Chamber is a YC W26 startup offering an AIOps platform to automate GPU infrastructure management, helping ML teams save time and optimize resource utilization across multi-cloud and on-prem environments.

Your AIOps Teammate to

Built by observability and AI infrastructure veterans from

Meet Chambie, your AIOps teammate

Setting up GPU infrastructure across clouds, creating training jobs, and fixing or optimizing them shouldn't be hard.

That's why we built Chambie, your all-in-one AIOps teammate to accelerate ML team velocity. No more infra setup, no more missed failures. Chambie handles everything automatically.

Your team is spending too much time babysitting infra.

Workloads fail silently. Root-causing means digging through logs, metrics, and orchestration events across tools.

GPUs sit idle in one cluster while jobs queue in another. No way to balance capacity across clouds.

Getting the right outcomes for training jobs means correlating model experiment metrics with infrastructure metrics, and running many manual iterations to get there.

Give your ML team hours back every week.

While running more on existing GPUs.

Observe & Debug

Full GPU workload observability with automatic performance insights and root cause analysis. Find the issue in seconds, not hours.

Orchestrate & Optimize

Advanced cross-cloud orchestration maximizes GPU availability and utilization. Run more on the infrastructure you already have.

Iterate & Ship Faster

Chamber connects experiment metrics to infrastructure data and uses agents to help you iterate faster. Analyze runs, tune resources, and resubmit jobs automatically using our CLI, SDKs, or even in Slack. We work where you work.

Frequently Asked Questions

How long does it take to set up Chamber?

We handle deployment for you. Our team gets Chamber running in your environment, whether that's Kubernetes, Slurm, or a hybrid setup, with zero disruption to existing workflows.