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šŸŒ AI Has Entered the Building: The Future of Energy Management is Here

The Moment Everything Clicked: How BrainBox AI Gives Buildings Brains

When Sam Ramadori first met Jean-Simon Venne, he wasnā€™t looking for a career change. He was deep in private equity, investing in traditional industriesā€”manufacturing, industrial operations, and companies built on physical infrastructure, not software. He knew how hard it was to make even modest energy efficiency gains.

Shaving 3% off energy costs in a factory meant a team of 10, a multi-million-dollar budget, months of disruption, and a painful approval process. That was just the reality of dealing with physical industries notoriously slow to embrace anything that disrupts business as usual.

Then Venne laid out his vision for BrainBox AIā€”and Ramadori nearly fell off his chair.

Instead of installing expensive new hardware, ripping out legacy systems, or forcing complex retrofits, BrainBox AI would layer intelligence on top of what already existed. It would tap into a buildingā€™s control systems, optimize them in real time, predict problems before they happen, and slash energy wasteā€”all without turning a single screw.

The promise wasnā€™t a few percentage points in savings. It was 10, 20, and sometimes even 30% reductions in energy use and carbon emissions. It was possible because BrainBox AI offered customers an autonomous AI system that continuously digested data and continuously learned how to do its job better.

Sam knew what he had to do: explain to his wife why a guy with no technical background was leaving his financially secure future to run an artificial intelligence startup.

Buildings: The Sleeping Giant of Energy Waste

For years, the climate conversation about emissions has focused on cars, coal plants, and industry. But buildings are among the biggest culpritsā€”accounting for nearly 40% of global carbon emissions.

Half of that comes from heating and cooling.

HVAC systems are dumb, reactive, and wasteful. They donā€™t anticipate; they just respond, often working against the buildingā€™s needs and the energy grid.

A self-driving car anticipates obstacles, reroutes and adjusts in real time. HVAC systems? Theyā€™re stuck in the past, mindlessly burning through energy.

BrainBox AI changes that.

A thermostat, even a "smart" one, only knows whatā€™s happening now. BrainBox AI sees six hours into the futureā€”with 99% accuracy.

It factors in: 

āœ… Real-time weather data (Is the sun about to hit those west-facing windows?) 

āœ… Building occupancy shifts (Is an office floor emptying out for the day?)

āœ… Energy prices (Is electricity about to get more expensive?) 

āœ… Carbon intensity (Is the grid producing renewable energy or mostly fossil fuels?)

By adjusting proactively, BrainBox AI smooths operations, navigates around costly energy spikes, and reduces the overall carbon footprint.

Ramadori and Venne understandā€”and the industry is slow to realizeā€”that buildings are drowning in data, but nearly all of it is discarded.

Every thermostat reading, fan speed adjustment, and heating and cooling cycleā€”millions of data points go to waste daily.

In an era where data is the new oil, buildings might be the biggest wasters of intelligence on the planet.

Scaling Fast: The Dollar Tree Breakthrough

BrainBox AIā€™s approach isnā€™t just smartā€”itā€™s fast, seamless, and cost-effective from Day One.

When Dollar Tree signed on with BrainBox AI, 600 locations across 18 states were operational on its platform within monthsā€”without heavy equipment, installation downtime, or disruption to store operations.

The AI simply plugged into the existing systems, started learning, and began optimizing.

One Dollar Tree executive put it admiringly:

ā€œBrainBox AI helps you offset costs from day one. Itā€™s also incredibly flexible; you get new equipment, it adapts. You move to a new location, it moves with you. You grow, it grows with you.ā€

Thatā€™s the real superpower of BrainBox AI in buildings: It keeps learning.

If a retailer remodels, BrainBox AI relearns.
If an office gets new windows, BrainBox AI recalibrates.
If energy prices spike, BrainBox AI shifts its strategy in real-time.

For building owners and operators, this isnā€™t just better energy efficiency; itā€™s a business advantage.

AI is Filling the Gaps in a Labor-Strapped Industry

The HVAC industry has another problem: There arenā€™t enough skilled technicians.

North America alone employs 400,000 technicians but still has a deficit of 100,000 unfilled jobs.

That means thousands of buildingsā€”offices, warehouses, stores, hospitalsā€”operate inefficiently simply because no one has time to fix them.

BrainBox AIā€™s virtual engineer, ARIA, is changing that.

ARIA acts as an on-demand AI assistant for maintenance teams. It can:
šŸ”¹ Diagnose issues remotely (so a technician knows whatā€™s wrong before they arrive).
šŸ”¹ Recommend fixes and suggest spare parts (so there are no wasted trips).
šŸ”¹ Predict machine and part lifespans (so problems are prevented before they happen).

In an industry where labor is stretched thin, ARIA isnā€™t replacing workersā€”itā€™s making them radically more efficient.

Time Magazine named ARIA one of the best inventions of 2024.

The Future: A Smart Grid of AI-Powered Buildings

BrainBox AIā€™s ambition goes beyond individual buildings.

Historically, power grids have focused on supply, but preparing them to satisfy future needs requires developing new intelligent demand capabilities.

Next up for BrainboxAI: weaving the brains of all of its AI-powered buildings into a network to scale a demand-response business that can:

  • Adjust energy use in real time to reduce stress on the grid.

  • Throttle down consumption when the grid is overloaded to prevent blackouts.

  • Tap into cleaner energy sources when renewables are abundant.

With Trane Technologiesā€™ acquisition of BrainBox AI last month, the goal is clear: scale the AI-driven transformation as widely and quickly as possible.

Listen to this podcast episode on AppleSpotifyYouTube, and all other platforms.

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Number of the week: 250 Million

Thatā€™s the square feet of commercial real estate that BrainBox AI operatesā€”equivalent to about half the office space in Manhattan. Itā€™s achieved this remarkable scale in just under six years, making its first sale in May 2019.

Quote of the week: 

ā€œAI isnā€™t replacing techniciansā€”itā€™s making them radically more effective. Instead of walking into a building blind, they get a full diagnostic before they even arrive.ā€

ā€”Sam Ramadori, CEO of BrainBox AI

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The Road to Solve AIā€™s  Energy Challenge

As solutions like BrainBox AI expand, weā€™re tracking the data centers powering AIā€™s growth. We recently spoke with Nazar Khan, CTO of TeraWulf, a company building hydro-powered AI data centers in New Yorkā€”proof that low-carbon, high-performance computing (HPC) is now possible.

Still, data centers account for 2ā€“3% of global emissions, and demand is rising. But few in the industry are standing still.

Take Nvidia, the worldā€™s most valuable company and the central actor in AIā€™s exponential growth. Its newest GPU, Blackwell, is 96% more energy efficient than Hopper, released just two years ago. Over the past decade, Nvidiaā€™s GPUs have become 45,000 times more energy efficient.

Yet efficiency alone wonā€™t curb AIā€™s energy appetite. The Jevons Paradox tells us that as AI becomes cheaper and more accessible, usage will skyrocket, likely offsetting efficiency gains.

Thatā€™s why a new wave of startups is reimagining all aspects of AI digital infrastructure.

Corintis: The Next Leap in Liquid Cooling

Cooling is one of AI computingā€™s biggest hidden costs and emissions sources. It consumes nearly 30% of a data centerā€™s electricity to prevent chips from overheating. In response, data centers are shifting from air cooling to more effective yet technically complex liquid cooling.

Weā€™re tracking Switzerland-based startup Corintis. Its breakthrough is microfluidic cooling embedded directly in the chip, which extracts ten times more heat than conventional liquid cooling solutions.

The impact:
āœ… More powerful AI without overheating.
āœ… Lower cooling costs and water use.
āœ… A significant cut in energy wasteā€”and emissions.

As AIā€™s energy demand soars, every efficiency gain matters.

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