Develop the AI you own with frontier velocity

One platform for your AI lifecycle, on your infrastructure — Kubernetes, Slurm, 20+ clouds

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AI Compute Platform

Bring order to sprawling
AI compute and workloads

SkyPilot is the AI Compute Platform: Bring all AI compute (Kubernetes, Slurm, VMs, on-prem), and run the entire AI lifecycle — with frontier-level velocity.

One platform, frontier velocity

Manage any AI compute

Manage any cluster, any cloud, any Kubernetes, or Slurm—under one interface.

Capabilities for modern AI teams

From CLI to intelligent scheduler, GPU monitoring, or quotas, SkyPilot equips your infra with frontier velocity.

Trusted by leading cloud providers

Kubernetes

Slurm

AWS

GCP

Azure

CoreWeave

Nebius

Lambda

Together AI

OCI

Paperspace

Vast

Fluidstack

Cudo

RunPod

IBM

SCP

vSphere

Cloudflare

Prime Intellect

Seeweb

Fast-moving AI teams, faster

SkyPilot gives AI teams a simple interface to run the entire AI lifecycle, so everyone moves faster.

DEVELOPMENT

PRE-TRAINING

POST-TRAINING

REINFORCEMENT LEARNING

BATCH INFERENCE

DEPLOYMENT

Development

Spin up instantly. Connect with SSH or IDE. Or run agent fleets.

Pre-training

Scale to thousands of nodes, auto-swap when GPUs fail.

finetune.sky.yaml

Post-training

Launch parallel runs with gang and topology-aware scheduling.

Reinforcement Learning

Co-schedule RL components on heterogeneous hardware.

Batch inference

Run cost-efficient, fault-tolerant batch workloads.

Docker

Ray

Hugging Face

Verl

PyTorch

DeepSpeed

vLLM

SGLang

Deploy, bring any framework

From training to serving — works with your favorite framework.

Supercharge your AI infra

Infra teams seamlessly orchestrate all clusters (or clouds). With the ability to run on any compute, you future-proof your AI infra.

Easily add GPUs, maximize utilization

Add a new cluster/neocloud in minutes. SkyPilot pools all your compute providers to reduce fragmentation.

Scalable control plane

Onboard new users, teams, or workloads with ease. SkyPilot's control plane scales with you.

AI abstractions for Kubernetes

SkyPilot makes K8s AI-native: Multi-cluster support, topology-aware scheduling, quota, and preemption.

Multi-cloud GPU infrastructure

When needed, scale to new providers with confidence.

Standardizing providers

Onboard all your providers with common operations — validation, benchmarks, observability. Same for management.

SkyPilot Multi-Cluster

With native multi-cluster support, bring all GPU clusters into a single platform to drive higher utilization.

Priority queueing, GPU sharing, quotas

Maximize fleet utilization by intelligently scheduling workloads with different priorities and shapes (batch, train, inference).

GPU healthchecks

Proactive and reactive health checks across the fleet, with auto-remediation of GPU and NCCL-related faults.

Enterprise ready

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Secure, in your premises

BYOC and BYOK

Private VPCs / Airgapped

Use open-source or enterprise platform

Increase utilization, control AI spend

Auto stop idle compute

Advanced quota management

Cost management and reporting

Team controls

Fast onboarding with SSO

Unified dashboard for all your compute

Policy enforcement, RBAC, Workspaces

"SkyPilot provides a unified interface across all our clouds. Scaling to new GPU clusters now takes minutes instead of weeks, and our researchers launch 1000s of jobs across all our clouds in seconds."

Linden Li

Co-founder, Applied Compute

"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."

Tobi Lütke

CEO, Shopify

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"SkyPilot is one of the best training orchestrators I’ve used. Easy to setup, light weight to use and configurable in just the right places."

Sisil Mehta

ML Platform Lead, Abridge

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"SkyPilot is now our standard AI infrastructure layer, powering all our training and enabling us to scale online RL to 2,000+ GPUs on K8s, previously impossible on Slurm."

Tony Wu

Core Researcher Engineer, H Company

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"Moving from SLURM to SkyPilot was a strong win for us. A unified next-gen platform to manage all our clusters means we can scale GPUs exactly when we need them without lock-in."

Debajyoti Datta

Co-Founder, Hippocratic AI

Linden Li

Co-founder, Applied Compute

“SkyPilot provides a flexible orchestration layer that adapts to Nubank's infrastructure and operational requirements, rather than constraining us to a rigid platform. Equally valuable is the strength of the SkyPilot community and the responsiveness of its support. Together, these have made SkyPilot a foundational part of how we run AI workloads at scale.”
Abhishek Shivanna
Machine Learning Senior Manager, Nubank
“SkyPilot simplifies job submission to kubernetes, reducing yaml burden for users to contend with. Open source, growing fast in adoption. We expect the market to consolidate around a few approaches [...] and SkyPilot for those running in multi-cloud scenarios.”
SemiAnalysis
AI & Semiconductor Research Firm
“As we scaled, we needed to onboard new GPU vendors like Nebius for additional GPU capacity. SkyPilot Platform made it super easy for our AI team to start training foundation models on new infrastructure from day one, with built-in GPU health monitoring, no Kubernetes expertise needed.”
Rui Zhang
Head of Core Engineering, HeyGen
“SkyPilot enables us to accelerate and scale our experimentation by seamlessly managing compute resources across clouds and clusters. It abstracts away low-level infrastructure operations, such as provisioning and scheduling, allowing researchers to focus on model development and evaluation.”
Srijith Rajamohan
Head of AI Research, Redis
“Skypilot makes prototyping ML workloads incredibly low friction! I can just throw this header at the top of my script, and it'll run automatically.”
Kyle Corbitt
CEO, OpenPipe
“SkyPilot's approach to a unified interface across clouds is the kind of thoughtful abstraction the AI community needs. ”
Jeremy Howard
Founder, Answer.AI
“Infra behind RFM-1: Our Robotics Foundation Model is trained on several clouds; this gives us more GPUs for high experimentation velocity. ”
Rocky Duan
CTO, Covariant
“SkyPilot has been a great tool for saving costs and scaling easily on neoclouds.
What used to require weeks of custom setup now takes minutes, giving us seamless access to better GPU availability and pricing beyond just the hyperscalers.”
Hongbo Miao
Senior Staff AI Engineer, Archer Aviation
“Awesome package that we use on a daily basis for our NIH BRAIN project. Thx Skypilot team 🙏”
Joe Ecker
Director, Genomic Analysis Lab, Salk Institute
“GenAI workloads demand new tools to handle everything from dev pods to large training runs, often on different clusters and accelerators. SkyPilot is such a tool that gives us not only these AI-native capabilities but also the flexibility of infra choices. Our large-scale model training has all moved to SkyPilot now.”
Junghwan Lim
CTO, Motif Technologies
“Great cloud management framework for AI researchers. SkyPilot makes provisioning and controlling GPU instances across cloud providers simple and cost-efficient, thereby allowing the scientists to focus on core AI work.”
Ljubomir Buturovic
VP Machine Learning, Inflammatix
“SkyPilot has become our go-to platform for AI workloads. Its intelligent scheduler saves us the overhead of manually managing GPU resources.
Our teams are more productive, and our compute costs are substantially lower.”
Srivatsan Sridhar
Head of Data Science, 314e Corporation
“By integrating Nebius with SkyPilot we are able to execute jobs across multiple GPU providers without disrupting internal processes.”
Javier Moreno
Principal Engineer, Shopify
“SkyPilot's flexibility across k8s and neoclouds lets us easily get capacity when we need it - we're hitting 90%+ utilization without any overprovisioning!”
Moin Nadeem
Co-founder & CEO, Phonic
“SkyPilot has enabled our scientists to get up and running quickly, removing the need to wrestle with Kubernetes provisioning, resource tuning, or configuration details. It makes our complex Kubernetes cluster feel accessible and empowers AI researchers - regardless of their k8s experience - to run scalable workloads with confidence.”
Jason Chin
VP, AI Development, Pathos
“We always find ourselves migrating between clouds to find the best deal for our long-running training jobs. SkyPilot has made interoperability across clouds very ergonomic, and our entire team is now scheduling workloads via our centralized SkyPilot deployment. This has saved us countless hours wrestling with manual config and allows us to focus on the actual ML research. Could not recommend enough!”
Eitan Borgnia
COO, Relace
“SkyPilot stands out because it treats governance and cost visibility as first-class concerns. That combination makes it much easier to run large-scale AI workloads responsibly while keeping operational controls and spend in view.”
Jayachander Kandakatla
Senior MLOps Engineer, Ford Credit
“SkyPilot's ease of use and multi-cloud flexibility make it the obvious choice for our AI infrastructure. Our researchers run workloads easily across multiple clouds and on-prem without wrestling with Kubernetes - and when requirements shift, the infra team can pivot cloud vendors in minutes, not months.”
Casper Thuis
Technical Lead, Core AI, TKH Group