Our approach
AI in logistics starts with a useful tool for a real task.
We build AI to assist operational teams, with oversight, clear responsibility and an understanding of everyday work.
AI that assists your team.
Operational logistics is critical everyday infrastructure. Introducing AI requires careful attention to documents, data, exceptions, responsibility and the people doing the work.
vimoki develops systems that reduce the workload for teams and keep them in control. Decisions remain traceable, with human oversight built in.
Our approach starts with actual transport communication: what information is missing, who needs it, where is it stored and how can it support a reliable decision? This is where clarification work arises.
Technology works best when it fits the work itself. We build AI around its users so that taking the next practical step in daily operations becomes easier.
We are all still learning what this technology can do. vimoki starts with controlled experiments that are small enough to learn from and concrete enough to produce something useful.
Human oversight remains part of the process.
Start with a controlled pilot and check the results.
Clarify data protection, governance and responsibility early.
Integrate with existing systems.
Test in everyday operations.
Management
AI is a management issue because clarification work takes up real capacity.
vimoki builds technology for operational processes. We focus on how information is prepared, how decisions are made and what this means for quality, speed and responsibility.
Management needs to understand where work is done today, which risks must be controlled and how much change the organisation can support when introducing AI.
Alexander Krieg and Boris Gloger bring experience in logistics, software development and decades of work with management teams. We build technology that fits daily operations and makes practical change possible.
For management, this means starting small enough to learn under controlled conditions, while committing enough effort to achieve a practical change.
Our principle
Try it, build it, then scale under controlled conditions.
This gives companies a practical way to build AI capability in logistics and supply chains.