Building intelligence shaped by physics,
engineered for measurable action
Hoordad Energy is a French building-intelligence and climate-tech company developing operational intelligence for buildings and local energy assets.
We combine physics, software engineering, machine learning, edge systems, and measurement discipline to help buildings move from fragmented data to explainable,
bounded and verifiable action.
Buildings generate data.
They rarely learn from what happens next.
Modern buildings already contain meters, sensors, automation systems, energy assets, and increasingly rich streams of operational data.
Yet much of that information remains fragmented, reactive, or disconnected from measurable outcomes.
Hoordad was created to connect operational context, forecasting, bounded recommendations, operator oversight, and verification within one continuous workflow.
From astrophysics and scientific computing
to intelligent buildings
Hoordad was founded by Maryam H. Roodsari, a physicist and software and machine-learning engineer whose background spans astrophysics, scientific instrumentation, data engineering and operational software systems.
In astrophysics, complex environments cannot be understood through one signal alone. Reliable interpretation requires multiple observations, physical context, modelling, uncertainty and continuous validation.
Buildings present a related challenge. Their behaviour emerges from weather, occupancy, equipment, control logic, energy flows, comfort requirements and human decisions.
Treating those signals separately produces dashboards. Interpreting them together creates operational intelligence.
Every operational action should be understandable, bounded and measurable.
Intelligence becomes valuable
when it can prove its effect
Hoordad’s approach does not end with a forecast or recommendation.
A useful operational system must preserve the context behind a decision, respect technical and operational boundaries, involve the operator where required, and compare the expected outcome with the measured result.
Observe → Understand → Predict → Decide → Act → Prove
The objective is not autonomous control for its own sake.
It is a disciplined path from building data to accountable operational improvement.
One intelligence foundation.
Three product directions.
ORBIT
Operational Intelligence
Hoordad’s first commercial priority is connecting building data, operational context, forecasts, bounded decisions, and verified results.
PRISM
Active Surfaces
The industrial roadmap extending Hoordad intelligence toward photovoltaic glazing, responsive opacity, daylight, and thermal functions.
ATLAS
Portfolio Intelligence
The future multi-site layer designed to compare buildings, reuse validated strategies, and scale operational learning.
From architecture to field proof
Hoordad is currently developing the Orbit MVP, a controlled demonstrator and the framework
for its first pilot collaborations in France.
The immediate objective is to validate one clearly bounded operational use case using real
or representative building data, operator-reviewed recommendations and measurable evidence.
The company is working with specialised software, embedded-systems and industrial partners
to prepare the path from prototype to pilot and later deployment.
ORBIT MVP
Operational workflow, data integration and proof interface.
CONTROLLED DEMONSTRATOR
Sensors, edge connectivity, energy data and representative systems.
CONTROLLED DEMONSTRATOR
Sensors, edge connectivity, energy data and representative systems.
Turn one operational challenge into measurable evidence