Automated document extraction: How AI document processing works in the back office

How does automated extraction work in practice?

A successful start requires a clear focus. Instead of automating all receipts at once, one specific process is enough for the first step. In a pilot project, we proceed systematically from requirement to implementation.

The process is divided into three clear steps:

• Limit the document type: We jointly clarify the formats, the required mandatory fields, the monthly volume and the current workload. This creates a defined test scope.
• Test with examples: We compare the data extracted by the AI with verified target values. We record errors, exceptions and the remaining checking effort for your team.
• Decide on implementation: You receive an evaluation, a proposal for the future workflow and a cost estimate for the connection to your systems and operation.

The goal is for your team to stop typing standard data and only check disputed fields. We jointly determine which fields and items you need. We then test the recognition on a representative selection of your documents. You can find further details on this approach in our AI document processing.

Which workflows are suitable for AI document processing?

Many structured and semi-structured documents can be processed, provided the scan quality and layout are sufficient. Typical back-office use cases include incoming orders, price lists, property details or service reports. By automatically extracting PDF documents, you turn unstructured files into usable data sets for your CRM or ERP system.

A good example of a sensible application is quote automation in technical trade. Customers often mix article numbers, free text descriptions and incomplete features in their email or spreadsheet enquiries. Sales currently transfers these lines manually, searches for suitable products in the catalogue and later types the confirmed quote again as an order.

With automation, the customer list is broken down into items, quantities and open features. The items are matched with your product group. Unambiguous matches are assigned. Missing features and unclear descriptions are presented to your team for review. Sales confirms prices, availability and delivery details from an approved pricing source before the quote goes to the customer.

How do we avoid errors when automatically extracting PDF documents?

An AI makes mistakes. Therefore, professional human control is an integral part of the process. Missing information, contradictions and uncertain results are submitted for review according to agreed rules. A human gives approval before a process continues or data is written into your system.

A project from the real estate sector shows how well this works in practice. For the Berlin estate agent Everpeak Properties, apartment details, price lists and floor plans of new building projects are automatically extracted and created directly in the Propstack CRM. From there, the properties appear on the website and in the app.

The system is live. So far, 156 apartments from three projects have been extracted and created. In the first project with 69 apartments, the cross-check with the original documents showed zero discrepancies. This was based on a test with real documents in which every discrepancy was logged. How well recognition works on your documents is exactly what the pilot test shows. Read more about this in the description of the Everpeak project.

How much does AI-supported document processing cost?

We work with fixed prices for each step, which you receive in writing beforehand. A pilot usually takes two to six weeks and covers one document type with up to 300 documents. We define the fields and checking rules, present unclear areas for review and deliver an agreed export as Excel or CSV.

The following overview shows the guide prices for the pilot and ongoing operation. The effort depends on the data quality and the desired system connections.

There are also grants or promotional loans for many digitisation projects. We check which programme suits your project as part of the free first check. You can find all details on costs in our price overview.

What about data protection and retention obligations?

When you automatically extract documents, you often process personal data or business-critical information. Before we start, we contractually define which data is processed, where, by whom and for how long.

If we process personal data on your behalf, we first conclude a Data Processing Agreement (AVV) according to Art. 28 of the General Data Protection Regulation (DSGVO). We process personal data of customers in the EU in data centres within the EU. We record the exact location in the AVV. If you require it, we operate the system with a provider in Germany or on your own servers.

Important: We do not train AI models for other customers with your data. With external providers, we choose terms without training on customer data. In addition, you must observe the legal requirements for invoices and receipts. The extraction does not change the mandatory information or the retention periods. The retention obligations under § 147 AO (German Fiscal Code) continue to apply: the software only extracts the data for the workflow and does not replace proper archiving. Clarify with your tax adviser how originals and scans are kept.

What is the easiest way to start?

The easiest first step is a free test. Send us three sample documents, redacted if you prefer. For a later pilot project start, we then need ten to twenty typical and difficult examples. These should ideally be anonymised for the initial review. We also need a list of the required fields.

We review the documents and discuss your workflow and the desired target system in a 30 to 60-minute video call. You then receive an outline with the approach, feasibility, limitations and a fixed price for the pilot. This step is completely non-binding for you. Simply arrange a free initial check.

Sources

• GDPR (DSGVO): Art. 28 (Data Processing)
• Section 147 AO, Regulations for retention

Written with AI assistance, checked against the information on our pages and approved by DDC’s editorial review. Not legal advice for individual cases.