Chamber - GPU Infrastructure Optimization Platform
Y Combinator W26Your GPUs are idle.
We put them to work.Your GPUs are idle.
We put them to work.
Built by engineers from
The $240B problem nobody talks about
AI/ML teams on average run on 40-60% GPU usage. [1] That's millions in wasted compute sitting right under your nose.
0%+
GPU capacity wasted
5-0mo
B300 lead time
0x
Longer queue times
Low visibility
You can't see which GPUs are idle, unused, or failing until it's too late.
Silent failures
Bad GPUs corrupt training runs. You find out days later when the model doesn't converge.
Endless queues
Teams wait for GPUs while others sit idle. No smart scheduling means constant bottlenecks.
Team silos
No visibility across teams. One team hoards GPUs while another waits months for access.
See your potential savings
Calculate how much you could save by maximizing GPU usage with Chamber.
Workloads
Running
12
Pending
8
Completed
47
Total
67
llama-finetune-v2
8× H100 · 2h 34m
embedding-train
64× H100 · Queued #2
rlhf-experiment
16× H100 · Preemptible
Jobs start 3x faster
with intelligent queuing
Chamber finds idle GPUs across teams and automatically schedules work. High-priority jobs preempt lower ones, and resume automatically when resources free up.
Detect bad nodes
before they kill your training
Silent GPU failures waste weeks of training. Chamber continuously monitors hardware health and automatically isolates failing nodes before they corrupt your runs.
Capacity Pools
1 WarningTotal Pools
3
Total Instances
260
Production GPU Pool
Node gpu-23 flagged
2m agoMemory errors detected · Auto-isolated from scheduling
Everything you need to
maximize GPU performance
Preemptive Queue
High-priority jobs pause lower ones, resuming automatically on completion.
Fleet Metrics
Monitor GPU usage, costs, and performance across your entire fleet.
Team Fair-Share
Set budgets and quotas. Unused allocation automatically lends to others.
Fault Tolerance
Auto-detect and isolate failing GPUs before they corrupt training runs.
Most teams don't know their true GPU usage. Chamber gives you the visibility and control to maximize every GPU in your fleet.
See your GPU utilization
in 3 minutes
One helm command. Automatic GPU discovery. See exactly where your GPUs are idle.
Get started for freeNo credit card · Any K8s cluster · 3-min setup
FAQ
Tap questions to expand
Management software improves ROI through automated scheduling and workload cleanup. Engineers get GPU availability when they need it, while decision-makers gain visibility into cluster usage and make informed capacity decisions.
Why do I need software to manage my GPUs?
Management software improves ROI through automated scheduling and workload cleanup. Engineers get GPU availability when they need it, while decision-makers gain visibility into cluster usage and make informed capacity decisions.
By minimizing idle time through intelligent scheduling and improving workload efficiency. Our preemptive queue system ensures high-priority jobs run immediately while lower-priority work automatically resumes when resources free up.
How does Chamber reduce GPU costs?
By minimizing idle time through intelligent scheduling and improving workload efficiency. Our preemptive queue system ensures high-priority jobs run immediately while lower-priority work automatically resumes when resources free up.
Chamber works with any Kubernetes-based GPU cluster, including on-prem, cloud (AWS, GCP, Azure), and hybrid setups. We support NVIDIA GPUs across all major architectures.
What infrastructure do you support?
Chamber works with any Kubernetes-based GPU cluster, including on-prem, cloud (AWS, GCP, Azure), and hybrid setups. We support NVIDIA GPUs across all major architectures.
Yes. Chamber runs within your infrastructure. We only collect anonymized telemetry—your models, datasets, and code never leave your environment.
Is my data secure?
Yes. Chamber runs within your infrastructure. We only collect anonymized telemetry—your models, datasets, and code never leave your environment.