---
title: "Anyscale"
description: "Managed platform for Ray, the distributed compute framework"
url: "https://shippin.io/products/anyscale"
---

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# Anyscale

> Managed platform for Ray, the distributed compute framework

| Field | Value |
|---|---|
| Website | https://anyscale.com/ |
| Category | AI |
| Pricing | Paid |
| Launched | 25 September 2026 |
| Upvotes | 0 |
| Builder | [@shippinio](https://shippin.io/users/shippinio.md) |
| Logo | https://img.logo.dev/anyscale.com?token=pk_aazUW6Q3T3mf77KpXTSxcw |
| Cover | https://img.logo.dev/anyscale.com?token=pk_aazUW6Q3T3mf77KpXTSxcw&size=512 |

## About Anyscale

Anyscale is the company behind Ray, the open-source framework for distributed Python and machine learning, and it offers a managed platform for running Ray workloads in production. Ray lets developers scale Python code across a cluster for tasks like distributed training, hyperparameter tuning, batch inference, data processing, and reinforcement learning, using a consistent API instead of stitching together separate systems for each stage. The Anyscale platform adds managed clusters, autoscaling, job orchestration, observability, developer tooling, and optimizations that improve performance and reduce cost relative to self-managed Ray on raw cloud instances. It targets machine learning and AI platform teams that have outgrown single-machine workflows and want to run large training and inference pipelines without operating the underlying distributed infrastructure themselves. Anyscale has invested in serving large language models efficiently, including offerings around fine-tuning and high-throughput inference for open models. Because the platform is built on open-source Ray, teams can develop locally and move to Anyscale for scale without rewriting code, and can fall back to self-hosting if needed. Anyscale is sold as an enterprise platform with usage-based pricing on top of the cloud compute it manages, and is used across industries running production AI and data systems.

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