Anyscale

A platform for scaling distributed AI workloads including training, data curation, and embeddings using Ray.

Venture Funded$102MSeries CAndreessen HorowitzAmplify PartnersFoundation Capital

distributed computingmachine learningscalabilityenterprise security

About

Anyscale is a platform built on Ray for scaling distributed AI workloads. The vendor describes capabilities for multimodal data curation across videos, images, text, and audio; distributed model training across GPU clusters with elastic scaling and GPU observability; batch embedding generation for search, retrieval, or training; and post-training with frameworks like SkyRL and veRL. The platform supports existing AI libraries including PyTorch, vLLM, SGLang, and XGBoost with Python APIs across thousands of nodes. Features include fine-grained hardware allocation for different CPUs, GPUs, TPUs, or accelerator racks like NVL72; in-memory distributed object store or direct transport over RDMA for communication; pooled GPUs that dynamically reallocate capacity; and multi-cloud execution across AWS, GCP, Azure, Nebius, and CoreWeave. The vendor states the platform includes access controls and authentication including SSO, SAML, SCIM, and audit logs. Ray, which powers Anyscale, reports 500M+ downloads, 41K+ GitHub stars, and 1.2k+ contributors.

Read from anyscale.com on 2026-08-26. We describe what the vendor states; we do not audit it.

Enterprise Readiness

from cataloged data

67/100 · Strong

Security & ComplianceNot disclosed

No compliance certifications listed

Deployment FlexibilityStrong

Flexible deployment: Cloud, Hybrid, Self-Hosted

Integration DepthStrong

8 documented integrations

Proven AdoptionPartial

5 documented use cases

Company MaturityStrong

Founded 2019 · Series C

Composite of public compliance, deployment, integration, adoption, and company signals. “Not disclosed” reflects gaps in available data, not a vendor deficiency.

Independently sourced

Pulled directly from regulator filings and platform APIs. No vendor or editorial input.

Activity classifier

Active

last GitHub commit 0d ago

GitHub API2026-05-27

anyscale

Open source product· 637★· Apache-2.0· active 3mo ago

Python · Jupyter Notebook · HCL · Go Template

falling · -4★ (-0.6%) 30d

OSV vulnerability feed2026-08-24

No known advisories

Enterprise Use Cases

Distributed model training

AI workload orchestration

Scalable data processing

Real-time ML inference

Enterprise AI governance

Integrations

AWSAzureGoogle CloudKubernetesTensorFlowPyTorchMLflowDatabricks

How Anyscale compares

Tool	Readiness	Pricing	Deployment	Compliance	Integrations
Anyscale	67 · Strong	Enterprise	Cloud, Hybrid, Self-Hosted	—	8
Groq	Not scored	Enterprise	Cloud, On-Premise, Hybrid, Self-Hosted	—	8
Weights & Biases W&B	Not scored	Freemium	Cloud, On-Premise, Hybrid, Self-Hosted	—	8
Comet ML Platform	70 · Strong	Enterprise	Cloud, On-Premise, Hybrid, Self-Hosted	—	8

Peers from the same category, ranked by Enterprise Readiness. Readiness is a composite of cataloged compliance, deployment, integration, adoption, and company signals.

Frequently Asked Questions

What is Anyscale used for?

Anyscale is a platform for scaling distributed AI workloads including training, data curation, and embeddings using Ray. It is commonly used for distributed model training, ai workload orchestration, scalable data processing, and real-time ml inference.

Is Anyscale free, and how is it priced?

Anyscale uses enterprise pricing, typically a custom quote based on seats, usage, and requirements. Contact the vendor for a quote.

How can Anyscale be deployed?

Anyscale supports Cloud, Hybrid, and Self-Hosted deployment. On-premise and self-hosted options support data-residency and air-gapped requirements.

What does Anyscale integrate with?

Anyscale documents 8 integrations, including AWS, Azure, Google Cloud, Kubernetes, TensorFlow, and PyTorch.

When was Anyscale founded?

Anyscale was founded in 2019 and has raised $102M in funding.

Is Anyscale enterprise-ready?

Based on cataloged data, Anyscale has an Enterprise Readiness score of 67/100 (Strong tier), derived from its compliance, deployment, integration, adoption, and company-maturity signals.

Quick Facts

PricingEnterprise

DeploymentCloud, Hybrid, Self-Hosted

Founded2019

Funding$102M

CategoryData & MLOps

Procurement

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