AI Energy Usage is a Black Box
We open it.
See every watt your AI consumes. Know exactly where it goes. Cut waste without cutting speed.
Real-time attribution
Every Workload Has a Power Signature
AluminatiAi reads the energy curve of each job — inference, training, stress test — and maps every watt to the work that drew it.
Chatbot simulation — calm baseline draw
25W+ prefill spike → sustained plateau
Pinned at TDP — max batch size
100 iters · rhythmic training heartbeat
Data from live Apple M5 benchmark · llama.cpp + MLX · 3B parameter model
What You Can't See Is Costing You
AI infrastructure hides its biggest inefficiency in plain sight.
Invisible Consumption
Your GPUs are running. But where's the power going?
Cost Without Cause
Cloud bills show cost. Not cause.
Scale Amplifies Waste
What wastes pennies on 10 GPUs burns thousands on 1,000.
Guesswork Compliance
Regulators want numbers. You have guesses.
How It Works
Install
A lightweight agent. 60 seconds. Zero disruption.
See
Every watt, mapped to every job, model, and team.
Save
Cut waste. Hit targets. Ship faster.
Install
A lightweight agent. 60 seconds. Zero disruption.
See
Every watt, mapped to every job, model, and team.
Save
Cut waste. Hit targets. Ship faster.
Energy Intelligence, Not Just Monitoring
Go beyond dashboards. Get actionable insight into every watt.
See exactly where your power goes
GPU-level power monitoring captures real-time consumption from every card. No sampling, no estimates — actual watts, attributed to actual work.
Know who used what — down to the training run
Energy gets mapped to jobs, models, users, and teams. Not just "this GPU drew 300W" — but "this fine-tuning run consumed 15 kWh over 6 hours."
Make smarter decisions with real data
Compare training runs, identify inefficient jobs, and make energy-aware scheduling decisions. Reduce waste without sacrificing performance.
Built Specifically for AI Workloads
Energy-first monitoring. Traditional tools focus on utilization or throughput. We start with power consumption and work backwards to attribution and optimization.
Designed for ML infrastructure. Not generic compute monitoring adapted for AI. Built from the ground up to understand training runs, inference workloads, and multi-GPU jobs.
Attribution at every layer. From the GPU to the model to the team. Energy usage becomes a first-class metric alongside accuracy, latency, and cost.
Start Monitoring Your GPUs Today
Try our lightweight GPU monitoring agent free for 7 days. Track energy costs, identify waste, and optimize your infrastructure — all from a real-time dashboard.
No credit card required · 7-day free trial · Cancel any time
The Future of AI Is Energy-Aware
As AI scales, teams that understand and optimize their energy footprint will build faster, cheaper, and more sustainable infrastructure.
Join ML platform teams and AI infrastructure engineers building the next generation of energy-aware systems.
Live benchmark · Apple M5 · llama.cpp + MLX · 3B parameter model