Q&A

01 What exactly is the S³AI Energy Center?

S³AI is an intelligent plug-and-play Energy Center that offers a more efficient, flexible, and sustainable alternative to conventional
heating and cooling systems.

Through AI-driven integration, energy synergies between the two systems are activated, allowing energy to be recycled and upcycled
multiple times.

The effect: 50% less energy consumption – without any intervention in the building structure and for just €100/m² GFA.

We transform your building from a pure energy consumer into an active energy collector, energy storage system and AI energy
orchestrator.

We use the energy already inside your building.

02 How can you cut energy use by 50% without a
full renovation? Combined effect S³AI = f (WR₄₅ , KU₃₅ , AI₂₅) ≈ 50_%

1. WR₄₅ – Heat Recycling 45%

We use existing energy sources within the building – solar energy, including the south-to-north shift, occupants, IT equipment and other internal heat sources.

2. KU₃₅ – Cooling Upcycling 35%

In summer, excess heat is converted into valuable cooling energy, instead of being released unused into the environment.

3. AI – Intelligent Integration 25%.

Conventional if-then programming is not flexible or intelligent enough to manage the complexity of a building energy system. AI connects the systems,
recognizes dynamic relationships and controls energy flows predictively.

The combined effect: 50% less energy consumption.

03 Why do we use AI?

Standalone systems such as district heating substations, heat pumps, gas boilers and chillers can be reliably controlled using fixed
rules.

However, when these systems are interconnected to reduce energy consumption by up to 50% through energy circulation, the
number of interactions increases exponentially. Conventional if-then rules become too complex, error-prone and difficult to
manage.

We use AI because our S³ Energy Centers intelligently couple different energy generators – and this requires intelligent, predictive
coordination of the energy flows. A game changer for decarbonizing the existing building stock.

04 What roles do machine learning and mathematical
optimization play at S³AI?

At S³AI, machine learning and mathematical optimization have clearly defined, separate roles.

Machine learning predicts: How will the building behave? How will heating or cooling demand develop? What are the expected heat recycling and cooling upcycling yields?

Which storage charge levels are optimal at what point in time? How will the systems respond?

Mathematical optimization decides: Which systems should operate, when and how, in order to achieve the defined objective as efficiently as possible?

Simply put: AI predicts. Mathematics decides.

05 Does the operator retain control?

Yes. The operator or facility manager always retains control of the system. Operational requirements, comfort requirements,
technical limits and planned maintenance are taken into account as constraints in the optimization.