Many companies want to use AI and do not know where it really pays off. This guide shows typical use cases, real project examples and the path from potential analysis to pilot. The principle throughout: AI prepares, your staff decide. Delivery through our process automation and AI service.
AI pays off where many similar cases with unstructured content arrive: documents, emails, receipts, free text. If you recognise yourself in one of these fields, that is the process we start with in the potential analysis.
Sound familiar?Letters, emails and attachments are reviewed by hand, assigned to a case and filed. What matters is decided by whoever has time.
Sound familiar?Invoices are printed, checked, coded, signed off and then entered in the accounting software. Discount deadlines pass unnoticed.
Sound familiar?Requests arrive by email, phone and portal. Standard cases tie up as much capacity as complex ones because the answer is gathered from several systems.
Sound familiar?Annual settlements, monthly reports or statements are compiled by hand from receipts, contracts and spreadsheets, every time from scratch.
Sound familiar?Anyone looking for a template, a contract clause or an earlier decision asks around or clicks through drives and mailboxes.
Sound familiar?Quotes, meeting minutes, findings and reports are produced from templates, notes and dictation, with a lot of typing and copying.
Sound familiar?Completeness checks, comparisons with the previous year and the four-eyes principle happen on a sample basis because there is no time for more.
Anonymised examples from our work, each with starting point, solution and outcome. All examples in full, with approach and technologies used, are on the project examples page.
We do not start with a tool, we start with your processes. One process as a pilot, then expansion following the same pattern.
We review your processes together with the people who run them: effort, volume, data situation and the systems involved. The result is a list of the places where AI pays off and the places where a rule or a form is enough.
One process, one department, live operation with real cases. Approval points are defined, every action is logged, feedback flows straight back in. We tell you the effort after the potential analysis.
The pilot is connected to your business systems: Microsoft 365, ERP, DMS, accounting or CRM. Rules and model are updated from the corrections your staff make, results are reviewed regularly.
Further processes, document types and sites following the same pattern, with the lessons from the pilot and key figures from live operation.
Before every deployment we clarify which data is processed, where it resides, who may access it and which legal basis applies. Data processing agreements are in place before any service sees data. Without that clarification we do not start.
AI steps recognise, check and prepare. Anything that goes out or changes data is approved by a person. Every action is logged, every correction feeds back into the rules.
We work with what is already in place in your environment and add only what is missing. In the Microsoft world that is Microsoft 365 with Copilot, Power Automate, Power Apps and SharePoint, plus Microsoft Azure for services that should run in your own tenant. On top of that come AI document and receipt recognition, our own AI agents with clearly limited rights and logging, interfaces to ERP, DMS, DATEV and CRM, and custom software from our own development where standard building blocks are not enough. Which models and services fit in a given case is decided by data protection, the data situation and your process, not by the vendor.
With the process that ties up the most time today and has many similar cases, such as incoming mail, incoming invoices or standard requests. In the potential analysis we review your processes with the people who run them and define the first pilot. Whatever can be described as a rule becomes a rule; AI is added where rules are not enough.
You usually do not need your own model. Recognition of documents, receipts and requests runs on existing models that we tune to your cases through rules, examples from your business and the corrections your staff make. What you do need is a clarified data situation: where the documents are, who may see them, which systems are involved.
That depends on the process, the systems involved and the interfaces. That is why we do not quote a flat price but proceed like this: the potential analysis defines the scope of the first process, and from that we produce a quote with a fixed scope for the pilot. After the pilot you decide whether and how to continue.
Before every deployment we clarify which data is processed, where it resides, who may access it and which legal basis applies. Where possible, services run in your own Microsoft environment; data processing agreements are put in place. AI only sees what the respective user is allowed to see, so we check permissions before the start.
In our projects AI takes over the preparation: recognising, assigning, checking, drafting. The professional decision, the approval and the contact with the outside world stay with your staff. In practice, work shifts from routine to exceptions and complex cases.
That depends on complexity and interfaces, so we do not promise a duration. We deliberately keep the first process manageable so that the pilot runs in live operation early, and we give you the time frame after the potential analysis.
No. Microsoft 365 is often the simplest basis because Copilot, Power Automate and SharePoint are already licensed. We also deliver AI document recognition, AI agents and interfaces with other systems, for example with your property management or accounting software and our own custom software.
The potential analysis starts with a conversation about the processes that tie up the most time today.
