Energia AI · Company
About Energia AI
Energia AI is an AI control platform for commercial HVAC. We focus on how a building responds to weather, occupancy and control changes, so that control decisions can be evaluated against its actual operating needs.
Our starting point is an existing commercial building with central controls and a specific concern: equipment running beyond occupancy, recurring manual adjustments or energy use the team cannot explain. The aim is lower operating costs within the requirements the building team approves.
Founder
Edoardo Orfanini, founder.
Building response before equipment control
Our approach combines building models, learning from operating data and simulation to prepare control strategies. Available plans, equipment information and trend history help define the model and the scope of the evaluation.
A simulation is preparation, not a customer result. Savings in a particular building must be established through a suitable field comparison. We assess energy costs alongside occupied comfort rather than presenting a modeled percentage as a performance promise.
Your facilities team remains part of the decision
We assess fit with your engineer and existing controls provider. That includes the available data, equipment, access permissions and permitted changes. A protocol name such as BACnet or Modbus does not establish compatibility on its own.
Before equipment control begins, the pilot process calls for agreement on operating boundaries and verification of manual override and fallback for the actual installation. These are site requirements, not a claim that every building is ready to connect.
How to evaluate our work
We distinguish the platform’s intended approach, the requirements of a proposed pilot and evidence of an actual result. Research by other organizations helps explain the opportunity for better building operation. It does not establish Energia AI performance.
Read our commercial HVAC optimization guide for the underlying concepts, or use the pilot decision guide to define what an evaluation must prove.