Propose a project.
Kodulabor accepts a limited number of projects each quarter. We look for problems that are specific, measurable, and worth studying — where the experiment itself advances what we know about applied AI.
If the project fits our research agenda, we run the experiment, measure everything, and publish the results. You get a working solution and a structured assessment. The field gets another data point.
How projects are selected
Not every inquiry becomes a project. We evaluate each proposal against our research criteria: Is the workflow measurable? Is the problem real and recurring? Will the results be instructive for others? Projects that meet these criteria are scoped tightly — typically days to weeks, not months. Some are paid engagements. Some are research collaborations where the published case study is the primary output.
What we look for
The common thread: the problem is real, the outcome is measurable, and the results are worth publishing.
How it starts
Describe the problem. We do a brief evaluation to understand the workflow and whether it meets our research criteria. If it does, we propose a scope, timeline, and assessment plan. If it doesn't, we'll say so — no cost, no pressure. We only take on work where the measurement will be worth publishing.