Capability

AI, Digital Twins & Physical Intelligence

Physical sensor data, SCADA, modelling and machine learning connected to Digital Twin and decision-support workflows.

What we do

Oliveris applies AI where it is grounded in a real physical system. We define what must be measured, acquire and synchronise sensor data, reconstruct system state, combine measurements with engineering or physics-based models, and integrate machine-learning methods where they add value. This physical-intelligence layer supports Digital Twins, process monitoring, anomaly detection, chemical-state recognition, predictive operation and engineering decision support without separating the AI from the system it must understand.

Technical competencies

How we work in this area

Time-aligned data acquisition
Signal processing and sensor fusion
System identification
Digital Twin interfaces
State estimation
Machine-learning integration
Predictive analytics
Process optimisation
Uncertainty-aware decision support
PLC/SCADA and supervisory data integration
Industrial data interoperability

What it enables

Improved process visibility
Earlier fault and degradation detection
Model calibration from real measurements
Predictive operation
Data-driven optimisation
More defensible engineering decisions

Collaboration model

How we collaborate

Our role is typically the connection between physical equipment and the digital model: defining what must be measured, building the data path, maintaining signal quality and integrating the resulting information into analytics, Digital Twin and control workflows.

Projects