Solutions
See more than the machine log.
A controller knows the setpoint, not the outcome. We add the sensing that shows what really happens, record it at the machine and, with models our engineers train on your data, turn it into results your team can use.
Four building blocks
Choose where to start.
Multimodal sensing
Which modality sees which fault, and why several sensors find more.
Learn moreMeasurement & monitoring systems
Inline inspection of every part and condition monitoring of machines and vehicles.
Learn moreEdge AI & signal processing
Why evaluation belongs at the machine, and what we deploy there.
Learn moreData logging & insights
Traceable recordings as the basis for models you own.
Learn moreDo we have to modify the machine?
No. The hub and its nodes mount on the column, frame or housing. The controller, the program and the safety circuit stay untouched.
Where does our data go?
It stays on your site. A deployed model runs on the edge device next to the process; only the distilled result is written to your systems. Raw recordings from a feasibility study are yours, handed over on your storage. Nothing requires a cloud account.
Is the AI in the control loop?
No, and it will not be. Our models grade parts and report conditions. They never sit in a real-time control loop, an interlock or a safety function. Process changes remain decisions your people or your controller make.
We build small batches. Is there enough data?
Often yes. In e-LAS+ the inline inspection was built to work with small batch sizes, and the feasibility measurement is designed to answer exactly this: how many parts, how many defects, and whether the signal separates them. If it does not, we say so.
We have no recordings of failures. Can you still train a model?
Yes. Anomaly detection learns what normal looks like from healthy recordings and flags anything that departs from it. Fault labels come later, as faults occur or from a test rig, and the model moves up to fault detection and classification when the data supports it.
Who owns the data, the labels and the model?
You do. Training runs on our premises or yours, never in a third-party cloud. You receive the model, its feature pipeline, the evaluation report and the labelled dataset.
Which systems do you integrate with?
The result is a record keyed to the part, module or asset. It appears on the operator dashboard at the machine and, on request, can be passed to your MES and to digital product and battery passports (being developed in DIGIBATT360). Grafana, OpenSearch and Kafka integration on request.
Next step
Not sure which approach fits?
Describe what you measure today and the decision you need. We suggest the sensors and the first step.