Cutting the energy bill on what you already run
Sector Small manufacturer with energy-intensive plant.
The situation
Heating, cooling and compressed air ran on fixed settings regardless of conditions. Energy was one of the largest controllable costs and nobody was actively managing it.
What CAPIO did
We used the data the plant already collected, temperatures, loads, run times, to model how the systems behaved, then tuned the settings to hold output while using less energy. No new hardware, just machine learning applied to existing sensor data, with changes reviewed before they went live.
The outcome
- Energy cost on the targeted systems down by close to a fifth *representative*
- Output and comfort unchanged, so no trade-off for the saving *representative*
- A repeatable method the team can point at the next system *representative*
We were sitting on the data to do this for years. We just were not using it.
- Turning AI activity into a governed programme
- Compliance and competence as the growth engine
- Seeing the whole field, not five percent of it
- An expert made available at scale
- The support desk that answers itself
- An expert on tap for a small firm
- Fluency across a whole small company
- Catching fraud before it lands
- Contracts read in seconds
- More jobs per van, fewer miles
- A small dev team that ships like a bigger one
- Keeping subscribers who were quietly leaving
- Lifting the whole field, not just the top performers
- Buying at the right moment, not out of habit
Case studies are anonymised. Representative outcomes are benchmarked to independent research and illustrate typical results rather than a specific client figure.