AI in industry
Practical guidance for applying AI and data to production, operations and organisational decisions, with the limits stated and the evidence shown.
Explore the programme →Three connected fields of work
Artificial intelligence is our main field. Energy is where we apply the same standard of evidence to a sector changing faster than its guidance can keep up. The middle programme is where the two meet, and where independent work is scarcest.
AI for energy
How forecasting, anomaly detection and optimisation can improve energy systems, and where those claims tend to outrun the evidence.
Explore the programme →Energy and renewables
Independent methods for energy efficiency, photovoltaics and storage, grounded in Bulgarian operating conditions rather than sales assumptions.
Explore the programme →How the three fit together
The programmes are not three separate audiences. They are one argument, applied at three distances from the machinery.
AI in industry asks whether a given use case is worth attempting at all, and what has to be true before it is. Most published material skips this question, because the organisations publishing it are selling the answer.
AI for energy takes those methods into a domain with unusually good data and unusually poor use of it. Meters produce time series continuously; comparatively little of it reaches a decision. Forecasting, anomaly detection and optimisation are the obvious applications, and the obvious places to be over-sold.
Energy and renewables is the foundation underneath both. A payback figure that assumes the wrong irradiation, degradation or self-consumption rate produces a confident number and a bad decision, with or without a model attached.
What is the same across all three: we publish the method alongside the conclusion, we state what our figures assume, and we say plainly when the evidence does not support acting yet. Nothing on this site is for sale.