Announcing SkyPilot Platform and our $20M funding | SkyPilot
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li]:!relative [&_ul>li]:!pl-4 [&_ul>li]:before:!absolute [&_ul>li]:before:!top-[0.75em] [&_ul>li]:before:!left-0 [&_ul>li]:before:!block [&_ul>li]:before:!h-[5px] [&_ul>li]:before:!w-[5px] [&_ul>li]:before:!-translate-y-1/2 [&_ul>li]:before:!transform [&_ul>li]:before:!rounded-[1px] [&_ul>li]:before:!bg-black [&_ul>li]:before:!content-[''] [&>p:first-child]:!mt-0 prose-td:border-b prose-td:!border-t-0 prose-tr:!border-b-0 prose-td:border-grey-200 [&_code]:before:!content-none [&_code]:after:!content-none prose-p:text-18px prose-ul:text-18px prose-ol:text-18px prose-blockquote:!text-18px [&_h1]:mx-auto [&_h1]:lg:max-w-[780px] [&_h2]:mx-auto [&_h2]:lg:max-w-[780px] [&_h3]:mx-auto [&_h3]:lg:max-w-[780px] [&_p]:mx-auto [&_p]:lg:max-w-[780px] lg:prose-ul:max-w-[780px] prose-ul:mx-auto [&>div]:mx-auto [&>div]:lg:max-w-[780px] [&>blockquote]:mx-auto [&>blockquote]:lg:max-w-[780px] lg:prose-ol:max-w-[780px] prose-ol:mx-auto">p:first-child]:!mt-0">Every hour an AI team spends fighting infrastructure is an hour the frontier doesn't move.<br>Today, SkyPilot is out of stealth. We help frontier AI teams build intelligence faster by removing their biggest bottleneck: AI compute fragmentation.<br>Custom intelligence is stalled by fragmented AI compute #<br>Shortly before ChatGPT's release, I was a PhD researcher at Berkeley in the lab that incubated Databricks and Spark, running lots of training jobs on GPUs from AWS. We used AWS because they gave our lab free compute.<br>The problem was, everyone in the lab was using AWS, too. The lucky ones sometimes got GPUs. The unlucky got no-capacity errors. It was our first glimpse into the GPU shortage.<br>Our lab did receive credits from other providers. GCP, Azure, and some unknown "specialized clouds" (we call them AI neoclouds now). No one used them. Each provider's setup was a 10-step wiki page no one wanted to follow. New concepts, new APIs, but the worst part was migrating our precious workloads and state. It's too complicated.<br>We wanted to use one system to manage all our AI compute. Not five.<br>So we started building it in open source. We called it SkyPilot. We asked: Can we build a system to unify all our compute into a single pool — a "sky" of cloud compute?
Fast forward to 2026, SkyPilot is used by hundreds of companies. Working with them, it became clear the problem we saw is now orders-of-magnitude more severe in industry.<br>Since GPU demand far outpaces supply, AI teams have to get GPUs anywhere they can. They then firefight fragmented compute — three hyperscalers, six neoclouds, a dozen Kubernetes clusters, many accelerator SKUs. Researchers burn time on siloed workload setup (yes, migrating workloads or state is still a pain). Infra gets paged when GPUs go down. Frontier AI teams move slowly even on the fastest compute ever built.<br>Companies put up with this because they have to build custom intelligence — agents, apps, and models that are trained on each company's data, workflows, and knowledge. Intelligence only they can build. Intelligence that beat closed models on quality and cost.<br>We believe the next winners in AI will win by custom intelligence. They will control their AI stack: their compute, data, and intelligence. They will need more compute. Not less.<br>To accelerate building custom intelligence for every organization, an open, provider-agnostic AI compute layer capable of running frontier workloads is needed.<br>We built SkyPilot for this reality.<br>Turning fragmented compute into one AI supercomputer #<br>SkyPilot is a control plane that turns fragmented compute into one "AI supercomputer". It abstracts your AI compute — across neoclouds or hyperscalers — into one pool of resources, so they can be centrally managed and efficiently used.
While SkyPilot started as a research-y open source project, it's now running a meaningful share of AI compute across hundreds of leading companies:<br>Top deployments surged past 1,000+ nodes and 10,000+ GPUs<br>GPU hours consumed on SkyPilot grew 35% MoM, 6x in last 6 months<br>14M+ downloads (~6M in last 3 months alone)<br>280+ contributors<br>SkyPilot is BYOC (Bring Your Own Compute). It offers native support for most AI workloads: interactive development, jobs, batch inference, evals, large-scale training, and RL. All workloads run on your compute, with your frameworks of choice.<br>Frontier teams use SkyPilot to build custom intelligence #<br>Hundreds of leading organizations already run on SkyPilot — from top neolabs to Fortune 500 enterprises. They're building custom intelligence that leads their vertical, with some users seeing 10x faster time-to-intelligence and double-digit increase in GPU utilization.<br>Abridge is defining the standard for AI in healthcare, trusted by 300+ major health systems in the US. With SkyPilot, they achieved 10x faster AI experimentation:<br>"SkyPilot is easy to setup, light weight to use and configurable in just the right places. We can now...