Help build the GPU visibility the market keeps promising.
Organizations are standing up GPU farms faster than anyone can measure them. Plenty of tools say they monitor GPUs, yet most stop at one vendor, one cluster, or one cloud bill. Visual One Intelligence® is building the view that covers the whole estate, and the Advisory Council is the small group of infrastructure leaders shaping it with us.
The questions change as GPU adoption grows.
Some clusters start with a few experimenting teams and grow into production. Others run at full load from day one. The questions are the same either way; high-volume adopters just reach them in days instead of months.
Few teams, low utilization.
- Set a utilization baseline and tagging
- Compare on-prem cost with cloud
Many teams, mixed schedulers.
- Find orphaned capacity
- Normalize cost across resources
- Begin showback
Production and research share it.
- Move to chargeback
- Forecast and plan purchases
- Weigh buying against bursting to cloud
No GPU environment is one-size-fits-all.
Rising AI and cloud costs are pushing more organizations to bring GPU capacity in-house, building out data centers to run their own NVIDIA farms. That moves a growing share of AI spend on-prem, outside the cloud bill most cost tooling is built around.
A common setup looks like this: a shared scheduler gives every team with an AI project time on the local cluster. That solves access. It does not solve visibility, because the cluster underneath is rarely one thing.
NVIDIA, AMD, and Intel hardware each report in their own way through their own tools. The scheduler sees jobs, not cost. The cloud bill sees only the cloud. So the people accountable for the spend are left piecing a picture together by hand, and three questions go unanswered:
- Do we really need more GPUs?A new purchase request lands with no data on how the existing cards are used.
- Who is using them, and who should pay?Every team draws on the cluster, and the cost sits in one central budget.
- What is AI spend returning?Finance asks, and nobody owns the answer.
One view across the estate, starting with the hardware most of it runs on.
We would rather show you exactly where the work stands than describe a finished product that does not exist yet.
Built today
- NVIDIA GPU telemetry collectorBuilt on NVIDIA Data Center GPU Manager (DCGM), capturing utilization at the source.
- Fully loaded on-prem costingAcquisition, maintenance, power, floor space, and personnel, priced with the same rigor as cloud.
- Industry-standard rate cardStart costing on-prem infrastructure with industry-standard device costs, even before your own financial data is clean.
- Chargeback and showbackBy business unit, owner, or cost center, for storage and compute across cloud and on-prem.
- Budget-versus-actual and forecastingAcross the hybrid environment, on a FinOps Certified Platform that is SOC 2 Type II certified.
In development, shaped by the council
- GPU utilization and cost reportingThe reporting layer on top of the collector: what each GPU does and what it really costs.
- Chargeback for GPU workloadsExtending the existing tag model so “who pays for AI” gets an answer.
- AI token usage trackingBringing what AI workloads consume into the same budget and forecast view.
- One view across GPU manufacturersThe goal is a single pane of glass for mixed hardware. NVIDIA comes first; what comes next is a council question.
A working group, with your requirements in the build.
The Advisory Council is a small group of IT and infrastructure leaders who run real GPU environments and want a say in how they get measured. Members see the work early, tell us where it falls short, and help decide what gets built next. There is no cost to take part.
- 1
Apply
Tell us about your GPU footprint in the short form below. We will set up a call to confirm the fit.
- 2
See what is built
We walk you through the collector and the platform it feeds, and where it makes sense, stand it up in your environment alongside our team.
- 3
Shape what comes next
Your feedback goes straight to the people building it.
A real answer for your GPUs, and a say in how it gets built.
A real solution for on-prem GPU efficiency and cost
- Built against your environmentCouncil members are first in line for GPU utilization and cost reporting as it lands, measured on the hardware you actually run instead of a demo.
A voice in what comes next
- Direct access to the teamYou work directly with our product and analyst teams, with early access to GPU reporting as it lands and a real voice in the roadmap.
“Visual One Intelligence did all the work for us so we could spend our time on decision-making, not data collection and analysis.”
IT Manager, Large Retailer“Visual One Intelligence helped us to make better decisions and save money.”
VP of IT Infrastructure, Major Food ProducerApply to the GPU Visibility Advisory Council.
If you own GPUs and cannot see how they are used or what they really cost, we are building this for you, and we would rather build it with you.
Seats are limited so every member gets real time with the team. Tell us about your environment and we will be in touch to set up a call.