
Push your AI code to a repo. We handle containers, scaling, cold
starts, and infrastructure — you ship features.

No DevOps degree required. From local code to globally
deployed GPU endpoint in under a minute.


Idle functions cost exactly $0. Workers shut down automatically between requests — no wasted GPU-hours.

Set per-worker concurrency limits. Route burst overflow to a queue and process at your own pace.

We pre-warm replicas based on your traffic patterns, cutting cold start probability by up to 80%.

Idle functions cost exactly $0. Workers shut down automatically between requests — no wasted GPU-hours.

Set per-worker concurrency limits. Route burst overflow to a queue and process at your own pace.

We pre-warm replicas based on your traffic patterns, cutting cold start probability by up to 80%.

From single A100s to multi-node H100 clusters — spin up bare-metal
GPU capacity in under a minute with no scheduling queues.

vs. self-managed Kubernetes GPU pods


From single A100s to multi-node H100 clusters — spin up bare-metal
GPU capacity in under a minute with no scheduling queues.


One-click GitHub / GitLab integration. We listen to push events on any branch you configure.

We detect Python, pin CUDA, cache your requirements.txt, and produce a reproducible image in seconds.

New builds get 10% of traffic first. If health checks pass, traffic shifts 100% with no downtime.

Every deploy is versioned. Roll back to any previous build in one click or one CLI command.


2.3 - CUDA 12.4

Transformers 4.x

0.5 - PagedAttn

10.x - FP8

SDXL - Flux

GGUF - GGML

0.4 - XLA

MusicGen - MACs

Protein - Mol

Any CUDA image
