AI MVP development: from use case to a working proof of concept in a few weeks
An AI proof of concept answers the question no concept paper can: does this work with our data, in our process, for our users? We build it together with your employees — on site or remotely, hands-on, and in a short time frame.
AI proof of concept instead of a slide deck
Most AI initiatives do not fail because of technology. They fail because planning takes too long and trying starts too late. Our approach is proactive: we pick one concrete use case with you, bring the people to the table who run the process today, and build an AI prototype they can operate themselves.
The result is not a document but working software on real or realistically anonymized data. You see how the model behaves, where it shines and where it breaks — before you release a large budget.
AI pilot project together with your team
We do not disappear and deliver at the end. During the pilot we sit with your domain experts, test daily, collect feedback and adjust the prototype. That builds acceptance in the team, and the knowledge stays with you — not with us.
- Joint kick-off: sharpen the use case, define success criteria, review the data
- Short iterations with the employees who will use the result later
- Deliberately small scope: one task done right instead of ten done halfway
- Open questions on quality, cost and data protection get answered in the POC, not postponed
POC with AI agents, RAG or plain LLM integration
Depending on the use case we build the AI MVP as a simple LLM component inside your software, as a RAG system on top of your knowledge, or as a POC with AI agents that call tools and handle multi-step tasks. We choose the architecture so that a successful prototype is not thrown away but grown into a production system.
The outcome: a basis for decision
At the end of the AI pilot you have three things: a working prototype, measured results against the criteria defined up front, and an honest recommendation — continue, adjust or stop. A clear stop is a good outcome too if it prevents an expensive project.
Frequently asked questions about AI MVPs
How long does an AI proof of concept take?
We plan deliberately short: a few weeks, not months. The exact duration depends on the use case and your data and is agreed together in the intro call.
Do we need our own AI team for this?
No. We need the people who know the process today — domain experts, not data scientists. Technology, infrastructure and models are on us.
What happens to the prototype after the POC?
The code is yours. If the decision is “continue”, we grow the prototype into a production system — or your team takes over with our documentation.
Do you work on site with us?
Gladly. Especially in a POC, close collaboration with your team is the biggest success factor. We combine on-site days with remote work — whatever fits your team.
Which use case should we try first?
Tell us about your process — in the intro call we tell you whether a proof of concept is worth it and how we would approach it.