Chamber

Chamber is an AIOps agent for machine learning teams that puts GPU infrastructure on autopilot. Its agent, Chambie, continuously monitors GPU clusters across clouds, forecasts demand, detects unhealthy nodes and reallocates resources in real time, so teams can run about 50 percent more workloads on the same GPUs without manual intervention. When a training run fails, Chambie diagnoses the root cause, fixes the configuration, reruns from checkpoint and posts a plain language summary of what happened and why to Slack, so an engineer reads it over coffee instead of getting paged at 3am. Beyond incident work it discovers idle GPU capacity, right sizes and schedules workloads across teams and capacity pools by real time demand and priority, correlates experiments with infrastructure and resubmits tuned jobs, and can even take a training job described in plain language, write the code, build it, submit it and monitor it, all from the CLI, a Python SDK or Slack. Chamber installs with a single Helm command and discovers your GPUs, workloads and teams on its own, with no config files, instrumentation or migration project. Critically, the agent runs inside the customer's own cluster on Kubernetes, Slurm or a hybrid setup, so models, datasets and code never leave the environment and only stripped operational metadata reaches Chamber; the platform is SOC 2 Type I and II attested. Built by former Amazon and Meta infrastructure leaders, including a founder who led Amazon's central GPU orchestration service and launched AWS CloudWatch Application Signals, Chamber is a Y Combinator Winter 2026 company based in Seattle.