70% of High-Performance Compute is wasted on preventable failures. Expanse predicts job failures, orchestrates across clusters, and autonomously fixes running workloads.
One platform. Any scheduler. No wasted compute.
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Infrastructure is expensive. Wasting it on silent crashes and unoptimised jobs destroys ROI.
Memory spikes kill training runs 10 hours in.
Requesting 1 GPU for a distributed ml training task.
Waiting days for resources that crash on launch.
Over-provisioning hardware by 2x to be "safe".

The New Way
The old way
What the intelligence layer unlocks
Expanse doesn't just monitor your jobs - it understands them. Every capability builds on a shared knowledge base that gets smarter with every workload.
See everything.
Real-time metrics across every job, node, and GPU in your fleet, looking at memory usage, queue depth, training progress, and more. All streaming into a single dashboard. No more SSH-ing into nodes to figure out what went wrong.
Know before you submit.
Before your job hits the queue, Expanse estimates runtime, flags out-of-memory risk, and recommends resource adjustments. It learns from every job it's ever seen, so the more your team run, the sharper the predictions become.
One command. Any cluster.
Submit once and let Expanse handle the rest. It abstracts away scheduler differences across SLURM, Kubernetes, and custom runtimes - managing dependencies, data transfers, and coordinating multi-step pipelines.
Jobs that fix themselves.
The Expanse agent watches running jobs for signs of failure: crashes, stalled progress, runaway memory, and more. It doesn't just alert. It diagnoses the root cause, adjusts the configuration, and resubmits. Automatically.
The Autonomous Agent
The agent sits on top of the Expanse intelligence layer, drawing on structured data, and custom tooling the platform provides. It works around the clock so you don't have to.
When a job fails overnight, the agent diagnoses the issue, adjusts the configuration, and resubmits, all before you even notice. You open your laptop to results, not a stack trace.
The agent draws on the full Expanse intelligence layer: cluster data, job history, resource predictions - and acts on it around the clock. No pager duty. No 2am SSH sessions.
Every action the agent takes is logged. What it detected, why it intervened, what it changed. No black boxes. You stay in control without doing the work.
Knowledge Base
Expanse learns from every workload it touches. Failure signatures, resource profiles, and recovery patterns feed back into a shared intelligence layer - so predictions get sharper with every run across the network.
The more jobs Expanse sees, the more accurate it gets. OOM predictions, runtime estimates, and failure detection all improve continuously as the knowledge base grows.
When a researcher in London hits a gradient divergence, an engineer in SF benefits from the fix. Anonymised patterns flow across the network - your team learns from every team.
Need to keep your data private? Enterprise licences run a fully isolated knowledge base - same intelligence, trained only on your own workloads. No data leaves your infrastructure.
"Expanse saved us a lot in one week by catching a low memory provisioning before we launched a 500-node training run."
"The pre-flight checks are a lifesaver. No more waiting 12 hours in a queue just to fail effectively instantly."
Start a pilot in 2 weeks. If we don't deliver value, you've lost nothing.