Technology
Industrial AI on your operational data
Industrial AI only works when the data underneath it does. We build both: the connected-data foundation from your assets and systems, and the models on top that predict, detect and support decisions — governed, and reviewed by a person before anything acts.
What it covers
AI on the data your operation produces
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Prediction & forecasting
Forecast cost, demand, wear or capacity from your own operational history.
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Anomaly & condition monitoring
Spot the readings that matter in sensor and time-series data.
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Decision support
Put the model’s output where a person can act on it — not in a dashboard nobody opens.
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Built on connected data
The IoT, integration and twin layer the AI depends on — engineered first.
Proof
Where it has run before
Case study Manufacturing · Digital Twin · AITelling the operator which dial to turn
How Toobler built a real-time physics digital twin and an AI recommender for a plastics extrusion line, advising the smallest dial change that clears a fault.
Case study Construction · AIEngineering Construction Cost Intelligence and AI Expense Forecasting
How Toobler engineered a construction cost-intelligence platform for Nael — structured cost management, CVR and machine-learning expense forecasting from macro-economic signals.
Case study IoT · Digital Twin · Real-timeThe software platform behind connected smart lighting
How Toobler built a multi-tenant cloud platform for connected lighting: real-time control and monitoring of thousands of LED fixtures and sensors.
Case study Construction · Digital Twin · IoTA Construction Progress Digital Twin, Integrated with BIM
How Toobler engineered a BIM-integrated construction progress digital twin for Nael — simulation, live monitoring and AI forecasting of cost, timeline and resources.
Sitting on operational data you don’t use?
We’ll assess the data you have and where AI would actually pay back.