AI reads the documents. People check instead of retyping.

AI reads the document the way a person would: it finds the fields you need, recognises what each one means and arranges them in a structured record. In a contract these may be the parties, the deadlines and the terms; in an application or a form, the data the customer filled in. The fields are then validated and written to your CRM, ERP or spreadsheet.

The difference from plain text recognition is the checking. The solution knows which fields it is looking for, validates them and flags when it is unsure. When confidence is low, the document stops for review by one of your people before the data reaches the system. That person corrects what is needed and confirms the record instead of retyping the whole document. The solution is part of our AI business process automation service and is tuned to the documents you actually receive.

You start with the document types that take up the most time today. We do not automate everything at once: in the first week we pick the types with the highest volume, look at where they come from and which system the data has to go into. Typical examples are applications and forms from customers whose data goes into the CRM, contracts from which deadlines and terms are extracted, and waybills and accompanying documents in logistics.

If your main flow is invoices, there is a separate solution for them: AI invoice automation, which sorts incoming and outgoing invoices and passes the data to your ERP. This page is about all other documents. If you have few documents or each one is different, manual processing may remain the better deal, and we will tell you so on the first call. It is free, takes 30 minutes, and afterwards you know whether it makes sense to continue.

Yes, the solution also works with scanned documents, as long as their quality allows them to be read. We do not promise this in advance for every document: we test it in the pilot with your real scans and see which go through on their own and which go to a person for review. Scanned documents go through the same check rules as the others, so uncertain fields stop for review by a person. If a document type is hard to read, you see it during the pilot, not after go-live.

Where the data stays is decided together with you. The architecture is agreed against your data and security requirements: where documents come in, where they are processed and which system they are written to. The solution connects to the systems you already use and does not require you to buy a new platform. The code, the model instructions and the deployment are yours, so control over the solution stays with your company after the project ends.

The first measurable results usually come within 2–4 weeks of the start. As a standalone project we start with a free call, a review of the documents and agreed metrics, then tune the extraction and run it in a pilot on real documents under supervision. Every solution is measured against its baseline for time, cost and errors, and if it does not deliver, it does not reach production. We stop it and pick the next process.

In a full AI transformation with the Encorp AIM (AI Implementation Method), data extraction is one of the processes chosen at Gate 1 from the opportunity map. There the test is a pilot in phase 2, with real documents and agreed metrics, and the solutions that work go into production in weeks 11–12. After go-live they move to AI Ops: support, improvements and new processes every month, with response within 24 hours.