Foobot
Built for pragmatic building teams
Like our clients, we take a pragmatic approach. As an innovative and profitable European SME, we stand apart from startups that promise free services before raising prices... or disappearing. Our strength: combining field expertise with a culture of innovation to make your buildings reliable and generate lasting savings.
Our approach
We help you regain operational control of your facilities.
The older a system gets, the more excuses we make for it. Yet, when it comes to HVAC, performance loss rarely comes from hardware wear and tear.
The real culprit is its management.
We often talk about “energy drift”. It's the phenomenon where a new or recently renovated building consumes X MWh/year, and then the bill increases year after year.
Why does this happen? Very often, management is “reactive”.
Over time, the initial design vision disappears in favor of operational quick fixes:
- The VIP complaint: Someone is cold in a specific area? The heating is forced on. The isolated problem is solved, but the building overconsumes for the remaining 360 days of the year.
- The degraded mode: A piece of equipment fails or a controller crashes? Continuous operation is temporarily forced to compensate for the breakdown… and the temporary becomes permanent.
Faced with an emergency, there is a lack of time or tools to analyze the root cause.
We end up losing track of the modifications and, consequently, of the energy consumption.
It is easy to point fingers at facility operators, but how can we expect good management from non-specialist players, primarily selected for their low cost?
The other element often blamed is the BMS (Building Management System), which is poorly mastered, failing, or quite simply… was never configured to keep historical data for analysis.
Yet, this situation is not inevitable. We are here to help you take back the controls.
Carbon footprint
What if AI were part of the solution?
AI is often accused of increasing our carbon debt. This may be true for LLMs, but not for all types of AI. We measured our models' carbon footprint, our ratio: 1/700
AI training
+1 tCO2e
Client buildings
-700 tCO2e/year
Figures based on cumulative annual performance: 1 year of training and 1 year of operation.
Values
What guides our work
Pragmatic integration
We work with existing BMS, documentation gaps, and real-world constraints.
Data analysis
Setting up data historization in controllers, consumption baselines, savings verification.
Comfort first
Comfort constraints are hard-coded into every optimization.
Next step
Let's discuss your real estate portfolio
Share your real estate or BMS context, we'll help you regain control