Every workload. Every cloud. One pane.
Workload Explorer
Advanced search and filtering across all workloads
| Name | Status | Class | Project | User | GPU | Count | Submitted | Cost | Actions |
|---|---|---|---|---|---|---|---|---|---|
| llama-ft-v2 | RUNNING | RESERVED | LLM Research | H100 SXM | 64 | 2/27/2026 | $2,340 | ||
| bge-embed-109 | RUNNING | ELASTIC | Embeddings | H100 SXM | 8 | 2/27/2026 | $412 | ||
| vit-pretrain-l16 | RUNNING | RESERVED | Vision | H100 SXM | 16 | 2/27/2026 | $890 | ||
| whisper-ft-v3 | RUNNING | ELASTIC | Speech | H100 SXM | 4 | 2/27/2026 | $156 | ||
| codegen-sft-13b | RUNNING | RESERVED | Code Gen | H100 SXM | 32 | 2/26/2026 | $4,120 | ||
| clip-align-xl | QUEUED | ELASTIC | Multimodal | H100 SXM | 32 | 2/27/2026 | — | ||
| reward-model-v4 | QUEUED | ELASTIC | RLHF | H100 SXM | 8 | 2/27/2026 | — | ||
| reward-train | FAILEDWhy? | ELASTIC | RLHF | H100 SXM | 8 | 2/26/2026 | $86 | ||
| dpo-align-7b | FAILED | RESERVED | Alignment | H100 SXM | 16 | 2/24/2026 | $1,240 | ||
| gpt-neo-eval | COMPLETED | ELASTIC | Evaluation | H100 SXM | 4 | 2/26/2026 | $58 | ||
| t5-summary-v2 | COMPLETED | ELASTIC | Summarization | H100 SXM | 8 | 2/26/2026 | $445 | ||
| bert-cls-ft | COMPLETED | RESERVED | NLP Prod | H100 SXM | 8 | 2/25/2026 | $310 | ||
| mistral-merge | COMPLETED | RESERVED | LLM Research | H100 SXM | 4 | 2/24/2026 | $124 |
Built by observability and AI infrastructure veterans from
Your newest teammate lives in Slack.
When a run fails, Chambie diagnoses it, fixes the config, reruns from checkpoint, and posts the summary — root cause, fix, and why — to your channel. You read what happened over coffee instead of getting paged at 3am.
Failed runs are diagnosed, corrected, and rerun from checkpoint — autonomously, even at 3am.
Ask anything about a run or the fleet — answers come with logs, metrics, and full context.
Describe a training job in plain language. Chambie writes the code, builds, submits, and monitors it.
Your job failed at 3am. Nobody woke up.
Scroll to scrub Chambie resolving a failed training run — root cause, fix, rerun — end to end. Scroll back up and it rewinds.
Less babysitting. More shipping.
Observe & Debug
Workloads fail silently. Root-causing means spelunking logs, metrics, and k8s events across five tools.
Chamber watches every workload and hands you the root cause in plain English — file, fix, and all.
root cause in secondsOrchestrate & Optimize
GPUs sit idle in one cluster while jobs queue in another. Nobody can see across clouds.
Cross-cloud orchestration routes work to free capacity. Run more on the GPUs you already pay for.
across clouds & clustersIterate & Ship
Connecting experiment metrics to infra metrics takes manual iteration after manual iteration.
Agents correlate experiments with infrastructure and resubmit tuned jobs — from CLI, SDK, or Slack.
in your flow of workLive before your coffee cools.
One Helm command. Chamber discovers your GPUs, workloads, and teams on its own — no config files, no instrumentation, no migration project.
Audited controls, certified.
The agent deploys into your cluster — not ours.
Models, datasets, and code stay in your environment.
Only stripped operational metadata reaches Chamber.
Hand the pager to Chamber.
Talk to the founders. See exactly how many engineer-hours your fleet gives back.
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.
Is my data secure?
Yes. Chamber is SOC 2 Type I certified. It runs within your infrastructure. Your models, datasets, and code never leave your environment.
What infrastructure do you support?
Multi-cloud and on-prem. Chamber works with AWS, GCP, Azure, on-prem clusters, Slurm, and Kubernetes, including hybrid setups across all of them.
What is the Chambie AI agent?
Chambie is Chamber's conversational AI teammate. Ask questions in natural language from Slack, the CLI, or the console — find failed jobs, explain bottlenecks, check utilization — and let it take action with full infrastructure context.
Can Chamber manage GPUs across multiple clusters and clouds?
Yes. Workloads route to available capacity across your entire fleet — on-prem, AWS, GCP, Azure, or hybrid — from a single control plane.
What integrations does Chamber support?
Slack, email, and custom webhooks for alerts and incident workflows, plus a programmable API, CLI, and Python SDK. Experiment trackers like Weights & Biases correlate directly with infrastructure telemetry.