the approval process itself, but also in the quality of data when the document is received. The new AI engine in iNVOiCE FLOW is based on a different logic than traditional OCR and brings more reliable invoice extraction - meaning fewer corrections, faster workflow and more stable accounting processes.
Extraction using OCR works on the principle of a structured shirt. The system expects the invoice to have a certain structure and searches for data in fixed positions. This is fast if suppliers always use the same layout. The moment the document changes even slightly, the accuracy of extraction drops significantly.
The accounting team then manually corrects errors caused not by the content of the invoice, but by the system's inability to handle document variability.
AI mining works differently. It doesn't look for text in a specific place, but tries to understand what each piece of data represents. Aurora - the new AI engine in iNVOiCE FLOW - is designed to handle different layouts of information without the need to set up new templates. It's not about "understanding" the document like a human, but it can recognize the structure of an invoice, find basic accounting data in a different visual format, and pre-fill it with much higher reliability than classic OCR.
It is this difference - OCR (often a fixed template) vs. AI (document structure recognition) - that is why there are fewer errors and less manual intervention today.
Better quality data = faster entry into workflow
If the invoice is read accurately at the input, it enters the approval workflow earlier and without corrections. Documents do not accumulate at the first checks, the accountant does not have to stop the process because of small things, and the individual steps follow each other smoothly. Companies that have multi-stage approval see the difference almost immediately.
More stable accounting data and less work on closings
More accurate data extraction has a direct impact on accounting . Fewer errors mean less tracking down at closing, less improvisation, and fewer situations where you have to figure out why the data doesn't match the approval part of the process.
The AI engine in iNVOiCE FLOW also gradually gets better at recognizing invoices that appear regularly in the company. This increases the accuracy of extraction over time without users having to set anything up.
Where fragmentation previously arose, stable data input comes into play, on which fast and predictable accounting work can be built.
How AI mining can work in your environment
AI invoice extraction is one of the most practical places today where AI can immediately relieve accounting teams - without complex process changes or work organization. If you want to see how more accurate extraction and faster workflow will work on your document types, we would be happy to connect with you and show you how AI extraction can work in your environment.
Are you dealing with invoice approval?
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