One GPU cluster across every cloud

Overcast pools hyperscalers, neoclouds, and your own racks into one cluster of GPUs and CPUs. Built for developers processing massive amounts of data. Run on our capacity or plug in your own cloud accounts.

label_video.pyyour workload

Lambda256 GPUs

CoreWeave224 GPUs

Nebius160 GPUs

AWS128 GPUs

Azure96 GPUs

Google Cloud64 GPUs

Crusoe64 GPUs

Your racks32 GPUs

One Overcast cloud

Every provider, routed as one cluster

label_video.pyyour workload

Lambda256 GPUs

CoreWeave224 GPUs

Nebius160 GPUs

yoursAWS128 GPUs

yoursAzure96 GPUs

Google Cloud64 GPUs

Crusoe64 GPUs

yoursYour racks32 GPUs

One Overcast cloud

Hyperscalers, neoclouds, and your own accounts and racks, routed as one cluster

From one prompt to thousands of GPUs or CPUs.

1Install the skill

One line teaches your agent to use Overcast.

Mix our capacity with your clouds and racks.

ProvidersPriceSecuritySpeed

Lambda

CoreWeave

Nebius

AWSyours

Azureyours

Google Cloud

Crusoe

Your racksyours

Price. Each job goes where it costs least, counting the cost of moving your data.Security. Sensitive jobs stay on your own accounts and racks, in regions you approve.Speed. Every provider at once, for the most machines and the fastest finish.

Cursor writes the code. No hardware to size.

Every machine, GPU or CPU, and dollar in one view. When the job finishes, the cluster scales to zero.

Overcast

BBurla

Jobs

Providers

Machines128

Billing

Settings

Recent jobs

label_videoGPUbacktest_fxCPUalign_genomesCPUetl_clickstreamCPU

JPJoe Perryjoe@burla.dev

label_videobacktest_fxalign_genomesetl_clickstream

Jobs / label_video

Running

job_8f2k41 · started 12:04 by joe@burla.dev via Cursor · H100 · optimize for speed

View logsCancel job

Machines running

128

of 128, 1,024 GPUs

GPU utilization

80.2%

live

Throughput

823,319/s

frames

Spend

$8,970

cap $25,000

1,656,000,000 / 3,600,000,000 frames46% · 40 min left

Machines 128 / 128 receiving code running

Lambda80%

32 machines · 256 GPUs

CoreWeave81%

28 machines · 224 GPUs

Nebius81%

20 machines · 160 GPUs

AWSyours80%

16 machines · 128 GPUs

Azureyours80%

12 machines · 96 GPUs

Google Cloud80%

8 machines · 64 GPUs

Crusoe80%

8 machines · 64 GPUs

Your racks80%

4 machines · 32 GPUs

EventsLogsOutputsstreaming

12:04:03INFOrouteSpeed: all 8 providers at once

12:04:04INFOdeployShipping code to 128 machines

12:04:41INFOcluster128 machines running, 1,024 GPUs at 80% utilization

One cloud is a bottleneck.

Overcast gets you past capacity shortages and gives every workload more options on cost, speed, and security.

When your provider runs out of capacity in us-east-1, GPU or CPU, your job waits in a queue.

Overcast pools every provider into one cluster, so capacity is wherever it is cheapest right now.

A machine pulled mid-run means lost results and a retry loop you have to write yourself.

Reclaimed machines are replaced in seconds and every finished result is kept.

Clusters sit half-used between jobs while the meter keeps running.

The cluster scales to zero the moment a job finishes, and never spends past your cap.

Modeled from public list prices, not measured runs. See the math

Every job goes to the cheapest, most secure, or fastest compute. Then every machine you rent runs close to full, without running out of memory.

Overcast picks where it runs

Choose price, security, or speed for each job.

Small tasks fill each machine. When a big task needs more memory, Overcast gives it room and boots another machine for the small tasks.

Crashes when a big task runs out of memory