Sustainable Neurosymbolic AI Infrastructure
Right now, over 12,000 Dutch businesses can't get power connections until the 2030s. AI datacenters are consuming entire city grids. We built a different path: neurosymbolic AI combining neural learning with symbolic reasoning uses 96% less energy, delivers explainable intelligence. This is how we keep the lights on for everyone.
The European Grid Crisis
This isn't a future problem. It's happening right now, across Europe. The numbers tell a story we need to understand.
Netherlands
12,000+ businesses waiting for power connections. Some won't get electricity until the mid-2030s.
Amsterdam
Complete ban on new datacenters. The grid simply can't handle more demand.
Frankfurt
Power connection queues stretch beyond 2030. Critical infrastructure can't expand.
Dublin
AI datacenters consume 80% of the city's electricity. Families compete with servers for power.
The cost is real: Grid congestion costs the Dutch economy €40 billion annually. Upgrading Europe's grid to handle current AI growth will require €200+ billion by 2040.
Meanwhile, hospitals, schools, and new homes wait years for power connections while AI datacenters get priority access to shrinking grid capacity.
How AI Broke The Grid
Let's look at the numbers. Not to scare you, but because understanding the problem is the first step to fixing it.
A Single AI Server's Real Impact
Hardware Components (NVIDIA DGX H100)
- 8× NVIDIA H100 GPUs5,600W
- CPU, Memory, Storage~500W
- Subtotal (IT Equipment)6,100W
- Datacenter Overhead (PUE 1.5×)+3,050W
- Total Power Draw9,150W
Annual Impact (60% Utilization)
- Energy Consumption48,139 kWh/year
- Cost (€0.30/kWh NL avg)€14,442/year
- CO₂ Emissions (393g/kWh)18,919 kg CO₂e
- Equivalent to...Keeping the lights on in 92 households for a year
The Scale of AI Infrastructure (October 2025)
Just OpenAI's 125,000 servers draw 1.14 gigawatts of continuous power. That's enough to power 3.8 million Dutch households.
To put that in perspective: the entire population of the Netherlands is 17.9 million people in 7.9 million households. OpenAI alone uses nearly half of what would power every home in the country.
When Datacenters Compete With Homes
It's not just about electricity. Every AI datacenter consumes the same scarce resources Europe needs to house its people.
Europe's Housing Crisis
Homes missing across Europe (3.5% of total housing stock in 2024)
Growing to 453,000 by 2027. Only 82,000 homes built in 2024 vs 100,000 target
Homes in 2025 (down 19%). Building permits down 40%+ since 2021
Italy: only 1.6 homes per 1,000 people. Spain: below 0.3% construction rate
Materials and skilled labor shortages making it worse every year
What One Datacenter Consumes
Acres per campus (only 30-40% can be developed)
Typical large-scale datacenter facility footprint
Of datacenter construction carbon footprint
Additional structural and reinforcement steel carbon cost
The Resources We're Fighting Over
Scarce Land
A single hyperscale campus uses 500-1,000 acres. That same land could house thousands of families in a country where every square meter counts.
Construction Materials
Concrete, steel, and specialized building materials in short supply. AI datacenters compete directly with housing construction for the same limited resources.
Skilled Workers
Construction workers, electricians, and engineers are in critically short supply. Every datacenter project pulls workers away from building homes.
What 96% Efficiency Really Means
When we use 96% less energy, we don't just save electricity. We need 96% fewer datacenters. That means:
In a housing crisis, every square meter, every ton of steel, and every skilled worker matters. Efficient AI isn't just about saving energy. It's about building the Europe we want to live in.
The Hidden Cost of AI Hardware
Energy consumption is just part of the story. The real waste is what happens when those expensive servers become obsolete.
Traditional GPU Servers
Each server contains rare earth minerals, specialized circuits, and cooling systems that become obsolete as AI advances. Most components cannot be recycled effectively.
Dweve Systems
Standard CPU or FPGA servers without specialized GPUs. Longer useful life because software improvements don't require new hardware. Components can be upgraded individually.
The Scale of the E-Waste Problem
According to industry sources, datacenter GPU lifespans can be as short as 1 to 3 years as AI models advance. This creates a massive hardware replacement cycle that traditional IT equipment never faced.
Why Dweve Creates Less Waste
No specialized GPUs means no need to replace servers when new GPU generations arrive
Software improvements increase capability without hardware changes
Standard components can be upgraded individually instead of replacing entire servers
Lower power consumption means less thermal stress, extending component lifespan
Simple air cooling reduces mechanical failure points compared to liquid cooling systems
Standard server components have established recycling and refurbishment channels
The Smarter Path
We asked a simple question: what if we stopped trying to brute-force intelligence with more power, and instead built truly sustainable AI that thinks more efficiently? The answer changed everything.
Verified against FP16 neural networks running identical benchmarks
Runs on standard CPUs or FPGAs with air cooling. No specialized GPUs needed.
Same intelligence, dramatically less impact on the grid. This is what energy-efficient AI looks like.
How This Works
Traditional GPU-Based AI
- ×Billions of floating-point calculations per inference
- ×Every parameter activates for every decision
- ×Requires specialized GPUs running continuously at 700W
- ×Industrial liquid cooling systems consuming water
- ×Can only run in specialized datacenters with dedicated power
Dweve Binary-Constraint Intelligence
- Binary yes/no decisions at the fundamental level
- Sparse activation: only 4-8 experts active per query
- Runs on standard CPUs or FPGAs with SIMD optimization
- Simple air cooling, no water consumption
- Runs anywhere: office, edge device, or datacenter
Real Impact Comparison
One server. Two approaches. Dramatically different outcomes for Europe's energy future.
Traditional AI Server (DGX H100)
Dweve System (Equivalent Capability)
Your 5-Year Savings Per Server
Switch one traditional AI server to Dweve, and here's what you gain
Two Paths Forward
We're at a crossroads. One path leads to limits and rationing. The other leads to abundance and accessibility. The technology exists for both. The choice is ours.
If We Keep The Current Path
Picture Europe in 2030 if AI keeps growing at 9,150W per server...
- •More cities join Amsterdam, Frankfurt, and Dublin in banning new datacenters
- •The waiting list for business power connections grows from 12,000 to hundreds of thousands
- •Grid congestion costs balloon from €40 billion to €100+ billion annually
- •Mountains of e-waste from GPU servers replaced every 1 to 3 years
- •European AI becomes a luxury only massive corporations with datacenter access can afford
- •We build new power plants for AI while families wait years for electricity connections
The Efficient Path
Imagine if we build smarter from today forward...
- AI grows 100× more capable while using the same total grid capacity we have today
- No more datacenter moratoriums because efficient AI fits within existing infrastructure
- Businesses, schools, and homes get power when they need it, not after years of waiting
- Longer hardware lifecycles mean less waste and lower replacement costs
- Every European business can afford advanced AI, not just tech giants with datacenter budgets
- We meet EU climate goals while advancing technology, not by choosing between them
Here's the good news: efficiency and capability aren't opposites. With a 25× efficiency gain, you can deploy AI 25× more widely with the same infrastructure. We're not choosing between progress and sustainability. We're choosing between smart growth and hitting a wall.
Built For European Sovereignty
Low-carbon AI isn't just good for the planet. It's the foundation of true data sovereignty.
On-Premise Intelligence
Because it uses so little power, you can run advanced AI right in your office on a standard power connection. Your data never leaves your building, never crosses borders, never raises questions with regulators.
EU AI Act Compliant
From August 2025, EU regulations require energy efficiency disclosure for AI systems. Our 96% reduction isn't just impressive, it's documented, verified, and ready for compliance reporting.
Grid-Friendly AI
No special power infrastructure needed. No datacenter moratoriums to navigate. No years-long wait for grid connections. Our grid-friendly AI deploys where your business needs it, when you need it.
Germany requires datacenters to use 50% renewable energy (rising to 100% in 2027). With 96% less total energy consumption, our renewable energy AI makes meeting these requirements trivially easy instead of prohibitively expensive.
What This Means For You
Big picture aside, here's what truly green AI with 96% energy reduction means in practice, right now.
No Special Infrastructure
Plug into a standard office outlet. No electrician, no datacenter, no years-long wait for grid capacity. If you have power for computers, you have power for this.
Solar-Powered AI
A small solar installation can power serious AI workloads. Battery backup becomes affordable. This is solar-powered AI that actually works. True carbon-neutral intelligence isn't a dream, it's practical.
Deploy Anywhere
In your office building. On a hospital floor. In a rural clinic. On a ship. If humans can work there, this AI can run there. No datacenter required.
Democratized Access
SMEs, startups, research labs, non-profits. When AI costs 96% less to run, you don't need a tech giant's budget to deploy it. Advanced AI for everyone.
Let's Build The Smarter Future
The grid crisis is real. The AI revolution is happening. But we don't have to choose between them. Efficiency isn't a limitation, it's an opportunity. Let's seize it.