Does the feed amount match the price?
Gas is produced with a delay. Whoever wants to run by price must plan ahead.
Concern 2 · feeding
What to feed, and when?
The feeding AI puts the electricity prices and the feeding recommendation side by side: which substrate in which amount, and when the plant should run.
Sound familiar?
Three questions from daily plant operation.
What did I actually feed?
The history of feed amounts often only sits in the control system.
What is recommended tomorrow?
A recommendation needs prices, stocks and the plant's limits.
How the learning system answers
Recommendation and history in one place.
The heat maps show measured daily amounts and the plan in one view, plus the prices the recommendation is based on.
How does the feed amount of the next days change with the new prices?
The system recommends feeding somewhat more on the expensive days and reducing the amount on the cheap ones. The price source is named.
Source: price forecast (15-minute prices), feed history from the control system
Example with invented data
Questions you can ask
- What did I feed last week?
- Which substrate pays off at this price?
- When should the plant run?
- Where does the price the recommendation is based on come from?
Every number comes from a fixed calculation, not from the language model. Every answer names its source.
What goes into the digester
The measured daily amounts and the plan are in one view.
What it looks like
Prices and recommendation side by side.
Prices on top, below the recommendation per substrate and day. Colour shows the deviation from today.
Feeding plan ahead of the price peak00:00
Price now–
Feed today–
Engine–
Example with invented values
From the silo to the recommendation
Prices, stocks and the plant's limits belong together.
How it works
From the price to the recommendation.
01
Fetch prices
The current price forecast is read in 15-minute steps, never averaged to hours.
02
Calculate the plan
A fixed calculation computes substrate amounts and plant output within the plant's limits.
03
Check and decide
You see plan and history side by side. The decision stays with you.
Learning system and Pseudomizer
Two building blocks, one goal: answers without handing out originals.
The learning system (RAG)
A system of your own with its own storage. It reads your documents and measurement data, answers in plain sentences and names the source. At night it asks itself new questions and reports gaps.
More on the local AIThe Pseudomizer
If you also want to use a large cloud AI, the Pseudomizer creates a shadow copy and checks it with subject-specific check chains. The original stays with you. Leak rate at the exit: 0.00 %. Guards detect, the judge stage blocks when in doubt, healing cleans up.
To the PseudomizerMore concerns
What operators also want to know.
Who uses how much electricity?
The plant's own consumption split across consumers, even when not everything is measured.
To the pageWhen should the CHP run?
Electricity price outlook as a heat map, to plan operation against the price.
To the pageMay this go to the cloud?
Original versus mirror: use cloud AI without originals leaving the house.
To the pageWhere does the heat go?
Heat network at a glance: flow, return, output, storage. One click opens the chart.
To the pageBring us your biggest annoyance.
One conversation, one real task from your daily work. We use it to show what AI and automation can do for you.