Data & predictive ML
Flags the failure before it stops the operation.
Failure, demand and risk, predicted on the operational history you already hold.
21 cases across 7 sectors
What it solves
Useful prediction nearly always looks the same: there is an operational history, there is an expensive event — a stoppage, a demand spike, a delay — and there is a window in which acting still helps. The model is usually the easy part. What decides whether it works is whether the operational data is where it says it is, and whether anyone can act on the warning when it arrives.
Where it applies
Defence
- On-premise
- Classified environment
- No route out
- Predictive maintenance of fleets and platforms
- Sensor data fusion
- Open-source intelligence analysis
Logistics
- Real time
- WMS · TMS
- Demand forecasting
- Route and last-mile optimisation
- Arrival-time prediction
Transport
- Traceability
- Real time
- Onboard edge
- Failure prediction from fleet data
- Demand and delay prediction
- Fleet optimisation
Health & pharma
- Sensitive data
- Validation
- Traceability
- Clinical risk prediction
- Clinical trial optimisation
- AI-assisted pharmacovigilance
Energy
- Critical infrastructure
- Distributed assets
- Generation and demand forecasting
- Failure prediction across distributed assets
- Price prediction and trading
Manufacturing
- Nothing stops
- Lives with what is there
- Equipment failure prediction
- Planning optimisation
- Advanced statistical quality control
Civil & construction
- Mountains of documentation
- Assets that last decades
- Schedule and cost prediction
- Structural monitoring
- Predictive asset and infrastructure management
Talk to us
Do you have a data & predictive ml case?
Half an hour. You leave with the problem framed and an honest answer on whether AI is the way to solve it.
Talk to us