A prototype before a budget
A proof of concept answers one question: does this work on our data, for our people? We keep it small, with one use case and a few weeks of work. If it works, we roll it out. If it does not, you have spent little and know why.
When AI implementation fits
WHEN IT FITS
It fits when you have a use case in mind, or a pilot that never reached production. It also fits when a tool was bought but is hardly used. If you do not yet know where AI adds value, start with a strategy session or our workshop.
Prototype and proof of concept
A working version on real data, built to be tested by the people who will use it. We agree beforehand what it has to prove.
Integration with your stack
We connect the solution to your data and tools, so it does not become a separate screen nobody opens. That includes access rights, logging and a fallback when a model is unavailable.
Custom AI development
Where a standard tool does not cover the workflow, we build it: applications on top of language models, with your knowledge, tone and business rules.
Flatline is the first Dutch Claude partner. We choose the model per task and keep the setup so that you can switch later.
Adoption
A system only pays off when people use it. We train the team on their own tasks, appoint an owner and agree how feedback leads to changes.
How an implementation runs
Scope. One use case, the data it needs and the result that counts as success.
Prototype. A working version in weeks, tested with the people who will use it.
Rollout. Integration, access rights, monitoring and training.
Maintenance. Models and tools change. We keep the solution up to date and adjust it with your team.
AI in practice
Have a use case in mind?
Tell us what you want to achieve and what has been tried so far. We reply with a proposal for a first prototype.
