Trusted by top AI teams


This is how we imagined the cloud to work: you define an ML job, it will find the cheapest places to run it and then does the work for you.




It's a new approach to utilizing AI infrastructure, making AI experimentation and scaling fast and simple.


1. provision an H100
2. sync my project
3. auto-install dependencies
4. run+stream logs
5. tear down the machine
Featured case studies

Scaling AI Infrastructure at Abridge with SkyPilot
Abridge moved from SLURM to a scalable multi-cloud AI infra with SkyPilot, unlocking 10x faster development cycles.

From SLURM to SkyPilot: How Avataar cut costs 11x with multi-cloud AI infra
Avataar migrated from SLURM to SkyPilot, cutting costs 11x and unlocking GPU capacity on neoclouds.

How Covariant uses SkyPilot to scale AI robotics on the cloud
Covariant runs AI on the cloud using SkyPilot, delivering models 4x faster and more cost-effectively.

GitGuardian's battle-tested open-source stack
SkyPilot powers GitGuardian's MLOps stack for scalable and flexible model development and deployment workflows.

How Papercup built a modern AI platform with SkyPilot
SkyPilot allows Papercup to easily run AI workloads on the cloud, while leveraging spot instances to reduce costs.

Kits.ai trains audio foundation models with SkyPilot
SkyPilot provides researchers at Kits.ai an unified interface to train their KGV family of models on their cloud infrastructure.

How IP Copilot reduces AI spend by 80% and evaluates LLMs 3x faster
Patent discovery and management firm IP Copilot uses SkyPilot to scale their AI fast while keeping costs down.

Analyzing the mouse brain atlas on the cloud with SkyPilot
SkyPilot enables Salk's scientists to perform ground-breaking neuroscience research 3x faster and at 5x lower cost.

How SkyPilot kickstarted the ML infra behind Jam & Tea's AI-native game
SkyPilot helped Jam & Tea Studios move beyond hosted APIs to create 80% cheaper GenAI solutions for their games.