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Anyscale is a fully managed AI infrastructure platform powered by Ray, from the creators of open-source Ray. It enables AI builders to run and scale data-intensive ML and AI workloads across multiple clouds with usage-based pricing and enterprise security.
Start here for the decision-making essentials: what Anyscale does, who it is for, how it is accessed, and the first-party sources behind this profile.
Usage-based billing
only pay for what you use with no monthly fixed fees
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Short answers to the questions buyers and builders commonly ask about Anyscale. Each answer cites the shared ledger below, where every source is listed once.
Run and scale data-intensive AI workloads powered by Ray, including distributed training, · Pooled GPUs across clouds, regions, and K8s clusters, dynamically reallocating capacity as · Fine-grained hardware allocation across CPUs, GPUs, TPUs, or accelerator racks like NVL72, · Scales existing AI/ML workloads efficiently via integrations with popular AI/ML libraries
Powered by Ray, Anyscale helps AI builders run data-intensive workloads to build and deploy Foundation Models and AI at scale on any cloud.
AI builders and the best AI teams · AI builders
Anyscale is the infra platform that gives AI builders all the flexibility they need, in the developer experience they want.
Developing and deploying RAG applications · Deploying, operating and scaling a machine learning API
developers who want to learn how to successfully develop and deploy RAG applications
Usage-based billing; only pay for what you use with no monthly fixed fees
Usage-based billing Only pay for what you use, no monthly fixed fees.
Robust APIs and SDKs to automate jobs, cluster management, and CI/CD integration
Robust APIs and SDKs Automate jobs and cluster management or integrate into your CI/CD pipelines with simple, intuitive APIs and SDKs.
Scales existing AI libraries like PyTorch, vLLM, SGLang, and XGBoost with Python APIs acro · Data platforms: MongoDB, Redis, Databricks, Snowflake · Orchestration tools: Prefect, Airflow, Dagster · ML frameworks: Hugging Face, Lightning, PyTorch, Keras
Scale existing AI libraries like PyTorch, vLLM, SGLang, and XGBoost with Python APIs across thousands of nodes.
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Production-scale AI with Ray | Anyscale
Fully managed Ray platform created by the team behind Ray · Powers data-intensive AI workloads including distributed training, multimodal data curatio · Scales PyTorch, vLLM, SGLang, and XGBoost with Python APIs across thousands of nodes
Run and scale data-intensive AI workloads powered by Ray, including distributed training, multimodal data curation, embedding generation, and post-training
Scales existing AI libraries like PyTorch, vLLM, SGLang, and XGBoost with Python APIs across thousands of nodes
Built on Ray, the open-source AI compute engine created by the Anyscale team
Multi-cloud execution across AWS, GCP, Azure, Nebius, or CoreWeave
Usage-based billing; only pay for what you use with no monthly fixed fees
Access controls and authentication including SSO, SAML, SCIM, and audit logs for multi-team security and governance
Three support tiers — Developer (exploratory workloads), Enterprise (production workloads), and Platinum (mission-critical) — with 24x7x365 Severity 1 coverage on Enterprise and Platinum tiers
Anyscale is the team behind Ray, the framework for scaling and productionizing AI applications
A concise view of the jobs, capabilities and integrations described in the recorded product sources.
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Nscale, a full-stack AI cloud platform, entered into a definitive agreement to acquire Anyscale, bringing Anyscale's ~200-person team into Nscale; Anyscale will continue operating under its brand and customers may run its software on Nscale infrastructure over
View source [6]Nscale announced a definitive agreement to acquire Anyscale, combining Nscale's GPU and data-center infrastructure with Anyscale's software layer for AI workloads; Anyscale's ~200-person team joins Nscale while operating under its existing brand.
View source [6]Nscale, a full-stack AI cloud platform, announced a definitive agreement to acquire Anyscale, bringing Anyscale's software layer for distributed AI workloads into Nscale's GPU, data center and power infrastructure stack.
View source [6]Nscale entered a definitive agreement to acquire Anyscale, integrating its distributed AI workload software layer into Nscale's full-stack AI cloud platform. Anyscale's ~200-person team joins Nscale while Anyscale continues operating under its brand.
View source [6]On 30 July 2026, Nscale announced a definitive agreement to acquire Anyscale, adding its AI workload software layer to Nscale's full-stack AI cloud platform; Anyscale's ~200-person team will join Nscale.
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These tools share a workflow, capability or audience with Anyscale. They may complement it rather than replace it, and are not presented as integrations or endorsements.
Pooled GPUs across clouds, regions, and K8s clusters, dynamically reallocating capacity as workload demand shifts
Fine-grained hardware allocation across CPUs, GPUs, TPUs, or accelerator racks like NVL72, with high-throughput distributed communication via Ray's in-memory object store or RDMA
Hosted data processing platform (Platform Services)
Cloud-hosted platform (Platform Services) governed by the Anyscale Platform Terms and Conditions
Scales existing AI/ML workloads efficiently via integrations with popular AI/ML libraries and frameworks
AI builders and the best AI teams
AI infrastructure with flexibility and developer experience for AI builders
Customer and technical support provided to users of the Services
Data platforms: MongoDB, Redis, Databricks, Snowflake
Orchestration tools: Prefect, Airflow, Dagster
ML frameworks: Hugging Face, Lightning, PyTorch, Keras
AI security partners: HiddenLayer, Protect AI, Lakera, Prompt Security, Guardrails AI
Fully managed Ray platform that runs, scales, and monitors AI/ML workloads so developers can ship products without managing infrastructure
Ray (open source distributed computing framework for AI/ML)
Ray was developed at UC Berkeley's RISELab in 2016-2017; Anyscale founded in 2019 as production-ready Ray
Ray is open source; Anyscale offers a fully managed commercial layer on top of it
2019
600 Harrison Street, 4th Floor, San Francisco, CA 94107, USA
Anyscale, Inc.
Make scalable computing effortless
Backed by a16z, NEA, Addition, and Intel Capital
Fully managed cloud infrastructure hosted by Anyscale
Robust APIs and SDKs to automate jobs, cluster management, and CI/CD integration
Grafana dashboards, existing observability stacks, and CI/CD pipelines
Direct access to the engineering team behind Ray for expert consultative support
Powered by Ray
Run and scale all ML and AI workloads
Any cloud and on-premises
AI builders
