IoT / Fleet
Fleet intelligence from raw telemetry
A fleet operator wanted to see how its vehicles were used across a large IoT network. We turned raw telemetry into usage maps and built them into the operations system the team already worked in.
Intelligent Solutions
Putting models into the tools and processes people already use.
We take models out of notebooks and into daily operations: pricing tools, planning systems, advisory software. We aim for a working first version in production early and improve it from there.
The problem
Many AI projects end with a good prototype that never reaches production, because nobody planned how it would fit into existing systems and routines.
How we work
- Deeper Business Understanding
Sit with the people who make the decisions and learn how they work today.
- Integration from the Start
Plan the integration into existing systems at the start of the project.
- Operationalize Before Optimizing
Ship a simple version to production first, then improve it based on real use.
- Operating Model Support
Agree who owns and maintains the solution after handover.
What you get
- AI embedded in your workflow
Model outputs shown inside the tools your team uses to make decisions.
- Continuous improvement loop
User feedback and new data flow back into the model.
- Handover with clear ownership
Documentation, training and a named owner on your side.
Projects
Retail
Automated pricing recommendations
A retailer's pricing team worked from spreadsheets. We added machine-learning price recommendations to their workflow, automated most of the manual review, and fed each pricing decision back into the model.
Write to Fredrik directly.
Fredrik Moeschlin CEO & Founder