Putting AI to work in mid-sized companies
We work with your staff to find the workflow where AI pays off, shape it with them around an early prototype and build it so your team can take it from there.
In many companies, staff copy information by hand from one system into the next, gather it from many screens and read long documents line by line. AI can change that. Still, many wait, because questions about data protection, policies and the right tool are open, and because they remember what AI could do a year ago.
We keep testing new tools and tell you which ones pay off for your workflows.
Four examples with mock data, drawn from work we know. Each one shows what the AI does and who decides.
An inquiry arrives by email, with a list of items many pages long attached. Today someone in inside sales reads it all, looks up the matching products and builds the quote line by line. Meanwhile the customer waits.
Three supplier quotes for the same request, each laid out differently, or two versions of a contract. Today someone puts them side by side and hunts for the differences.
Over the years a tool has grown: an Excel file with macros, an Access database, lists in SharePoint. Many people depend on it, only one person understands it, and every change is a risk.
For one task someone needs three values from the ERP and opens 25 screens to get them, every day.
Which workflow it is in your company, we find out in discovery. It may well be one that isn't listed here.
Examples with mock data
We shape the workflow with your project team in short cycles. Early on there is a working prototype that shows your staff what fits and what is missing. You can join at any stage.
You can check each of these in a project with us.
Business gets done between people, even when AI is part of the work.
In the applications we build, AI prepares decisions. Which ones it may make on its own under fixed rules is set in your authorization concept, once the trust is there. So we work on site with your staff.
Your staff test a working prototype early.
Every company works differently. Which use case pays off and how the workflow should look becomes clear once the people who do the work can try something. So discovery includes an early prototype built on your sample data, which we develop further with your project team in short cycles.
AI changes what people in your company do. We say so from day one.
Some work goes away, above all retyping from one system into another. Other work gets easier, and new work appears. We shape the change together with the people it affects.
Before we build, we agree on how you will measure success.
Before we build, we write down what should improve, how you will notice it and where you stand today. We report against that in every stage.
We build it so your team can take it from there.
The know-how stays with you, and there are people in your company who carry the topic forward. The application runs in your infrastructure; we take on support and further development if you want us to.
Founder and CEO
Roman spent 14 years in software development at a lighting manufacturer, where he built and led the digital unit, most recently as head of AI for automating quoting and order processing.
At ALUR he is responsible for clients, organization and systems.
Founder and CPO
Jan spent 16 years in product development, most recently as head of industrial design with a hand in marketing, portfolio and UX. He turns what people need into pragmatic solutions.
At ALUR he is responsible for brand, product and how we work.
We have been responsible for software, products, digitalization and AI inside companies. We know quotes, orders and ERP from daily work.
Roman Luig and Jan Zellerhoff lead ALUR. Specialists in development, AI, data protection and law work on your project, from our team and our broad network.
On the team
Who works on it depends on your project.
Builds the application and the interfaces to ERP, email and file storage.
Chooses the models, connects them and checks what they deliver.
Clarifies AI policy, data classes and contracts before the start.
Works with your key users and supports the start in day-to-day operations.
These commitments apply to every project, from the intro call to operation.
AI changes what people in your company do. We say so from day one and shape the change together with the people it affects. What gets evaluated is agreed before we start, with the works council where there is one. Names on a case are there for follow-up questions; nobody is compared with anyone else.
Before a single document goes through an AI, we agree with you and your IT team where your data is processed, which models run and who has access. At first the application only reads; write access comes only after your approval.
Before we start, we clarify which AI policy you need, how your data is classified and what your works council needs to know. Our specialists handle legal and data protection questions.
The application runs in your infrastructure. Whether we take on support and further development under a service level agreement or your IT takes over entirely, what that costs and what your IT receives is agreed before we build.
Plus typical cases and special cases as examples, two or three people from the department with time for workshops and someone from management who owns the project and decides. Your data doesn't need to be perfect for this. We bring in your IT for infrastructure and interfaces before we touch any data.
Tell us about one workflow that costs you time today. Afterwards we tell you whether discovery is worth it and where to start. If we're not the right fit, we'll tell you that too.