Anyscale

“Getting to our chemical space of billions of molecules is a non-trivial task. To provide reliable success rates for our customers, we need to filter out reactions that wouldn't work in practice using large-scale inference on billions of reactions. Being able to use multiple cloud providers without overhead and run within our own accounts was essential, especially given patentability concerns in drug discovery.”

“We chose Anyscale not just for what we needed today, but for where we know we’re heading. As our AI workloads grow more complex, Anyscale gives us the infrastructure to scale without limits.”

“Choosing Anyscale was a strategic bet on the future. As Notion AI use cases get more complex, I’m confident that Anyscale can handle it.”

“With Anyscale, we've been able to show people how easy it is to pull a model from Hugging Face and run it ourselves on-prem – it's become a compelling selling point as we advocate for adoption across our search and AI organization.”

“The IDE integration is epic. Anyscale lets me use my preferred tools like VSCode or Cursor on my laptop while still accessing distributed compute power. It's obvious that the Anyscale platform was built by developers for developers.”

“Anyscale gives me confidence in my deployments. If it works in my workspace environment, I know it’ll perform reliably in production as well.”

“With Anyscale, we've achieved 20% better latency compared to our previous solution – all while supporting continued user growth.”

“Anyscale made horizontal scaling easy out of the box. It gave us seamless scalability to keep up with our fast-growing, low-latency inference needs – all without adding operational burden.”

“At Notion, we knew our rapid growth would push our infrastructure beyond its limits. We needed a solution that could scale horizontally with our growth while maintaining strict low-latency performance requirements for our users. Anyscale was the answer.”

“Anyscale gives us the confidence that when we build, it just works. It removes the friction around environment management and scaling, so our teams can focus on delivering fast, intelligent experiences to our users.”

“With 15 engineers processing trillions of pixels per request, Xoople needs infrastructure it can trust at scale. Anyscale provides it, so every engineering hour goes into the product instead of managing infrastructure.”

“As AI moves into the physical world, it needs a trusted, continuously updated view of that world, delivered in a form it can use. That is what we are building, and Anyscale gives us the compute foundation to do it at scale.”

“We are a zero-to-one team building our first product, and Anyscale has let us build a better service and a better architecture, with happier engineers who get to work with tools that excite them.”

“Anyscale isn't just a platform, it's also a team of experts. Their forward deployment engineers spotted that CPU-bound image loading was leaving our GPUs idle and running epochs up to five times slower than they should. They worked side by side with us to tune that handoff, so the GPUs stayed fed. That kind of hands-on partnership is what drives real cost-efficiency gains in our business.”

“Anyscale Jobs packages our code and handles the whole run for us: spinning up a cluster, loading and running the data, writing the output, and tearing it down when the job is finished. With Anyscale, we can do this for multiple jobs, all running in parallel, without needing to directly manage compute or orchestration.”

“Partnering with Anyscale means every engineering hour we have goes into the product, and that is exactly where those hours belong.”

“With Anyscale, we can tap into on-demand A100 and H100 capacity across clouds to support our expanding R&D efforts and the growing volume of training runs they require.”

“GPU availability in the cloud is quite scarce and a primary bottleneck for us, as we needed access to premium GPUs like H100s on-demand. The ability to implement a multi-cloud solution has been instrumental in accelerating our AI development.”

“Our customers are extremely sensitive about their data. Anyscale lets us run distributed training in our own cloud environment, so we can keep our customers’ data in our own hands.”

“By offloading Ray cluster operations to Anyscale, our engineers can concentrate on pushing the boundaries of physical AI rather than managing distributed compute infrastructure.”

“Using Anyscale as our multi-cloud Ray cluster manager, we’ve made our training runs fully portable across hyperscalers and specialized cloud providers, maximizing GPU availability.”

“We had these new robotic behaviors we needed to onboard onto our product to meet rising customer demand, but the AI infrastructure that got us here couldn’t scale to handle the more complex models we needed for the next phase.”

““Anyscale enables us to push the boundaries of what’s possible in generative AI by giving us the flexibility to scale workloads seamlessly. This removes the risk around our infrastructure and allows our team to focus on innovation rather than infrastructure bottlenecks.””

“Before, sellers would take 28 days to fully onboard. With Catalog Transformer and Anyscale, we reduced that to just a few hours in most cases.”

“With GitHub Actions and the Anyscale CLI, we could deploy Ray clusters as code and manage three isolated environments for dev, test, and production. It gave our data scientists the autonomy they needed.”