I. The Thesis
Intelligence is approaching
the cost of energy.
AI is driving compute costs toward a floor set by physics: the energy required to flip bits.
Every operation has a minimum energy cost defined by thermodynamics
(Landauer's principle: kT ln 2 per bit erasure).
As hardware approaches this floor, the price of intelligence converges on the price of electricity.
Traditional cloud providers price by the hour, regardless of what your code actually does.
We price by the joule — you pay for the energy your workload consumes, nothing more.
This isn't just cheaper. It's the only pricing model that scales
as computation becomes abundant.
945 TWh
Projected datacenter
electricity by 2030
70%
Compute wasted on
unoptimized workloads
10–100x
Energy reduction with
optimized placement
$5 once
Minimum balance
spend it on compute
II. The Problem
You pay for time.
Your code uses energy.
A cloud server billed hourly charges the same whether your process is idle or saturating every core.
You're renting a chair, not buying work done.
Joule Cloud measures the actual energy each workload consumes —
compute, memory bandwidth, network, storage I/O —
and charges exactly that.
Idle processes cost near zero. Burst workloads pay for burst energy.
The bill reflects reality.
Billing unit
hours
joules
Idle cost
100%
~0%
Burst penalty
cap / upgrade
none
Energy visible
no
per-task
Placement
manual
auto / carbon
III. The Receipt
Every deploy gets an
energy receipt.
When your workload finishes, you get a receipt showing exactly where every joule went.
Compute, memory, network, storage — broken down per task,
with a total energy cost and carbon intensity based on the region's grid.
This isn't an estimate. It's metered at the hardware level, validated against
the Landauer floor, and reported with SCI scores for compliance
with ISO/IEC 21031, CSRD Scope 3, and emerging sustainability regulations.
Compute (4 cores, 12.3s)18.4 mJ
Memory bandwidth4.2 mJ
Network egress (2.1 MB)1.8 mJ
Storage I/O0.6 mJ
Total energy25.0 mJ
Region: Helsinki (80 gCO2/kWh) · SCI: 0.003 · RGESN: pass
IV. The Grid
13 regions. Workloads follow
the most efficient clean energy.
Your code isn't locked to a region. The scheduler continuously evaluates
carbon intensity, energy price, network latency, and thermal headroom
across all 13 nodes and migrates workloads to the optimal location.
A batch job started in Virginia may finish in Helsinki if Nordic wind power
drops the energy cost by 60%.
For latency-sensitive workloads, you pin regions. For everything else,
the grid does the math.
Sovereignty controls ensure data never crosses jurisdictions you haven't approved.
V. The Stack
One platform. From edge
to sovereign cloud.
Joule Cloud is a complete cloud platform —
compute, storage, networking, AI inference,
databases, and observability — all metered in joules,
all placed by the same energy-aware scheduler.