Use case · AI Studio
Energy management
Spot load peaks, understand consumption, control costs — before they show up on the bill.
01 · The brief
Managing energy before the cost is incurred.
Energy costs are not driven by volume alone, but by the interplay of load profile, market price, contract structure and risk. A single load peak — the highest quarter-hour value of the year — can determine a substantial share of the annual demand charges.
In a manufacturing business, hundreds of metering and data points deliver readings around the clock. Without intelligent analysis, the causes, the patterns and the possible countermeasures stay invisible.
The brief: make the connections visible before they appear as costs on the invoice — an agent team that captures data points, analyses them, recognises patterns, names the reasons and proposes concrete improvements.
02 · How it works
From data to recommendation.
Set up within days and connected to the existing data — after a short time the client’s own team was using the agents independently.
Step 01
Read
Metering and data points, meter readings, plant equipment and the production plan are read in continuously.
Step 02
Recognise
Load peaks, patterns and anomalies — linked to weather, public holidays and production planning.
Step 03
Recommend
The reasons are named and concrete measures proposed — technical as well as organisational.
Step 04
Monitor
Proactive reports and ad-hoc analyses on request — continuous rather than one-off.
03 · The outcome
What the agent team found.
Over a period of almost two years, all data points were analysed live and the billing-relevant annual peak determined precisely.
Several installations turned out to be the drivers — above all during the morning start-up. Crucially: the most expensive peaks occurred in a few short windows that can be capped deliberately.
- Staggered start-up and load spreading — feasible without investment.
- Cascade control for compressed air — modest investment, payback within a manageable period.
- A solid data basis for priorities, thresholds and future investment decisions.
04 · Scaling up
From own consumption to energy decisions.
Step 01
Stage 1 · Own consumption
Cap peaks, spread start-up loads, keep grid charges in view — an immediate reduction in operating costs.
Step 02
Stage 2 · Technology
A data basis for load management and investments such as frequency converters or storage — grounded in evidence rather than gut feeling.
Step 03
Stage 3 · Contracts & market
Shift flexible loads into favourable time windows and align contracts with the real demand structure.
Step 04
The decision stays with you
The agent team analyses, simulates and prioritises. Contract decisions, investments and procurement remain with management, purchasing and finance.
Does this sound familiar?
In a first conversation we look at your processes together and sketch out where an agent team would make the biggest difference. Free of charge and without obligation.