SOLUTIONSFrom the data you already capture to a decision you can make.
Each solution starts from a real operations challenge on monitoring networks. You will see the problem, the data you already have, what the model and the agent do, and which decision improves. The demo runs on synthetic data; the application runs on your own operation.
Problem
A critical rotating asset degrades over weeks with no one noticing, until the failure stops the line.
Context
The sensor data is there, but no one reads it in time or turns it into a concrete action before the shutdown.
Data you already have
- Asset vibration, temperature, and current
- Failure and shutdown history
- Maintenance work orders
What it does
A model computes the probability of failure at 7, 14, and 30 days, and an agent acts on that prediction with no manual intervention.
Which decision it improves
When to raise the work order, from sensor data to action, on your own operation.
The demo uses synthetic data created exclusively to illustrate how the solution works.
CARBON FOOTPRINT MEASUREMENT Problem
Calculating the carbon footprint takes weeks of manual work and the result arrives too late to act on it.
Context
By the time the figure is ready, the window to act on it has passed, and redoing it every period costs the same all over again.
Data you already have
- Energy and fuel consumption
- Process and production data
- Emission factors by source
What it does
A model projects emissions by scope and by process, and an agent builds the report, documents each factor, and warns when the target drifts.
Which decision it improves
Where to cut emissions and in what order, with a traceable figure computed on your own operation.
The demo uses synthetic data created exclusively to illustrate how the solution works.
ENERGY CONSUMPTION OPTIMIZATION Problem
An asset's consumption drifts from expected for weeks and the margin slips away without anyone noticing in time.
Context
The bill arrives once the overconsumption has already happened, without saying which asset caused it or how much was recoverable.
Data you already have
- Consumption curves per asset or line
- Process and load conditions
- Tariffs and time-of-use windows
What it does
A model projects the expected consumption curve and an agent isolates the asset behind it, quantifies the recoverable margin, and schedules the load toward the favorable window.
Which decision it improves
Which asset to service and when to run it, from consumption data to savings action.
The demo uses synthetic data created exclusively to illustrate how the solution works.
ENVIRONMENTAL IMPACT MEASUREMENT Problem
A fixed source's emission limit is crossed with no warning and the compliance record is built by hand when it is already too late.
Context
Continuous monitoring produces data all the time, but the deviation is detected after the fact, not before.
Data you already have
- Continuous monitoring of the fixed source
- Process conditions
- Applicable limits and regulation
What it does
A model projects the trajectory of each regulated variable at 8 and 24 hours, and an agent checks the limit, warns with margin, and documents the traceability of each figure.
Which decision it improves
When to adjust the process to stay under the limit, from continuous monitoring to the compliance record.
The demo uses synthetic data created exclusively to illustrate how the solution works.