From idea to working proof, in a few weeks.
An AI pilot is the low-threshold way to test an idea without investing big straight away. We build a bounded proof of concept on your own data, measure whether it works and make a clear go/no-go decision together.
What is an AI pilot?
An AI pilot (or proof of concept) is a short, bounded test in which you turn an AI idea into a working version and try it out on your own data. The goal is to establish within a few weeks, with measurable criteria, whether the idea works and delivers value, before you decide to invest big.
- From idea to proof in a few weeks
- Works on your own data and context
- Measurable criteria agreed in advance
- Ends with a clear go/no-go decision
Why start with a pilot?
AI ideas often sound promising in a meeting room, but the real question is whether they work on your data, in your process, with your people. Making a big investment without that proof is gambling. A pilot turns that gamble into a well-founded choice.
The risk of AI projects is that they start big and abstract, cost a lot of money and only deliver something after months. We turn that around: small, concrete and fast. Within a few weeks you have a working version in hand that you can genuinely try out.
That takes discipline in scope. We deliberately choose one bounded use case and agree in advance what success means. That way we prevent a pilot from ballooning into an endless experiment with no decision.
As forward deployed engineers we don't build a pretty demo and leave. We work on your real data, measure what it delivers and stay involved until you can make a well-founded decision: continue, adjust or stop.
What you get from us
Bounded pilot
One sharply chosen use case, developed into a working version on your own data. Small enough to build quickly, big enough to prove something.
Measurable criteria
Together we define in advance when the pilot is a success. So you judge the result on facts, not gut feeling.
Go/no-go decision
A clear, well-founded recommendation based on the results: continue, adjust or stop. Including what we learned along the way.
Scaling advice
On a go, we outline what is needed to deploy the solution more broadly and structurally, so the step to implementation becomes small.
How do we approach it?
From sharpening the use case to a well-founded go/no-go decision.
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Sharpen the use case
3-5 working daysTogether we choose one bounded question with enough impact to be worthwhile and enough focus to build quickly. We define up front what success means.
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Build
2-4 weeksWe build a working version: not a pretty demo, but a solution you can genuinely try out on your own data and in your own context.
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Test & measure
1-2 weeksA small group of users starts working with it. We measure the criteria agreed in advance and gather feedback from real use.
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Go/no-go & scaling advice
a few daysBased on the results we make a well-founded decision together: continue, adjust or stop. On a go, you get concrete advice for scaling up.
What can you test with a pilot?
For knowledge & documentation
A smart search assistant
Test whether an AI assistant that pulls answers from your own documents genuinely saves time. Working in a few weeks on a bounded set of documents, so you see if it holds up before you roll out broadly.
For customer contact
Faster handling of queries
Test whether AI can help your team draft answers to common customer questions. We measure quality and time savings on real cases before you make it part of the process.
For operations
Automating a manual process
Take one recurring, time-consuming task and prove whether AI can reliably take it over. A pilot shows whether the business case holds without you investing big straight away.
Does the pilot work? Then we take the step to AI implementation and, when the solution is embraced broadly, to scaling AI across the rest of the organisation.
No sharp use case for a pilot yet?
The AI Readiness Scan helps you determine where in your organisation the most value can be found. A good starting point for choosing the right pilot.
Take the AI Readiness Scan
Frequently asked questions about the AI pilot
How long does an AI pilot take?
Most pilots run from idea to go/no-go in about four to eight weeks. That depends on the complexity of the use case and the availability of data. We deliberately keep the scope small, so you quickly have real proof in hand instead of a long-running project with no interim result.
What do we need to provide for a pilot?
Three things: a clear use case, access to the relevant data or documents, and a few people willing to try out the solution and give feedback. We take care of the building and the technical side. So you don't need in-house AI expertise to start.
What happens after the pilot?
On a go, we translate the pilot into a scaling plan: what is needed to deploy the solution more broadly and structurally. We handle that through AI implementation and, when you are ready for the next phase, scaling AI. On a no-go, you know with evidence why something doesn't work, which is just as valuable as avoiding an expensive misstep.
Doesn't a pilot just stay a nice demo?
No, and that is exactly the point. We agree measurable criteria in advance and test on your own data in your own context. So at the end you don't know whether something looks nice, but whether it genuinely works and delivers value. A pilot is an investment in certainty before you go big.
An idea you want to test without big risk?
Book a no-obligation call. In 30 minutes we determine together whether your idea lends itself to a pilot and what a logical first step is.