We analyse your workflows together with your teams and assess where AI pays off and where it does not. The result is an implementation plan with effort and cost. On request, we implement it ourselves.
Many companies know that AI is relevant to them. What is usually open is where exactly it helps in their own operations, what adoption costs and in which order to proceed. AI consulting answers these questions for your company and turns them into an AI strategy you can actually implement.
We advise SMEs, mid-sized companies, public bodies and non-profit organisations in Austria. Our principle: we start with the process, not the model. Only once it is clear how the work really runs do we decide where AI is used in the company. And because we build the solutions ourselves, the advice does not stop at the slide.
We run expert interviews, spend time on site with the team and watch over their shoulder. That way we see your workflows as they happen day to day, not as they look on the org chart. It shows where time gets lost and which steps repeat.
Every possible use case is placed by effort and impact in an Impact Effort matrix. We also say no when AI is not the right tool.
The assessment becomes a plan: which use case comes first, what it means in effort and cost, and which prerequisites in data or systems are still missing.
You implement the plan internally or with us. We build automations and custom AI solutions ourselves, with specialists from our network where needed. That keeps responsibility with one partner from analysis to hand-over.
30 minutes, free of charge, in person with Simon Micheler. You describe your situation and goal; we tell you whether and how consulting makes sense.
Analysis together with the people who will later work with the solution. The result is the Impact Effort matrix with prioritised use cases.
We begin with the use case that has a noticeable effect. Small, visible wins build trust. The first pilot is tested by the team.
After a successful test we train users until the team carries on independently. Simon Micheler describes the three stages in his book "Digital Translator".
Most AI projects don't fail on the technology. They fail because no one read the process properly beforehand and no one supported adoption in the team afterwards. That is the most common mistake we see.
The second lies in the data. At a timber group, Microsoft's Copilot read a product table as running text rather than structured data, which led to wrong results. It only worked once the data had been moved into a clean structure and connected properly.
The third is processes that have grown over years. At a social-services organisation, an automation runs cleanly on the technical side but is not yet in live operation, because inconsistent formats and many intake channels have built up over time. Good consulting spots such hurdles before anything is built.
For over a year we have been supporting a large Austrian social-services organisation with AI adoption, as an ongoing process rather than a one-off project. Strategy, technology and enablement come from a single source.
View projectFor a Dutch HealthTech startup we rethought a recovery app for people with addiction: away from a WhatsApp chatbot with a high drop-off rate, towards a gamified learning path. The role was closer to a co-founder than a classic consultant.
View projectAt the core, Simon Micheler and Nikolay Krastev work on your project together. Simon leads strategy and analysis and brings over ten years of product work and team leadership. Nikolay studied Artificial Intelligence at JKU Linz and leads the technical delivery. He assesses early on what is feasible and how much effort it takes.
For specialist topics such as data science or change, we bring in profiles from a curated network. Whoever works on your project is named specifically in advance.
It clarifies where AI brings concrete value in your workflows. We analyse the processes with your teams, rate the possible use cases by effort and impact and draw up an implementation plan with effort and cost. On request, we implement it ourselves.
The process is not analysed properly beforehand, and adoption in the team is not supported afterwards. On top of that come data in the wrong form, such as tables a tool reads as running text, and processes grown over years with inconsistent formats.
An outside view sees workflows that are taken for granted internally. We bring the experience of 32 generative AI projects with agents. The goal is still that your team carries on by itself at the end and ownership stays in-house.
Yes. KI ALPIN is an AI consultancy based in Vienna and works for companies in Austria. We run workshops across the DACH region. The intro call takes place via Microsoft Teams.
Especially there, because time and budget are limited and a wrong move is expensive. We start with the use case with the highest ROI and say honestly when AI does not pay off for a workflow.
The intro call is free of charge and takes 30 minutes. We discuss scope, timeline and investment individually, based on your context. The implementation plan at the end of the consulting includes the effort and cost of implementation.